Recursive Boundary Block Splitting in Image 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 encoding simplicity is maintained, but images with sizes not matching block dimensions cannot be properly encoded

Engineering Contradiction:

Improveencoding simplicityVSAvoidimage size adaptability

Core Design Contradiction:

Ease of manufactureVSAdaptability or versatility

Solution Approach 1:

The image is divided into multiple blocks of predetermined sizes (e.g., 16x16, 32x32, 64x64 pixels). Each block can be independently encoded, allowing the system to handle images of various sizes by selecting appropriate block dimensions and numbers, thus resolving the contradiction between encoding simplicity and image size adaptability.

Inventive Principle:

Principle #1Segmentation

2Manufacturing precision

If recursive partitioning is performed on blocks containing image boundaries, then boundary processing accuracy is improved, but encoding complexity increases

Engineering Contradiction:

Improveboundary processing accuracyVSAvoidencoding complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

Recursive partitioning is applied selectively only to blocks that contain image boundaries, while blocks fully within the image boundary use standard encoding. This localized approach improves boundary processing accuracy without unnecessarily increasing encoding complexity for the entire image.

Inventive Principle:

Principle #3Local quality

3Productivity

If larger blocks are used for partitioning, then encoding speed is improved, but processing precision for detailed regions deteriorates

Engineering Contradiction:

Improveencoding speedVSAvoidprocessing precision

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The image is segmented into blocks of various sizes based on content characteristics. Larger blocks are used for uniform regions to improve encoding speed, while smaller blocks are used for detailed regions to maintain processing precision, thus resolving the contradiction between encoding speed and processing precision.

Inventive Principle:

Principle #1Segmentation

4Adaptability or versatility

If padding is applied to adjust image size to block multiples, then encoding compatibility is improved, but image quality at padded regions deteriorates

Engineering Contradiction:

Improveencoding compatibilityVSAvoidimage quality

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The padding operation, which inherently degrades image quality by adding artificial pixels, is converted into a benefit by using the padded regions to create complete blocks that can be properly encoded. The degradation is localized to minimal padding areas while the majority of the image maintains quality, and the overall encoding compatibility is improved.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Data Source

PatentUS20260082043A1Image encoding method/device, image decoding method/device, and recording medium in which bitstream is stored

Publication Date: 2026.03.19 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.