Image Encoding Partitioning Index for Quality and Data Volume

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Solution Overview

Problem

Existing image encoding/decoding techniques struggle with efficiently handling high-resolution and high-quality images, leading to increased data volumes and transmission/storage costs.

Innovation Solution

The proposed method involves an image decoding method that acquires a partitioning index from a bitstream to generate a prediction sample by weighted-summing prediction samples of subblocks, and an image encoding method that determines a partitioning index and encodes it, using it to generate prediction samples for encoding.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If high resolution and quality images are used, then image quality is improved, but data volume increases leading to higher transmission and storage costs

Engineering Contradiction:

Improveimage qualityVSAvoiddata volume

Core Design Contradiction:

Manufacturing precisionVSQuantity of substance

Solution Approach 1:

The current block is divided into multiple subblocks, and each subblock is processed independently with different prediction modes. This segmentation allows for more precise local prediction, improving image quality while maintaining compression efficiency by adapting to local variations in the image content.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different prediction modes are applied to different subblocks within the current block based on their local characteristics. This local quality approach ensures that each region is predicted with the most appropriate mode, improving overall reconstruction quality without uniformly increasing complexity across the entire block.

Inventive Principle:

Principle #3Local quality

2Productivity

If multiple prediction modes and processing techniques are used, then encoding/decoding efficiency is improved, but system complexity increases

Engineering Contradiction:

Improveencoding/decoding efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The prediction mode is dynamically selected for each subblock based on local image characteristics and block size. This dynamic adaptation allows the system to use simpler modes when appropriate and more complex modes only when necessary, improving efficiency while controlling overall complexity through selective application.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The partitioning index and prediction mode parameters are changed based on the current block size and characteristics. By adapting these parameters to the specific context, the system achieves better encoding efficiency without maintaining fixed complex structures, allowing flexibility that reduces unnecessary complexity.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250039376A1Image encoding/decoding method and apparatus, and recording medium in which bitstream is stored

Publication Date: 2025.01.30 ELECTRONICS & TELECOMM RES INST

AI summary

Disclosed herein are an image encoding/decoding method and apparatus. The image decoding method includes acquiring a partitioning index of a current block from a bitstream, and generating a prediction sample of the current block by weighted-summing a prediction sample of a first subblock of the current block and a prediction sample of a second subblock of the current block based on the partitioning index. The partitioning index indicates a partitioning distance and a partitioning direction included in a predefined table.