Performance comparision of color image compression based on enhanced Vector quantizer designed using different color spaces

This paper presents compression of color images using vector quantization (VQ). Being vector quantization is lossy compression technique, the quality of the decompressed images is degraded. In order to achieve trade off between quality of compression along with good compression ratio, the vector qua...

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Bibliographic Details
Main Authors: Dandawate, Y.H., Joshi, M.A., Umrani, S.M.
Format: Conference Proceeding
Language:English
Subjects:
Codebook
Color
Image coding
Image color analysis
Image reconstruction
PSNR
Quality Measures
Self Organizing Feature Maps
Transform coding
Vector quantization
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Summary:This paper presents compression of color images using vector quantization (VQ). Being vector quantization is lossy compression technique, the quality of the decompressed images is degraded. In order to achieve trade off between quality of compression along with good compression ratio, the vector quantizer must be designed optimally. In this paper, we have designed an enhanced vector quantizer (codebook) by selective training of self-organized feature maps network with different images for quality improvement. The performance is analyzed using various quality measures along with conventionally used PSNR. The vector quantizer is designed for different color spaces such as RGB, HSI, HSV, YCbCr and performance is tested for quality determination. Finally, performance is compared with JPEG in terms of quality and file sizes.
DOI:10.1109/ICIAS.2007.4658463