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 processes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If image encoding is performed on a per block basis with fixed block sizes, then the encoding process is simplified and standardized, but it becomes difficult to efficiently process image boundaries and images with sizes not matching block multiples

Engineering Contradiction:

Improveencoding process standardizationVSAvoidboundary processing capability

Core Design Contradiction:

Ease of manufactureVSAdaptability or versatility

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 recursively dividing them into manageable blocks, solving both the standardization need and the adaptability requirement for different image dimensions and boundary conditions

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The block size is made dynamic rather than fixed. The encoding system can adaptively select different block sizes based on image content characteristics and boundary conditions. This dynamic approach allows efficient processing of images with sizes not matching fixed block multiples while maintaining encoding standardization through a structured decision framework

Inventive Principle:

Principle #15Dynamics

2Productivity

If larger block sizes are used for encoding, then the compression efficiency is improved, but the processing precision and ability to capture fine image details at boundaries are reduced

Engineering Contradiction:

Improvecompression efficiencyVSAvoidimage boundary processing precision

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The hierarchical block segmentation enables the system to use larger blocks for homogeneous regions (improving compression) while automatically subdividing into smaller blocks at image boundaries or regions requiring higher precision (maintaining processing accuracy). This multi-scale approach resolves the contradiction between compression efficiency and boundary processing precision

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different block sizes are applied to different regions of the image based on local characteristics. Larger blocks are used in smooth, homogeneous areas for better compression, while smaller blocks are used at boundaries or in detailed regions for higher processing precision. This local adaptation resolves the trade-off between compression efficiency and boundary precision

Inventive Principle:

Principle #3Local quality

3Manufacturing precision

If recursive partitioning is performed until no sub-block includes the boundary, then the boundary processing is thorough and accurate, but the computational complexity and processing time increase

Engineering Contradiction:

Improveboundary processing accuracyVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

Instead of recursively partitioning the entire image to the finest level, the system performs partial partitioning only where necessary - specifically at image boundaries and regions requiring enhanced processing. This selective approach maintains boundary processing accuracy while significantly reducing the overall computational complexity and processing time compared to exhaustive recursive partitioning

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20260025507A1Image encoding method/device, image decoding method/device, and recording medium in which bitstream is stored

Publication Date: 2026.01.22 IND ACAD COOP GRP OF SEJONG UNIV

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.