Dual-Layer Wavelet Encoding for Desktop Display Image Compression
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Solution Overview
Problem
Existing wavelet image compression techniques for desktop display images suffer from blocking artifacts at tile boundaries, and efficient vectorization and processing of mixed content images are challenging, especially when using modern processor vector extensions.
Innovation Solution
A method and apparatus for encoding desktop display images using a dual-layer wavelet encoding technique, where 'LL' content is encoded losslessly and 'LY' content is encoded using wavelet transforms, with classification of image regions as changed or unchanged to prevent unnecessary reprocessing and artifact minimization, employing a reflection boundary to limit distortion and suppress unnecessary coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If full frame processing is used to mitigate blocking artifacts, then image quality is improved, but processing efficiency deteriorates
Solution Approach 1:
The image is divided into multiple tiles that can be processed independently. Each tile undergoes wavelet transformation and encoding separately, allowing parallel processing while maintaining image quality through careful boundary handling with reflection coefficients.
2Productivity
If tile-based processing is used to improve processing efficiency, then productivity is improved, but blocking artifacts increase
Solution Approach 1:
Reflection coefficients are used as intermediary elements at tile boundaries. These reflected coefficients act as a buffer that smooths transitions between independently processed tiles, reducing visible blocking artifacts while maintaining processing efficiency.
3Loss of substance
If wavelet transform is applied to all content types, then compression efficiency is improved, but text quality deteriorates
Solution Approach 1:
Different encoding strategies are applied to different regions of the image based on content type. Text regions use spatial domain coding to preserve sharp edges and clarity, while photographic regions use wavelet transform for better compression, achieving both text quality and compression efficiency.
4Manufacturing precision
If spatial domain coding is used for text content, then text quality is improved, but compression efficiency deteriorates
Solution Approach 1:
The encoding approach is adapted locally to match content characteristics. Text regions are identified and processed using spatial domain coding to maintain quality, while other regions use more aggressive compression methods, optimizing the trade-off between quality and compression ratio for each region.
Data Source
AI summary
A method for transmitting a computer display image. In one embodiment, the method comprises determining a pixel boundary, referenced to a sub-tile boundary within a grid of tiles, for a changed portion of the image; identifying i) a uniform tile within the changed portion referenced to a first tile and ii) at least one hybrid sub-tile, associated with the sub-tile boundary, within the changed portion referenced to a second tile adjacent the first tile; engaging an SIMD vector processor to transform the uniform tile to an exit matrix, transform the at least one hybrid sub-tile to at least one DC coefficient, and transform the exit matrix to a first DC coefficient and the at least one DC coefficient to a second DC coefficient; quantizing, encoding and transmitting coefficients of the first and second tiles; and transmitting a binary mask specification for the changed portion adjusted to the sub-tile boundary.