Video Encoding Hierarchical Coding Units
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Solution Overview
Problem
Conventional video codecs face inefficiencies in encoding and decoding high-resolution video content due to fixed macroblock sizes, leading to increased macroblocks per picture and decreased data compression efficiency.
Innovation Solution
The method involves adaptive determination of coding unit size and encoding mode based on image characteristics, using hierarchical encoding units of varying sizes to split images into maximum, deeper, and minimum coding units, and employing Rate-Distortion Optimization for optimal encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed macroblock sizes are used for encoding, then encoding simplicity is maintained, but data compression efficiency decreases for high-resolution video
Solution Approach 1:
The patent applies dynamic coding unit sizes that adapt to different regions of the video frame and different depth levels in the hierarchical structure. Instead of fixed macroblock sizes, the encoding system dynamically selects coding unit sizes (e.g., 64x64, 32x32, 16x16, 8x8 blocks) based on local image characteristics and depth, allowing larger units for simple regions and smaller units for complex regions, thereby improving compression efficiency while maintaining encoding feasibility
Solution Approach 2:
The patent implements local quality adaptation by applying different coding unit sizes and encoding modes to different spatial regions and depth levels. Each coding unit can be independently configured with appropriate partitioning and prediction modes based on local image complexity, motion characteristics, and depth information, enabling optimized compression for each local region rather than uniform encoding across the entire frame
2Productivity
If hierarchical encoding units of varying sizes are used, then data compression efficiency improves, but device complexity increases
Solution Approach 1:
The patent segments the video encoding process into a hierarchical structure with multiple depth levels, where each level divides coding units into smaller partitions. This segmentation allows systematic exploration of different coding unit sizes (from large 64x64 blocks down to small 8x8 blocks) in an organized manner, managing the complexity through structured division rather than random trial of all possible configurations
Solution Approach 2:
The patent employs dynamic selection of coding unit sizes and partitioning modes at each depth level based on local image characteristics. The encoding apparatus adaptively determines the optimal coding unit size for each region and depth, avoiding the need to evaluate all possible configurations exhaustively. This dynamic adaptation reduces computational complexity while maintaining high compression efficiency through intelligent local optimization
3Manufacturing precision
If the number of macroblocks per picture increases, then image detail representation improves, but encoding and decoding time increases
Solution Approach 1:
The patent segments the image into a hierarchical structure where detail representation is achieved through progressive refinement across multiple depth levels rather than using a large number of uniformly small macroblocks. This segmentation allows the system to use larger coding units for regions where high detail is not critical and smaller units only where necessary, reducing the total number of coding units compared to conventional fixed-size macroblock approaches while maintaining image detail quality
Solution Approach 2:
The patent applies local quality optimization by using smaller coding units and more sophisticated partitioning only in regions requiring high detail representation (such as edges, textures, or motion boundaries), while using larger coding units in smooth or homogeneous regions. This local adaptation reduces the overall number of coding units and processing operations compared to uniformly fine-grained macroblocks, thereby reducing encoding and decoding time while preserving necessary image detail
Data Source
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AI summary
Disclosed is a method of encoding a video, the method including: splitting a current picture into at least one maximum coding unit; determining a coded depth to output a final encoding result according to at least one split region obtained by splitting a region of the maximum coding unit according to depths, by encoding the at least one split region, based on a depth that deepens in proportion to the number of times the region of the maximum coding unit is split; and outputting image data constituting the final encoding result according to the at least one split region, and encoding information about the coded depth and a prediction mode, according to the at least one maximum coding unit.