Image Compression
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Resource Overview
Spatial coherence often exists between color values of sampling points across an image surface - for instance, the identical coloration of two mice, the background wall, and gray floor. These uniform color blocks can be effectively compressed through algorithms like run-length encoding or discrete cosine transform.
Detailed Documentation
There is often spatial coherence between the color values of adjacent sampling points on an image surface. For example, in an image, the coloration of two mice, the background wall, and the gray floor may share identical RGB values. Consequently, we can compress these uniformly colored blocks using techniques such as region-based encoding or frequency-domain transformations, thereby reducing the overall file size of the image. Implementation typically involves color quantization algorithms to identify uniform regions, followed by compression methods that replace repetitive pixel data with more efficient representations.
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