Image Compression via Parameter-Assisted Inpainting
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Solution Overview
Problem
Conventional image compression techniques prioritize coding efficiency over perceptual quality and often increase encoding complexity, failing to effectively combine artificial synthesis with conventional coding principles to achieve improved image compression ratios.
Innovation Solution
The method involves partitioning an image into smooth and unsmooth blocks, compressing unsmooth blocks' content, summarizing smooth blocks with parameters, and using parameter-assisted inpainting at the decoder to reconstruct smooth blocks, thereby enhancing compression ratios and perceptual fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional compression techniques are used to improve coding efficiency, then compression ratio is improved, but perceptual quality deteriorates and encoding complexity increases
Solution Approach 1:
The image is divided into multiple blocks, and each block is independently classified as smooth or unsmooth based on local characteristics. This segmentation allows different processing strategies to be applied to different regions, improving overall perceptual quality while maintaining compression efficiency.
Solution Approach 2:
Different compression strategies are applied to different regions: smooth blocks use parameter-based inpainting while unsmooth blocks use conventional compression. This local differentiation ensures that perceptual quality is prioritized in regions where it matters most without sacrificing overall compression ratio.
2Productivity
If conventional compression techniques are used to improve coding efficiency, then compression ratio is improved, but encoding complexity increases
Solution Approach 1:
The encoding process is segmented into distinct stages: classification, parameter extraction for smooth blocks, and conventional encoding for unsmooth blocks. This segmentation allows the system to optimize each stage independently, reducing overall encoding complexity while maintaining high compression ratios.
Solution Approach 2:
For smooth blocks, instead of encoding full pixel data, the system extracts and encodes only essential parameters that guide the inpainting process. This parameter-based approach significantly reduces the amount of data to be encoded and processed, lowering encoding complexity.
3Manufacturing precision
If smooth blocks are compressed instead of summarized with parameters, then more image detail is preserved, but compression ratio decreases
Solution Approach 1:
The system applies different preservation strategies based on local block characteristics: smooth blocks are represented by compact parameters that capture essential visual information, while unsmooth blocks receive full compression processing. This local differentiation achieves high compression ratios without sacrificing important image details.
Solution Approach 2:
Instead of copying and storing full pixel data for smooth blocks, the system creates a simplified representation using extracted parameters. These parameters serve as a compact copy that enables accurate reconstruction through inpainting, achieving high compression while preserving visual fidelity.
4Manufacturing precision
If parameter-assisted inpainting is used to reconstruct smooth blocks, then perceptual quality is improved, but decoding complexity increases
Solution Approach 1:
The parameter-assisted inpainting process is self-contained and can be performed independently at the decoder using only the received parameters and local image context. This self-service capability eliminates the need for complex centralized processing, reducing decoding complexity while maintaining high perceptual quality.
Solution Approach 2:
The extracted parameters serve as intermediaries that bridge the compressed representation and the final reconstructed image. These parameters guide the inpainting process without requiring complex algorithms, simplifying the decoding process while enabling high-quality reconstruction of smooth blocks.
Data Source
AI summary
Systems and methods provide image compression based on parameter-assisted inpainting. In one implementation of an encoder, an image is partitioned into blocks and the blocks classified as smooth or unsmooth, based on the degree of visual edge content and chromatic variation in each block. Image content of the unsmooth blocks is compressed, while image content of the smooth blocks is summarized by parameters, but not compressed. The parameters, once obtained, may also be compressed. At a decoder, the compressed image content of the unsmooth blocks and the compressed parameters of the smooth blocks are each decompressed. Each smooth block is then reconstructed by inpainting, guided by the parameters in order to impart visual detail from the original image that cannot be implied from the image content of neighboring blocks that have been decoded.