Pixel Block Re-Encoding for Hybrid Lossy-Lossless Compression
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Solution Overview
Problem
Current image and video compression techniques face challenges in balancing compression ratio and image quality, with lossless compression offering high fidelity but low ratios and lossy compression sacrificing detail, and existing methods often require choosing between these without simultaneous implementation.
Innovation Solution
A hybrid codec system that selectively uses lossy and lossless compression based on image content, such as edge detection, allowing for adaptive encoding and decoding using indicators to determine compression type for each pixel block, and a lossy block repair process to enhance quality by re-encoding unchanged blocks with lossless compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If lossless compression is used, then image quality is maintained, but compression ratio is low
Solution Approach 1:
The image is divided into multiple blocks, and each block is independently compressed using either lossless or lossy compression based on its characteristics. This segmentation allows different compression strategies to be applied to different regions, achieving both high quality where needed and high compression where acceptable.
Solution Approach 2:
Different compression methods are applied to different blocks based on local image characteristics such as edge presence. Blocks containing edges use lossless compression to preserve detail, while blocks without edges use lossy compression to achieve higher compression ratios. This local differentiation resolves the contradiction between quality and compression ratio.
2Productivity
If lossy compression is used, then compression ratio is improved, but image quality deteriorates
Solution Approach 1:
The image is divided into multiple blocks, and each block is independently compressed using either lossless or lossy compression based on its characteristics. This segmentation allows different compression strategies to be applied to different regions, achieving both high quality where needed and high compression where acceptable.
Solution Approach 2:
Different compression methods are applied to different blocks based on local image characteristics such as edge presence. Blocks containing edges use lossless compression to preserve detail, while blocks without edges use lossy compression to achieve higher compression ratios. This local differentiation resolves the contradiction between quality and compression ratio.
3Productivity
If hybrid compression is used, then compression ratio and image quality are balanced, but device complexity increases
Solution Approach 1:
The image is divided into multiple blocks, and each block is independently compressed using either lossless or lossy compression based on its characteristics. This segmentation allows different compression strategies to be applied to different regions, achieving both high quality where needed and high compression where acceptable.
Solution Approach 2:
Different compression methods are applied to different blocks based on local image characteristics such as edge presence. Blocks containing edges use lossless compression to preserve detail, while blocks without edges use lossy compression to achieve higher compression ratios. This local differentiation resolves the contradiction between quality and compression ratio.
Data Source
AI summary
Systems and methods are described herein for repairing a block of pixels in image data that was encoding using a lossy type of compression. In one aspect, it may be determined that a first pixel block within a first frame of image data was encoded using lossy compression, where the first pixel block comprising a plurality of pixels. Next, it may be determined that the plurality of pixels in the first pixel block in a second frame of the image data are below a threshold difference as compared to the plurality of pixels within the first frame of the image data. Responsive to the determining, the first pixel block may be re-encoded in the second frame or a subsequent frame of the image data using lossless compression.