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Proceedings Paper

Image compression using frequency-sensitive competitive neural network
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Paper Abstract

Vector Quantization is one of the most powerful techniques used for speech and image compression at medium to low bit rates. Frequency Sensitive Competitive Learning algorithm (FSCL) is particularly effective for adaptive vector quantization in image compression systems. This paper presents a compression scheme for grayscale still images, by using this FSCL method. In this paper, we have generated a codebook by using five training images and this codebook is then used to decode two encoded test images. Both SNR and PSNR and certainly the visual quality of the test images that we have achieved are found better as compared to other existing methods.

Paper Details

Date Published: 8 February 2005
PDF: 8 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.582144
Show Author Affiliations
Choudhury A. Al Sayeed, Bangladesh Univ. of Engineering and Technology (Bangladesh)
Abul Bashar M. Ishteak Hossain, Bangladesh Univ. of Engineering and Technology (Bangladesh)

Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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