Image Boundary Block Partitioning for Adaptive 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 recursive partitioning until no boundary sub-blocks exist, and adjusting image sizes on a per block basis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If image encoding is performed on a per block basis, then compression efficiency is improved, but it becomes difficult to process images where the size is not a multiple of the block size

Engineering Contradiction:

Improvecompression efficiencyVSAvoidadaptability to different image sizes

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The image is divided into multiple blocks of a predetermined size for encoding. When the image size is not a multiple of the block size, the image is segmented into regular blocks that can be processed efficiently and remaining pixels that form incomplete blocks at the boundaries

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different processing methods are applied to different regions of the image: complete blocks use standard block-based encoding for high compression efficiency, while incomplete boundary blocks use special handling (such as padding or separate processing) to maintain adaptability to various image sizes

Inventive Principle:

Principle #3Local quality

2Productivity

If recursive partitioning is performed on blocks containing boundaries, then boundary processing efficiency is improved, but the complexity of the partitioning process increases

Engineering Contradiction:

Improveboundary processing efficiencyVSAvoidpartitioning process complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

Blocks containing image boundaries are recursively partitioned into smaller sub-blocks until the boundary falls within a sub-block of appropriate size. This segmentation allows boundary pixels to be properly identified and processed separately from internal pixels

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The partitioning process is performed in advance to identify and isolate boundary-containing blocks before the actual encoding process. This preliminary action prepares the data structure for more efficient boundary processing during encoding

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260025503A1Image 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.