Image Decoding Device Selective BDOF Processing
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Solution Overview
Problem
Existing techniques for Bi-Directional Optical Flow (BDOF) processing face challenges in reducing processing time consistently across both software and hardware implementations.
Innovation Solution
An image decoding device and method that incorporates a motion vector decoding unit, a refinement unit for correcting motion vectors, and a predictive signal generation unit that determines whether to apply BDOF processing based on information calculated during refinement processing, thereby optimizing processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If BDOF skipping processing is implemented using software, then execution time is shortened, but execution time increases in hardware-based implementation
Solution Approach 1:
The patent applies different processing strategies to different blocks based on local characteristics. By calculating sum of absolute differences (SAD) for each block and comparing against a threshold, the system selectively applies BDOF processing only where needed, rather than uniformly across all blocks. This local differentiation resolves the contradiction by optimizing for software execution time while maintaining hardware implementation feasibility.
Solution Approach 2:
The patent changes the parameter of processing application by introducing a threshold-based decision mechanism. Instead of always applying or never applying BDOF, the system dynamically determines application based on SAD values. This parameter change enables the system to adapt to different implementation contexts (software vs hardware) while maintaining optimal performance.
2Loss of time
If BDOF buffer reduction technique is implemented using hardware, then execution time is shortened, but execution time increases when using software
Solution Approach 1:
The patent segments the video processing into distinct stages: motion vector decoding, refinement processing with SAD calculation, and selective BDOF application. By dividing the processing pipeline and allowing independent optimization of each segment for different platforms, the system resolves the contradiction between hardware and software implementation performance.
3Productivity
If selective BDOF processing is applied based on refinement processing information, then processing amount is reduced in hardware implementation, but processing time is shortened in software implementation
Solution Approach 1:
The patent performs preliminary SAD calculation during the refinement processing stage, before the final BDOF decision is made. By preparing this information in advance, the system enables fast selective BDOF application without requiring additional computation during the critical rendering path, thus improving both hardware efficiency and software performance.
Data Source
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AI summary
An image decoding device (200) includes: a motion vector decoding unit (241B) that decodes a motion vector from encoded data; a refinement unit (241C) that performs refinement processing to correct the decoded motion vector; and a predictive signal generation unit (241D) that generates a predictive signal on the basis of the corrected motion vector output from the refinement unit (241C), wherein the predictive signal generation unit (241D) determines whether or not to perform bidirectional optical flow, BDOF, processing for each sub-block which underwent the refinement processing, on the basis of information calculated in the course of the refinement processing, wherein the sub-block is generated by splitting a block, and wherein the predictive signal generation unit (241D) determines, for each of the sub-blocks, that the BDOF processing is not to be performed when a minimum search cost of the refinement processing is less than or equal to a predefined threshold value, wherein the search cost is a sum of absolute differences or any other indicator of the similarity between image signals, calculated in the course of the refinement processing.