Abstract
In this study, the effects of different color spaces on compression performance, when lossy compression is applied to a color image, were discussed. RGB, HSV, YIQ, CMYK and YCbCr color spaces were used in the system. DCT was applied to provide energy loss or k-means clustering was applied to reduce the number of colors to each image in different color spaces. Those two lossy compression approaches were followed by a lossless compression approach, called Entropy coding. Finally experimental results were given for comparison.
Keywords
Lossy compression
Color space
RGB color model
Lossless compression
Computer vision
Artificial intelligence
Color depth
Color Cell Compression
YCbCr
Computer science
Color quantization
Color image
Color histogram
Data compression
Image compression
Block Truncation Coding
Mathematics
Image processing
Image (mathematics)
Subject Areas
Advanced Data Compression Techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
Algorithms and Data Compression
·Artificial Intelligence ·Physical Sciences
Video Coding and Compression Technologies
·Signal Processing ·Physical Sciences
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