Recursive Image Block Partitioning for Boundary-Aware Encoding
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Solution Overview
Problem
Existing image encoding/decoding technologies face challenges in efficiently processing image boundaries and adjusting image sizes on a per block basis, leading to difficulties in compression efficiency and effective utilization of neighboring block information.
Innovation Solution
The method involves partitioning current images into blocks and sub-blocks, using quad tree or binary tree partitioning based on boundary conditions, and determining partition directions and types to optimize image encoding/decoding, with optional encoding/decoding of partition information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If image encoding is performed on a per block basis with fixed block sizes, then encoding simplicity is maintained, but it becomes difficult to process images where the size is not a multiple of the block size
Solution Approach 1:
The image is divided into multiple blocks of a predetermined size, and each block is further divided into sub-blocks. This hierarchical segmentation allows the encoding system to handle images of various sizes by recursively partitioning blocks until the boundary conditions are satisfied, thus maintaining encoding simplicity while adapting to different image dimensions.
Solution Approach 2:
The patent introduces dynamic block partitioning where blocks can be recursively divided into sub-blocks based on boundary conditions. This dynamic adaptation allows the encoding structure to flexibly adjust to images whose sizes are not multiples of the base block size, resolving the contradiction between fixed encoding simplicity and size adaptability.
2Manufacturing precision
If recursive partitioning is performed on blocks containing image boundaries, then boundary processing accuracy is improved, but encoding complexity increases
Solution Approach 1:
The patent applies different processing strategies to different regions: blocks containing image boundaries undergo recursive partitioning into sub-blocks for accurate boundary handling, while blocks without boundaries use standard encoding. This localized differentiation improves boundary processing accuracy without unnecessarily increasing complexity across the entire image.
Solution Approach 2:
Instead of applying recursive partitioning to all blocks, the patent selectively applies it only to blocks that contain image boundaries. This partial action approach achieves the necessary boundary processing accuracy while minimizing the increase in encoding complexity by limiting the recursive operation to only where required.
3Measurement precision
If all partition information is encoded, then decoding accuracy is improved, but compression efficiency decreases
Solution Approach 1:
The patent extracts and encodes only the essential partition information that is necessary for accurate decoding. By identifying and encoding only the critical partitioning details rather than all possible partition information, the system maintains decoding accuracy while reducing the bitstream overhead and improving compression efficiency.
Solution Approach 2:
The patent applies partial encoding of partition information by selectively encoding only the necessary partitioning details required for accurate reconstruction. This partial action approach achieves sufficient decoding accuracy without the penalty of encoding all possible partition information, thus maintaining compression efficiency.
Data Source
AI summary
The present invention provides an image encoding method and an image decoding method. The image encoding method of the present invention comprises: a first dividing step of dividing a current image into a plurality of blocks; and a second dividing step of dividing, into a plurality of sub blocks, a block, which is to be divided and includes a boundary of the current image, among the plurality of blocks, wherein the second dividing step is recursively performed by setting a sub block including the boundary of the current images as the block to be divided, until the sub block including the boundary of the current image does not exist among the sub blocks.