Image Compression via Texture-Adaptive Amplitude Reduction
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Solution Overview
Problem
Current image compression methods, such as the JPEG standard, fail to efficiently compress high-resolution images without significantly degrading subjective quality, particularly in applications like mobile media sharing where high compression efficiency is required.
Innovation Solution
An image compression method that performs amplitude decreasing processing on frequency domain coefficients based on the texture direction of the image, using discrete cosine transform and adaptive quantization matrices to differentiate between energy-focused and non-energy-focused regions, thereby reducing amplitudes in non-energy-focused areas without affecting image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If JPEG compression standard is used, then compression efficiency is improved, but subjective image quality deteriorates
Solution Approach 1:
The patent applies different quantization matrices to different frequency regions of the image. Specifically, it uses a first quantization matrix for a first frequency region and a second quantization matrix for a second frequency region, allowing each region to be processed with appropriate compression strength based on its local characteristics, thus maintaining quality where needed while compressing where possible
Solution Approach 2:
The patent changes the quantization parameters based on texture direction detection. By detecting the texture direction in different image regions and selecting quantization matrices accordingly, the system adapts the compression parameters to local image characteristics, achieving better quality-pres compression in textured regions while maintaining efficiency in smooth regions
2Productivity
If downsampling is performed on high-resolution image, then compression efficiency is improved, but image resolution and quality deteriorate
Solution Approach 1:
The patent changes quantization parameters based on detected texture directions in different frequency regions, allowing adaptive compression that preserves important image details while removing redundant information, achieving high compression ratios without downsampling
Data Source
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AI summary
The present invention relates to an image compression method and apparatus, where the image compression method includes a step of performing amplitude decreasing processing on a frequency domain coefficient or a quantization coefficient of a to-be-processed image. The image compression method includes: determining a texture direction of the to-be-processed image; and performing amplitude decreasing processing on the frequency domain coefficient or the quantization coefficient of the to-be-processed image according to the texture direction, where the frequency domain coefficient is a coefficient obtained after the image is transformed, and the quantization coefficient is a coefficient obtained after the frequency domain coefficient is quantized. According to embodiments of the present invention, amplitude decreasing processing is performed on a frequency domain coefficient of a to-be-processed image according to a texture direction of the to-be-processed image, which can improve the compression efficiency without affecting subjective quality of the to-be-processed image.