Summary
Vector Quantization is an efficient method for image compression. It has been developed as one of the most efficient image coding techniques. It is a process that maps the blocks of high rate digital pixel intensities into a relatively small number of symbols. The aim of this work is to use different ways to encode the homogenous/ heterogeneous or edge/smooth part of the image with the improvement of the existing Vector Quantization algorithms and reduce its complexity. Many techniques in this paper have been examined to improve the quality and the compression ratio for the compressed images, such as the block rotation process, the mean and mode operation, block classification, and random blocks selection. High PSNR results obtain when using scalar quantization as a pre processing with rand selection blocks and blocks rotation.
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Muhsen, Z.F., Jorj, L.A., Alhussaini, I.H. (2010). Improve Vector Quantization Strategy. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16295-4_9
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DOI: https://doi.org/10.1007/978-3-642-16295-4_9
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