Image Block Partitioning for Boundary-Aware Video 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, including methods for deriving partition information without explicit encoding.
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 predetermined sizes (e.g., 64x64, 32x32, 16x16 pixels) through hierarchical segmentation. This allows the encoding system to handle images of various sizes by selecting appropriate block dimensions, resolving the contradiction between encoding simplicity and image size adaptability.
Solution Approach 2:
The patent introduces a new dimension of block size variability by allowing multiple predetermined block sizes rather than a single fixed size. This dimensional change enables the system to adapt to different image dimensions while maintaining the simplicity of block-based encoding processes.
2Ease of operation
If the image size is adjusted to be a multiple of block size, then per block encoding can be performed, but image quality may deteriorate due to padding operations
Solution Approach 1:
The patent applies different quality treatments to different regions of the image. Actual image content is encoded with high quality using appropriate block sizes, while padding regions (if needed) are handled separately or minimized. This local differentiation maintains overall image quality while enabling per-block encoding operations.
Solution Approach 2:
The system performs preliminary determination of optimal block sizes and partitioning schemes before encoding begins. By pre-planning the block structure based on image dimensions and content characteristics, the system avoids quality-degrading padding operations and directly configures encoding parameters for optimal image quality.
3Manufacturing precision
If complex partitioning schemes are used to handle image boundaries, then image quality is maintained, but encoding complexity increases
Solution Approach 1:
The patent implements dynamic block size selection and partitioning strategies that adapt to image characteristics and boundary conditions. Rather than using fixed complex partitioning schemes, the system dynamically determines optimal block configurations, maintaining image quality while reducing encoding complexity through adaptive decision-making.
Solution Approach 2:
The system changes encoding parameters (block size, partitioning depth, prediction modes) based on image content and boundary conditions. By adjusting these parameters dynamically rather than using fixed complex schemes, the patent maintains image quality while simplifying the encoding process.
4Productivity
If more neighboring block information is utilized for prediction, then compression efficiency improves, but processing time increases
Solution Approach 1:
The patent applies partial action by selectively using neighboring block information based on prediction mode and block position. Rather than always using all available neighboring information, the system uses only the necessary subset, improving compression efficiency where needed while avoiding unnecessary processing time expenditure.
Solution Approach 2:
The system performs preliminary identification of suitable neighboring blocks and prediction modes before actual prediction operations. By pre-selecting the most relevant neighboring block information, the patent reduces the amount of data that needs to be processed while still achieving good 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.