Triangulation-Based Image Compression for Small Images
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Solution Overview
Problem
Existing image compression techniques, such as JPEG, are inadequate for compressing small images efficiently, as they do not significantly reduce the size of images independent of their characteristics, leading to increased bandwidth usage, especially for mobile devices with limited bandwidth.
Innovation Solution
An adaptive triangulation technique is employed, where a pixel grid is generated, points are added to the grid, and vertices are used to triangulate the image, with colors assigned using a color table, allowing for efficient compression and decompression of images by reducing the number of vertices and colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If JPEG compression standards are used, then image compression is achieved, but small images are not significantly compressed and bandwidth usage remains high
Solution Approach 1:
The image is divided into a grid of cells, and each cell is independently processed by selecting representative points and colors. This segmentation allows the compression algorithm to work efficiently on small images by treating each cell as a discrete unit, enabling significant size reduction while maintaining overall image quality.
Solution Approach 2:
The patent transforms the image representation from pixel-based to parameter-based by selecting key points (corners, centers, edges) and assigning colors to these points. This parameter change enables more efficient compression by storing only essential color information at strategic locations rather than every pixel, achieving better compression ratios for small images.
2Productivity
If domain-specific compression techniques are used, then compression efficiency improves for specific image types, but the technique is specialized and not universally applicable
Solution Approach 1:
The patent creates a universal compression algorithm that works across different image types by using a generic grid-based approach with representative point selection. The method applies the same core logic regardless of image characteristics, making it adaptable to various image types while maintaining good compression efficiency without requiring domain-specific customization.
Data Source
AI summary
An encoder system can include a pixel grid generator to receive an image having a first dimension, generate a grid having a second dimension, add a plurality of points to positions on the grid, and map a plurality of pixels of the image to the plurality of points. The encoder system can include a color module to assign a color to each of the plurality of points using a color table, a triangulation module to generate a plurality of vertices based on the plurality of points and triangulate the grid using the vertices, and a compression module to compress the vertices as a set of compressed vertex positions and a set of vertex colors.