Abstract
The process to minimize the total number of bits required to depict an image is known as image compression. The main goal of image compression is to minimize the transmission cost and to reduce the storage space. Vector quantization is a most popular technique for lossy compression due to its high compression rate and simple decoding algorithm. The key technique of VQ is the codebook design. In this paper, we have compared and found out the compression ratios of jpg and tiff images using VQ for lossy compression and k-means clustering.
Cite
CITATION STYLE
Chatterjee, R., Maity, A., & Chatterjee, R. (2019). Image compression using VQ for lossy compression. In Advances in Intelligent Systems and Computing (Vol. 814, pp. 241–246). Springer Verlag. https://doi.org/10.1007/978-981-13-1501-5_20
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