Feature-Region Image Compression for Clearer Target Objects

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Solution Overview

Problem

Images compressed as a whole often lose key information, resulting in blurry and unclear images.

Innovation Solution

An image compression method that identifies and compresses multiple feature regions within an image based on pixel channel values, using specific compression parameters to retain key information, thereby enhancing image clarity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If the image is compressed as a whole, then the compression process is simple, but the key information in the image is lost resulting in blurry images

Engineering Contradiction:

Improvecompression process simplicityVSAvoidkey information loss

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The image is divided into multiple image blocks based on feature importance, allowing different compression strategies to be applied to different regions. This segmentation enables the system to preserve key information in important regions while applying more aggressive compression to less critical areas, thus resolving the contradiction between compression simplicity and information preservation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different compression parameters are applied to different image blocks according to their feature importance. Important regions (containing target objects or key features) use compression parameters that preserve detail, while less important regions use more aggressive compression. This local quality approach maintains key information while still achieving overall compression efficiency.

Inventive Principle:

Principle #3Local quality

2Manufacturing precision

If different compression parameters are applied to different image feature regions, then the clarity of compressed images is improved, but the compression process becomes more complex

Engineering Contradiction:

Improveimage clarityVSAvoidcompression process complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis to identify image feature regions and determine their importance before compression. By pre-classifying image blocks and assigning compression parameters in advance, the system avoids complex real-time decision-making during compression, thus improving image clarity while controlling process complexity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes compression parameters (such as compression ratio, quality factor) based on the identified feature regions. By dynamically adjusting parameters according to regional importance rather than using a fixed parameter set, the system achieves higher image clarity while the parameter adjustment is guided by clear rules that prevent excessive complexity.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260019602A1Image compression method and apparatus, computer device, and computer readable storage medium

Publication Date: 2026.01.15 SHENZHEN TCL NEW-TECH CO LTD

AI summary

Embodiments of the present disclosure provide an image compression method and apparatus, a computer device, and a computer readable storage medium. The method comprises: according to channel values of pixel points in an image to be compressed, determining a plurality of image feature regions matched with a target object in the image to be compressed; according to compression parameters corresponding to each image feature region, respectively compressing each image feature region to obtain compressed image regions; and generating a compressed image according to the compressed image regions. The embodiments of the present disclosure can improve the definition of the compressed image.