Chroma Downsampling Error Evaluation for Image Compression
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Solution Overview
Problem
Chroma downsampling in image compression is not visually lossless in all situations, leading to artifacts, and existing methods lack effective evaluation and control mechanisms to optimize compression processes.
Innovation Solution
A method to evaluate the effect of chroma downsampling by computing errors based on DCT coefficients in the U and V planes, estimating perceptual effects, and applying control thresholds to select appropriate chroma downsampling modes, thereby optimizing the compression process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If chroma downsampling is applied to compress images, then compression ratio is improved, but image quality deteriorates due to artifacts
Solution Approach 1:
The patent applies different chroma downsampling strategies to different regions of the image based on local characteristics. By analyzing DCT coefficient diversity and error metrics for each block, the system selectively applies downsampling only where it is imperceptible, maintaining high quality in critical regions while achieving compression in suitable areas.
Solution Approach 2:
The patent dynamically adjusts chroma downsampling parameters based on image content analysis. By computing error metrics and DCT coefficient characteristics, the system adapts the downsampling intensity and methodology to match the specific properties of each image block, optimizing the balance between compression and quality.
2Productivity
If chroma downsampling is applied universally, then compression efficiency is improved, but visual losslessness deteriorates
Solution Approach 1:
The patent performs preliminary analysis of image blocks before applying chroma downsampling. By pre-computing error metrics and evaluating DCT coefficient characteristics, the system identifies suitable candidates for downsampling in advance, ensuring that only blocks where downsampling will be imperceptible are processed, thereby maintaining visual losslessness.
Solution Approach 2:
The patent implements a feedback mechanism where error metrics and quality assessments guide the chroma downsampling decision process. The system continuously evaluates the impact of downsampling on each block and adjusts its application accordingly, ensuring that compression efficiency is maximized without compromising visual losslessness.
3Manufacturing precision
If chroma downsampling control is added, then image quality is improved, but processing complexity increases
Solution Approach 1:
The patent divides the image into discrete blocks and applies chroma downsampling control independently to each block. By segmenting the processing task and applying simple error metric calculations and threshold comparisons to each block, the system achieves quality improvement through localized control without requiring complex global optimization algorithms.
Data Source
AI summary
There is provided an apparatus and a method of evaluating an effect of chroma downsampling in a compression process of an input image. According to examples of the presently disclosed subject matter the method can include: computing an error for a target chroma downsampling (“CDS”) block based on characteristics of DCT coefficients in the U and/or V planes of a respective CDS candidates group in the input image, and further based on a diversity of the DCT coefficients in the U and/or V planes of the respective CDS candidates group in the input image; and computing an estimated perceptual effect of CDS over the input image based on a plurality of target CDS blocks error values.