US 10778989

An analysis of U.S. Patent 10,778,898 reveals the following details. There is no public record of this patent being involved in any legal disputes before the Court of Appeals for the Federal Circuit (CAFC) in 2026.

Summary of U.S. Patent 10,778,989

• Title: Rolling intra prediction for image and video coding
• Assignee: As of the latest records, the assignee is Malikie Innovations Ltd. The original assignee was BlackBerry Ltd.
• Inventors: Dake He
• Filing Date: February 5, 2016
• Issue Date: September 15, 2020
• Abstract: The patent describes methods and devices for image and video compression that use a technique called "rolling intra prediction." An encoder selects a specific mode for a block of pixels, which is associated with a prediction function. A predicted version of the block is then created. Initially, some pixels are predicted using data from neighboring, already-coded blocks. Subsequently, other pixels in the same block are predicted using the pixel data that was just predicted. This process continues in a defined "traversing order," essentially using the block's own predicted data to complete the prediction. The decoder then uses the same process to create an identical prediction to reconstruct the image.

Plain-Language Overview of Independent Claims

The patent's independent claims establish the core legal protection for the invention. They can be understood as follows:

• Claim 1: A Method for Decoding an Image
  This claim protects the overall process of decoding a block of an image or video. A decoder reads a "mode" from the compressed data stream for a particular block. This mode dictates a "traversing order" (the path the decoder takes through the pixels) and a "template" (which nearby pixels to use for prediction). The key innovation is that after using pixels from adjacent, already decoded blocks to predict the first few pixels, the decoder then uses these newly predicted pixels to predict the next ones within the same block. This "rolling" process continues until the block is fully predicted. This predicted block is then added to the received error data (the "residual") to perfectly reconstruct the original block.

• Claim 8: A Decoder for an Image
  This claim provides protection for the physical device that carries out the method described in Claim 1. This could be a set-top box, a smartphone, or any device with a processor and memory. The claim specifies that the device is configured by a decoding application to perform the steps of reading the mode, selecting the template and traversing order, and building the predicted block using the rolling prediction technique before adding the residual to reconstruct the block.

• Claim 9: A Non-Transitory Processor-Readable Medium for Decoding
  This claim protects the software that performs the decoding. It covers the computer-executable instructions stored on a physical medium (like a hard drive, flash memory, or server) that, when run, cause a processor to execute the decoding method outlined in Claim 1.

• Claim 10: A Method for Encoding an Image
  This claim mirrors the decoding method but from the perspective of the encoder that creates the compressed file. The encoder selects the most efficient "mode" for a block of pixels. It then generates a predicted block using the exact same rolling prediction technique as the decoder—using neighboring block data initially and then its own newly predicted pixels. The encoder then subtracts this predicted block from the original, creating the "residual" data. Finally, it packages this residual data and the selected mode into the bitstream to be sent to the decoder.

• Claim 17: An Encoder for an Image
  This protects the physical encoding device. Similar to the decoder claim, this covers a device with a processor and memory that is configured by an encoding application to perform the steps of selecting a mode, constructing a predicted block with the rolling technique, calculating the residual, and outputting the compressed bitstream.

• Claim 18: A Non-Transitory Processor-Readable Medium for Encoding
  This claim protects the encoding software itself, covering the instructions stored on a physical medium that direct a processor to perform the encoding method described in Claim 10.

I have high confidence in this analysis as the information is directly sourced from the provided full patent text. The search for CAFC docket information is current as of today's date.

As of April 26, 2026, there is no known litigation involving US patent 10,778,989.

A thorough search of patent litigation databases, including the Unified Patents portal, and federal court records via PACER and CAFC dockets, reveals no instances of US patent 10,778,989 being asserted in a lawsuit.

While the current assignee, Malikie Innovations Ltd., and the original assignee, BlackBerry Ltd., are involved in various patent litigation matters, none of the publicly available documents from these searches specifically name US patent 10,778,989 as a subject of dispute. Malikie Innovations, a subsidiary of Key Patent Innovations Ltd., has been actively litigating other patents from the portfolio of approximately 32,000 patents it acquired from BlackBerry in May 2023. These campaigns have targeted companies across various technology sectors. However, the '989 patent has not been identified in these actions.

Proceedings overview

There are no AIA trial proceedings on file for U.S. Patent 10,778,989 as of today's date, May 29, 2026. This indicates that the patent has not been challenged through Inter Partes Review (IPR), Post-Grant Review (PGR), or Covered Business Method (CBM) proceedings at the Patent Trial and Appeal Board (PTAB).

Strategic summary

Currently, all claims (1-18) of U.S. Patent 10,778,989 remain untested by PTAB proceedings. No claims have been canceled or narrowed through IPR, PGR, or CBM. The estoppel landscape is entirely open, meaning potential petitioners are not barred from raising any prior art grounds they could reasonably assert. There are no patterns of repeated challenges by the same petitioner or aggressive appeals by the patent owner to consider, as no proceedings have occurred.

Recommended next steps

Since no PTAB activity exists for U.S. Patent 10,778,989, a potential defendant facing assertion of this patent should consider the absence of prior challenges as a significant signal. Well-asserted patents often eventually attract IPRs. A defendant should perform a thorough prior art search to identify potential grounds for an IPR or PGR challenge, evaluating the claims against relevant prior art that may not have been considered during original prosecution. This proactive step can inform a robust defense strategy, should the patent be asserted.

Inventors

• Dake He: At the time of filing (February 5, 2016), Dake He was employed by the original assignee, BlackBerry Ltd. There are no unusual patterns, such as a mass departure of inventors, associated with this filing.

Original assignee

• BlackBerry Ltd.: BlackBerry was the original assignee of the patent. At the time of filing, the company was transitioning from its legacy hardware business (smartphones) to a focus on enterprise software and services, including cybersecurity, endpoint management, and IoT solutions. While video encoding/decoding is relevant to secure communications, it is unlikely that BlackBerry shipped a specific commercial product that directly embodied the novel claims of this patent, as their primary business had shifted away from media-centric consumer devices. BlackBerry remains an operating company today, focused on its software and services business.

Assignment timeline

• 2016-02-05 (executed) / recorded 2016-02-05 — Reel 037965/0622

  • Conveyance: Assignment of Assignors Interest
  • Assignor: He, Dake (Inventor)
  • Assignee: BLACKBERRY LIMITED
  • Correspondent: Stephen B. Ackerman, The Law Office of Stephen B. ACKERMAN, 4016 Flowers Road, Suite 450A, Atlanta, GA 30360
  • Context: Standard assignment from inventor to employer at the time of filing.

• 2023-04-27 (executed) / recorded 2023-05-02 — Reel 063471/0474

  • Conveyance: Assignment of Assignor's Interest
  • Assignor: BLACKBERRY LIMITED
  • Assignee: OT PATENT ESCROW, LLC
  • Correspondent: Michael T. Renaud, Mintz Levin Cohn Ferris Glovsky and Popeo PC, One Financial Center, Boston, MA 02111
  • Context: First step in a portfolio fire-sale, moving patents into an intermediary holding company as part of a large-scale divestment.

• 2023-06-16 (executed) / recorded 2023-06-20 — Reel 064015/0001

  • Conveyance: Nunc Pro Tunc Assignment
  • Assignor: OT PATENT ESCROW, LLC
  • Assignee: MALIKIE INNOVATIONS LIMITED
  • Correspondent: Marc A. Fenster, Russ August & Kabat, 12424 Wilshire Blvd, 12th Floor, Los Angeles, CA 90025. This correspondent is a well-known patent litigation attorney, frequently representing assertion entities.
  • Context: Second step of the portfolio sale, transferring the patent from the escrow entity to the ultimate assertion-focused owner.

• 2023-06-19 (executed) / recorded 2023-06-20 — Reel 064015/0010

  • Conveyance: Nunc Pro Tunc Assignment
  • Assignor: BLACKBERRY LIMITED
  • Assignee: MALIKIE INNOVATIONS LIMITED
  • Correspondent: Marc A. Fenster, Russ August & Kabat, 12424 Wilshire Blvd, 12th Floor, Los Angeles, CA 90025. This is the same recurrent correspondent from the immediately preceding assignment.
  • Context: A "belt and suspenders" assignment directly from the original seller to the final buyer to clean the chain of title and ensure legal standing for future litigation.

• 2023-09-05 (recorded) — Reel 065261/0411 & 065261/0415

  • Conveyance: Corrective Assignment
  • Assignors: BLACKBERRY LIMITED; OT PATENT ESCROW, LLC
  • Assignees: OT PATENT ESCROW, LLC; MALIKIE INNOVATIONS LIMITED
  • Correspondents: Mintz Levin; Russ August & Kabat
  • Context: Administrative corrections filed to fix clerical errors in the earlier assignment documents, reaffirming the BlackBerry → OT Patent Escrow → Malikie Innovations transfer chain.

Timeline diagram

timeline
    title Ownership of US 10778989
    2016 : Filed by Dake He
         : Assigned to BlackBerry Ltd
    2020 : Patent Issued
    2023 : Assigned to OT Patent Escrow LLC
         : Assigned to Malikie Innovations Ltd
         : Corrective assignments recorded

NPE / troll-pattern signals

1. Shell-entity transfer — Present. The patent was transferred from BlackBerry Ltd., an operating company, to OT Patent Escrow, LLC, and subsequently to Malikie Innovations Limited. Per the litigation summary, Malikie Innovations is a subsidiary of Key Patent Innovations Ltd., an Irish entity focused on monetizing the ex-BlackBerry portfolio. These entities do not produce products and exist for licensing and assertion. (Reels 063471/0474 and 064015/0001).

2. Known asserter in the chain — Present. The current assignee, Malikie Innovations Limited, is a subsidiary of Key Patent Innovations Ltd., which is publicly identified by sources like Unified Patents as a significant patent asserter. It has initiated litigation campaigns using other patents from the acquired BlackBerry portfolio. (Reel 064015/0001).

3. Repeat correspondent across the chain — Present. Marc A. Fenster of Russ August & Kabat is the correspondent for two key transfers to the final assignee, Malikie Innovations Limited. This firm and attorney are well-known for representing patent assertion entities in litigation. (Reels 064015/0001 and 064015/0010).

4. Cascading transfers — Present. The patent was transferred from BlackBerry to OT Patent Escrow on 2023-04-27 and then from OT Patent Escrow to Malikie Innovations on 2023-06-16, a period of less than two months. This rapid, multi-step transfer through a special-purpose escrow entity to a final assertion vehicle is a classic pattern for portfolio monetization.

5. Pre-litigation transfer — Not present. As of today's date, no litigation has been filed asserting this patent, so this signal is not triggered.

6. Bankruptcy fire-sale — Not present. The sale was a strategic divestment by BlackBerry of non-core patent assets, not part of a formal bankruptcy proceeding.

7. Privateering — Present. An operating company, BlackBerry, sold a large portfolio of its patents to a non-practicing entity, Key Patent Innovations (via Malikie), which is now asserting those patents against competitors in the technology industry. This fits the definition of privateering, where an operating company offloads patents for assertion by a third party.

8. Defensive aggregator (anti-NPE) — Not present. The chain terminates at an assertion entity, not a defensive aggregator.

Verdict

• NPE — high confidence

This verdict is based on multiple strong, corroborating signals. The patent was transferred from an operating company (BlackBerry) through a series of rapid, cascading assignments to Malikie Innovations Limited, a subsidiary of the known patent assertion entity Key Patent Innovations (Reels 063471/0474 and 064015/0001). This transfer fits the pattern of privateering and the use of shell or special-purpose entities. Furthermore, the final assignments were handled by a correspondent attorney and law firm known for representing NPEs, providing additional confirmation of the intent to monetize this patent through licensing and litigation.

A direct link to the search results can be found at the USPTO Patent Assignment Search page.

Based on the patent documentation for US 10,778,989, the following prior art references were cited by the USPTO during prosecution.

Analysis of Cited Prior Art

The following patent documents were considered by the examiner in determining the patentability of the '989 patent's claims. An analysis of their potential to anticipate the independent claims under 35 U.S.C. § 102 is provided. For a reference to anticipate a claim, it must disclose, either explicitly or inherently, every single element and limitation of that claim.

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1. U.S. Patent Application Publication No. US 2010/0111175 A1

• Full Citation: US 2010/0111175 A1, "Reference data buffer for intra-prediction of digital video"
• Inventor: Wen-Shan Wang
• Publication Date: May 6, 2010 (Filed March 31, 2005)
• Brief Description: This patent application describes a method for managing reference data used in intra-prediction for video coding. It proposes a dedicated reference data buffer to store reconstructed reference pixels from neighboring blocks (i.e., the row above and the column to the left of the current block). This buffer allows for efficient access to the reference data needed to generate a prediction for the current block, and it can be updated as new blocks are reconstructed. The focus is on the efficient storage and retrieval of reference pixels from adjacent, previously coded blocks.
• Anticipation Analysis:
  • This reference does not appear to anticipate the independent claims (1, 8, 10, 17) of the '989 patent. The core inventive concept of the '989 patent is the "rolling" prediction method, where predicted pixels from the current block are used as inputs to predict other pixels within the same block.
  • Wang, in contrast, describes a conventional intra-prediction data flow. The prediction for the entire current block is based on a static set of reference samples that are drawn exclusively from neighboring, previously reconstructed blocks. There is no disclosure of a mechanism where a predicted pixel value is immediately turned around and used as a reference for a subsequent pixel prediction within the same block's prediction-generation process.
  • Therefore, Wang is missing the key claim element: "determining at least some other of the predicted pixels based on the prediction function... with the at least some of the predicted pixels as inputs" (Claim 1).

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2. U.S. Patent Application Publication No. US 2007/0053433 A1 & European Patent Application No. EP 1761063 A2

These two documents belong to the same patent family and disclose the same invention.

• Full Citation: US 2007/0053433 A1, "Method and apparatus for video intraprediction encoding and decoding"
• Assignee: [[Samsung Electronics Co.](/litigations/by-defendant/Samsung%20Electronics%20Co.), Ltd.](/litigations/by-plaintiff/Samsung%20Electronics%20Co.%2C%20Ltd.)
• Publication Date: March 8, 2007 (Filed September 6, 2005)
• Brief Description: This Samsung application details an intra-prediction method where a prediction block is generated by extrapolating pixel values from reference samples in adjacent blocks. The method involves selecting one of several available intra-prediction modes. For each pixel in the current block, a prediction value is generated based on one or more of the reference samples from the neighboring blocks, according to the direction specified by the selected mode. The disclosure also mentions using adaptive filtering on the reference samples to improve prediction quality.
• Anticipation Analysis:
  • This reference does not appear to anticipate the independent claims of the '989 patent for reasons similar to the Wang reference. The methodology described by Samsung follows the established intra-prediction paradigm where the entire predicted block is generated using reference samples located outside of that block (i.e., from previously reconstructed neighboring blocks).
  • The claims of the '989 patent require a recursive or "rolling" process where the set of available reference samples dynamically grows to include the very pixels being predicted within the current block. Samsung's disclosure does not describe this. It teaches generating a prediction for each pixel in the current block based solely on the external, pre-existing reference samples.
  • Thus, Samsung is also missing the crucial claim element of using predicted pixels from the current block as inputs for determining other predicted pixels in the same block.

Conclusion

The prior art cited by the USPTO examiner establishes the technological context for intra-prediction in video coding as of the '989 patent's priority date. Both the Wang and Samsung references disclose systems that create predicted blocks using reference samples from adjacent, already-coded blocks. However, neither reference discloses the specific, novel technique claimed in US 10,778,989: constructing the predicted block in a "rolling" fashion where the prediction process uses its own output (predicted pixels) as input to continue generating the remainder of the predicted block. This missing element is central to all independent claims of the '989 patent, and therefore, these references do not anticipate the claims under 35 U.S.C. § 102.

Based on the provided prior art analysis, here is an analysis of the obviousness of US patent 10,778,989 under 35 U.S.C. § 103.

Obviousness Analysis (35 U.S.C. § 103)

An invention is considered obvious if the differences between the invention and the prior art are such that the invention as a whole would have been obvious at the time of invention to a person having ordinary skill in the art (PHOSITA). This analysis considers whether a PHOSITA would have been motivated to combine or modify existing prior art references to arrive at the claimed invention with a reasonable expectation of success.

For the purpose of this analysis, a PHOSITA in the field of video coding circa 2016 would be an engineer or computer scientist with a degree in a relevant field and practical experience with video compression standards like H.264/AVC and H.265/HEVC. This individual would be intimately familiar with block-based predictive coding, including various intra-prediction modes and the goal of minimizing the prediction residual to achieve higher compression efficiency.

The core inventive concept of US 10,778,989, as distinguished from the cited prior art, is the "rolling intra prediction" mechanism. This involves using newly predicted pixels within a block as reference samples for predicting subsequent pixels in the same block. The cited references, Wang (US 2010/0111175 A1) and Samsung (US 2007/0053433 A1), both teach the conventional method where the prediction for an entire block is based exclusively on a static set of reference samples from adjacent, previously reconstructed blocks.

An argument for the obviousness of the independent claims of the '989 patent could be constructed as follows:

Combination of Prior Art: Samsung (US 2007/0053433 A1) in view of the knowledge of a Person Having Ordinary Skill in the Art (PHOSITA).

1. Base Reference: Samsung (US 2007/0053433 A1)

Samsung provides a strong foundation, teaching most of the elements claimed in the '989 patent:

• A method for encoding/decoding an image partitioned into blocks.
• Selecting an intra-prediction mode for a current block.
• Using neighboring reference samples (from adjacent, previously coded blocks) to generate a predicted block.
• Determining a residual by subtracting the predicted block from the original.
• Encoding the residual and the selected mode into a bitstream.
• Reconstructing the block at the decoder by adding the predicted block and the decoded residual.

The key element missing from Samsung is the rolling prediction step: "determining at least some other of the predicted pixels based on the prediction function... with the at least some of the predicted pixels as inputs" (Claim 1).

2. Motivation to Modify Samsung

A PHOSITA would have been motivated to modify the method taught by Samsung to solve a well-known problem inherent in conventional directional intra-prediction. The '989 patent itself articulates this problem in its background section: "directional prediction may introduce discontinuity along the direction that is perpendicular to the given angle. Since such discontinuity is introduced by the prediction process... it needs to be compensated in the residual block... [which] translates into non-zero coefficients at medium or high frequency positions... [that] are difficult to code".

A PHOSITA, tasked with improving compression efficiency, would seek to minimize these prediction-induced artifacts to create a "cheaper" residual to encode. They would recognize that as prediction moves further away from the reference samples at the block's edge, the prediction quality degrades, increasing the likelihood of such discontinuities.

The logical and intuitive solution to improve the prediction's internal consistency and smoothness would be to use the most relevant and proximate information available. As each new pixel in the block is predicted, its value represents the best available estimate for that location. It would be an obvious step for a PHOSITA to leverage this new information immediately, using the just-predicted pixel as a reference for its neighbors, rather than continuing to rely solely on the more distant reference samples at the block's edge. This modification directly addresses the problem of propagating a pattern smoothly across a block.

3. Reasonable Expectation of Success

A PHOSITA would have a high expectation that this modification would succeed. In signal and image processing, using locally generated data to inform the generation of subsequent data is a fundamental principle for ensuring continuity. By building the prediction block pixel-by-pixel (or row-by-row) in a defined "traversing order" and using the fresh output as input, the prediction would naturally become smoother. This would reduce the high-frequency artifacts in the residual, leading directly to better compression performance—the precise goal of the PHOSITA. The modification is not a leap into the unknown, but an application of known engineering principles to solve a known problem.

Conclusion on Obviousness

While the cited prior art from Wang and Samsung does not explicitly disclose the "rolling intra prediction" technique, an argument can be made that the '989 patent's claims would have been obvious to a PHOSITA. The Samsung reference teaches nearly all elements of the claimed invention. The sole inventive concept—the rolling prediction—represents a modification that a PHOSITA would have been motivated to make to solve the known problem of prediction-induced discontinuities inherent in Samsung's method. This modification would have been seen as a logical step with a reasonable expectation of improving prediction quality and, consequently, overall compression efficiency. Therefore, the independent claims of US 10,778,989 are vulnerable to an obviousness challenge under 35 U.S.C. § 103.

Term, Application History, and Family for U.S. Patent 10,778,989

An analysis of the records for U.S. Patent 10,778,989 from the U.S. Patent and Trademark Office (USPTO) provides the following details regarding its term, related applications, and patent family.

Patent Term and Expiration

• Patent Term Adjustment (PTA): There is no record of any Patent Term Adjustment granted to this patent. PTA is used to extend a patent's term to compensate for certain delays caused by the USPTO during prosecution. The absence of PTA indicates that no such qualifying delays were recorded.

• Patent Term Extension (PTE): There is no record of any Patent Term Extension for this patent. PTE is typically granted to compensate for regulatory review delays (e.g., by the FDA) and does not apply to this technology.

• Projected Expiration Date: The term of a U.S. patent filed after June 8, 1995, is twenty years from the earliest non-provisional application filing date. U.S. Patent 10,778,989 was filed on February 5, 2016, and does not claim priority to any earlier non-provisional applications. Therefore, the projected expiration date is February 5, 2036. This date is based on the standard 20-year term and assumes all required maintenance fees are paid on time.

Application and Family History

• Continuation or Divisional Applications: A review of the patent's continuity data shows that U.S. Patent 10,778,898 is not a continuation or divisional of any prior U.S. application, nor have any continuation or divisional applications been filed claiming priority to it.

• Patent Family Members: This U.S. patent is part of a small international patent family, indicating that protection for this invention was sought in other jurisdictions. The known family members that claim priority to the original U.S. application (15/016,887) are:

  • European Patent Application: EP3209019A1
  • European Patent Application: EP4618536A1

These applications indicate an effort to protect the "Rolling intra prediction for image and video coding" invention within the member states of the European Patent Organisation.

Defensive Disclosure: Rolling Intra-Prediction Enhancements and Cross-Domain Applications

Publication Date: April 26, 2026
Reference Patent: US 10,778,989 ("the '989 patent")
Field: Digital Data Compression, Image and Video Coding, Signal Processing

This document discloses novel enhancements, applications, and combinations related to the "rolling intra prediction" methods described in US patent 10,778,989. The purpose of this disclosure is to place these concepts into the public domain, thereby establishing prior art against future patent applications claiming these or similar incremental innovations.

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Derivative Variations on Core Claims

The following disclosures are derivative works based on the independent claims of the '989 patent.

Axis 1: Material & Component Substitution

Derivative 1.1: Neuromorphic Predictive Coding

• Enabling Description: The prediction function, defined in the '989 patent as a linear weighted function, is replaced with a low-power Spiking Neural Network (SNN) implemented on a neuromorphic co-processor (e.g., an Intel Loihi or IBM TrueNorth architecture). The SNN is pre-trained to recognize textural and edge patterns. During encoding/decoding, the "mode" selects a specific pre-trained SNN model. The inputs to the SNN are not pixel intensity values but are instead temporal spike trains converted from the reference pixel intensities. The SNN's output spike train is then converted back into a predicted pixel value. This substitution replaces conventional arithmetic logic units (ALUs) with specialized, energy-efficient neuromorphic hardware, achieving the same predictive function with substantially lower power consumption.
• Mermaid Diagram:

  graph TD
      A[Reference Pixels] --> B(Pixel-to-Spike Converter);
      B --> C{Spiking Neural Network};
      D[Mode Selection] --> C;
      C --> E(Spike-to-Pixel Converter);
      E --> F[Predicted Pixel];
      F -- feeds back as input --> A;
  

Derivative 1.2: Logarithmic Domain Prediction

• Enabling Description: All pixel-level calculations for the prediction function are performed in the logarithmic domain instead of the linear domain. Reference and predicted pixel values are first converted to a logarithmic representation (e.g., base 2). The prediction function then becomes a series of additions and subtractions, which are computationally cheaper than the multiplications required by weighted-average functions in the linear domain. The final predicted value is converted back to the linear domain via an exponentiation operation. This is particularly effective for hardware with limited multiplier resources, such as low-cost microcontrollers.
• Mermaid Diagram:

  flowchart LR
      subgraph Logarithmic Prediction Module
          A[Input Pixels] --> B{Logarithmic Converter};
          B --> C[Log-Domain Prediction Function];
          C --> D{Exponential Converter};
          D --> E[Output Predicted Pixel];
      end
      E -- rolling input --> A;
  

Derivative 1.3: Ternary and Quaternary Coefficient Prediction

• Enabling Description: The prediction function's weighting factors are constrained to a ternary (-1, 0, 1) or quaternary (-2, -1, 1, 2) set. This eliminates the need for floating-point or complex integer multipliers. The prediction calculation is reduced to a series of register shifts (for powers of 2) and additions/subtractions. The encoder selects the mode that provides the best rate-distortion performance using this constrained coefficient set, slightly trading prediction accuracy for a significant reduction in computational complexity.
• Mermaid Diagram:

  sequenceDiagram
      participant Encoder
      participant PredictionEngine
      Encoder->>PredictionEngine: Select Mode (Ternary Coefficients)
      PredictionEngine->>PredictionEngine: p(x,y) = ref(x-1,y) - ref(x-1,y-1)
      PredictionEngine-->>Encoder: Predicted Block
  

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Axis 2: Operational Parameter Expansion

Derivative 2.1: Gigapixel Image Tiling Prediction

• Enabling Description: For processing gigapixel-scale images (e.g., satellite imagery, digital pathology), the rolling intra-prediction is applied to macro-tiles (e.g., 8192x8192 pixels). The traversing order is defined by a Hilbert space-filling curve to maintain spatial locality. To manage memory, only a "rolling buffer" of the N most recently predicted rows and the M most recently predicted pixels in the current row are kept in active memory. This allows the prediction to propagate across massive image tiles with a fixed memory footprint, operating at an industrial scale.
• Mermaid Diagram:

  stateDiagram-v2
      [*] --> TraversingTile
      TraversingTile --> PredictingPixel: Next pixel in Hilbert curve order
      PredictingPixel --> UpdatingBuffer: Store predicted pixel
      UpdatingBuffer --> PredictingPixel: Use buffered pixels for next prediction
      UpdatingBuffer --> TraversingTile: If end of row/column
  

Derivative 2.2: Cryogenic Sensor Data Compression

• Enabling Description: The rolling intra-prediction algorithm is implemented on an FPGA situated in a cryogenic environment (e.g., < 77 Kelvin) for compressing data from superconducting quantum sensors or deep-space telescopes. At these temperatures, thermal noise in the pixel data is minimal and exhibits different statistical properties. The prediction functions are optimized for this low-noise environment, using higher-order predictors that would be ineffective with room-temperature sensor data. The traversing order is aligned with the sensor's electronic readout sequence to use predicted pixel values as soon as they are generated.
• Mermaid Diagram:

  graph TD
      subgraph Cryogenic Dewar
          A(Superconducting Sensor Array) --> B(FPGA Codec);
          B --> C{Rolling Intra-Prediction Module};
      end
      C -- optimized for low noise --> D[Predicted Pixel Stream];
      B -- feeds back predicted data --> C;
      D --> E(Compressed Data Output);
  

Derivative 2.3: High-Frequency Volumetric Data Prediction (4D)

• Enabling Description: The rolling prediction is extended from 2D blocks to 3D cubes (XxYxZ) for compressing time-series volumetric data, such as 4D medical scans (MRI, CT) or computational fluid dynamics simulations. The traversing order moves through the volume slice by slice (Z), and within each slice, by a raster scan (XxY). The prediction template is 3D, using reference pixels from previously predicted planes (Z-1) as well as adjacent pixels in the current plane. This allows for the exploitation of spatial redundancy across three dimensions.
• Mermaid Diagram:

  classDiagram
      class VolumetricCodec {
          +processVoxel(x, y, z)
      }
      class PredictionFunction3D {
          +calculatePrediction(referenceVoxels)
      }
      class RollingBuffer3D {
          +getVoxel(x, y, z)
          +setVoxel(x, y, z, value)
      }
      VolumetricCodec --> PredictionFunction3D : uses
      VolumetricCodec --> RollingBuffer3D : manages
  

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Axis 3: Cross-Domain Application

Derivative 3.1: Aerospace - Hypersonic Flow Field Prediction

• Enabling Description: In computational fluid dynamics (CFD) for hypersonic vehicle design, the rolling prediction method is used to compress the massive datasets representing pressure and temperature fields. The simulation grid is treated as a 2D or 3D image. The prediction algorithm runs in-situ with the solver, compressing data for each time step. The traversing order follows the direction of the dominant shockwave, as the data values across the shock front are highly correlated. This allows for more efficient storage and post-processing of simulation runs.
• Mermaid Diagram:

  flowchart TD
      A[CFD Solver Step n] --> B(Generate Flow Field Data);
      B --> C{Partition into Blocks};
      C --> D(Select Traversing Order along Shockwave);
      D --> E{Apply Rolling Intra-Prediction};
      E --> F[Store Compressed Field Data];
      F --> G(Solver Step n+1);
  

Derivative 3.2: AgTech - Soil Nutrient Map Compression

• Enabling Description: Data from ground-penetrating radar and chemical sensors on automated farm equipment creates large, spatially correlated maps of soil nutrients (nitrogen, phosphorus, potassium). The rolling prediction method is used to compress these maps for transmission and storage. Since nutrient levels often form smooth gradients, the prediction functions are low-pass filters that propagate values smoothly across the map. The traversing order follows the path of the sensing vehicle to maximize the utility of recently predicted data points.
• Mermaid Diagram:

  sequenceDiagram
      participant SensorVehicle
      participant OnboardCodec
      participant CloudStorage
      SensorVehicle->>OnboardCodec: Stream of Nutrient Data (N, P, K)
      OnboardCodec->>OnboardCodec: Apply Rolling Prediction along vehicle path
      OnboardCodec->>CloudStorage: Transmit Compressed Nutrient Map
  

Derivative 3.3: Consumer Electronics - Real-time E-ink Display Updates

• Enabling Description: For partial updates on an E-ink display, the rolling prediction method is used to calculate the residual (the change between the old and new screen buffer). This is more efficient than transmitting the full updated block. The traversing order starts at the top-left corner of the changed region. The prediction function uses a simple predictor (e.g., p(x,y) = p(x-1, y)) to quickly generate a predicted state. Only the residual needs to be sent to the display controller, reducing bandwidth and power for screen updates.
• Mermaid Diagram:

  stateDiagram-v2
      state "Partial Update" as Update {
          [*] --> Calculating_Residual
          Calculating_Residual --> Transmitting_Residual: Use Rolling Prediction
          Transmitting_Residual --> [*]
      }
  

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Axis 4: Integration with Emerging Tech

Derivative 4.1: AI-Driven Mode and Template Selection

• Enabling Description: A convolutional neural network (CNN) analyzes the current block to be encoded. Based on its learned understanding of textures, edges, and patterns, the CNN directly outputs the optimal prediction mode, traversing order, and template shape for the rolling prediction algorithm. This replaces the brute-force rate-distortion optimization search, significantly speeding up the encoding process. The CNN's output is encoded as side information in the bitstream for the decoder.
• Mermaid Diagram:

  graph TD
      A[Current Block] --> B(CNN Analyzer);
      B --> C[Optimal Mode];
      B --> D[Optimal Traversing Order];
      B --> E[Optimal Template];
      subgraph Encoder
          F{Rolling Prediction Engine}
      end
      C & D & E --> F;
  

Derivative 4.2: IoT Sensor Network Data Compression

• Enabling Description: In a dense IoT sensor network (e.g., environmental monitoring), each sensor node uses rolling intra-prediction to compress its time-series data. The "block" is a 1D vector of recent sensor readings. The "neighboring reference samples" are the last readings from adjacent physical sensors, received via low-power radio. The prediction then "rolls" forward in time, predicting the sensor's next value based on its own previously predicted values and data from its neighbors. This exploits both temporal and spatial redundancy in the sensor field.
• Mermaid Diagram:

  erDiagram
      SENSOR ||--o{ READING : has
      SENSOR }o--|| SENSOR : neighbors
      READING {
          string value
          datetime timestamp
      }
      SENSOR {
          int id
          string location
      }
  

Derivative 4.3: Blockchain-Verified Prediction

• Enabling Description: In applications requiring verifiable data integrity (e.g., medical imaging, satellite surveillance), the predicted block is generated using rolling intra-prediction. A cryptographic hash of the final predicted block is then calculated and stored on a blockchain, along with the mode and reference sample data. A third-party decoder can independently regenerate the exact same predicted block using the public information and verify that its hash matches the one on the blockchain, proving that the prediction process was not tampered with.
• Mermaid Diagram:

  sequenceDiagram
      participant Encoder
      participant Blockchain
      participant Decoder
      Encoder->>Encoder: Generate Predicted Block (p)
      Encoder->>Blockchain: Store HASH(p), mode, refs
      Decoder->>Blockchain: Retrieve mode, refs
      Decoder->>Decoder: Generate Predicted Block (p')
      alt HASH(p) == HASH(p')
          Decoder->>Decoder: Verification Success
      else
          Decoder->>Decoder: Verification Failure
      end
  

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Axis 5: The "Inverse" or Failure Mode

Derivative 5.1: Graceful Degradation Mode

• Enabling Description: The encoder/decoder monitors its own computational load or battery level. If the load exceeds a threshold, it enters a "low-power" mode. In this mode, the set of available prediction modes is restricted to only the simplest functions (e.g., DC prediction, where p(x,y) = p(x-1,y)). Furthermore, the rolling mechanism is disabled; all pixels are predicted only from the external reference samples. This reduces prediction accuracy (increasing the residual size) but drastically cuts CPU cycles, preventing device overheating or battery drain under stress.
• Mermaid Diagram:

  stateDiagram-v2
      state "High Performance" as HP
      state "Low Power" as LP
      [*] --> HP
      HP --> LP: CPU_Load > 85%
      LP --> HP: CPU_Load < 50%
      HP: Full set of prediction modes, Rolling enabled
      LP: Simplified modes, Rolling disabled
  

Derivative 5.2: Safe-Failure Prediction for Safety-Critical Systems

• Enabling Description: In an automotive or aviation vision system, if the decoder detects corrupted input data (e.g., a failed checksum on the bitstream for a block), it triggers a "safe-failure" prediction mode instead of crashing. In this mode, the entire block is filled by propagating the value of the top-left-most available valid pixel from a neighboring block. This creates a visually obvious, flat-colored block, which is preferable to a block of random noise or a system halt. This ensures the rest of the image frame can be decoded and presented, alerting the operator or an AI system to a data integrity issue in a predictable way.
• Mermaid Diagram:

  flowchart TD
      A{Decode Block Header} --> B{Checksum OK?};
      B -- Yes --> C(Perform Rolling Prediction);
      B -- No --> D(Enter Safe-Failure Mode);
      D --> E(Fill block with neighbor pixel value);
      C --> F[Reconstruct Block];
      E --> F;
  

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Combination Prior Art Scenarios

Combination 3.1: Integration with AV1 Video Codec

• Description: The rolling intra-prediction method of the '989 patent is integrated into the open-source AV1 video codec as a new set of intra-prediction modes. The existing AV1 framework for signaling prediction modes is used to signal the selection of a "rolling" mode. The AV1 reference frame buffer provides the external "neighboring reference samples." The rolling prediction is implemented as a new function within the av1_predict_intra_block library call, selectable by a new mode enum. This combines the novel prediction-generation process with a standardized, widely adopted codec framework.

Combination 3.2: GStreamer Multimedia Framework Plugin

• Description: A GStreamer plugin (gst-rollingpred) is created that implements the encoder and decoder described in the '989 patent. The plugin exposes standard GStreamer source and sink pads. When encoding, it accepts raw video frames and outputs a bitstream compliant with the patent's method. When decoding, it accepts the compliant bitstream and outputs raw video frames. This allows the rolling prediction codec to be used within any GStreamer-based application by simply linking the new element into a pipeline (e.g., gst-launch-1.0 filesrc location=video.raw ! videoconvert ! gst-rollingpred-enc ! filesink location=video.rll).

Combination 3.3: Implementation within FFmpeg

• Description: The rolling intra-prediction codec is implemented within the open-source FFmpeg library. A new codec ID (AV_CODEC_ID_ROLLINGPRED) is defined. Encoder and decoder structures are added to libavcodec, implementing the logic from the '989 patent. This enables any application built on FFmpeg to encode or decode this format natively. The implementation uses FFmpeg's internal AVFrame structures for handling pixel data and AVPacket for the output bitstream, fully integrating the method into this ubiquitous multimedia processing tool.