Image compression using frequency-sensitive competitive neural network

Choudhury A. Al Sayeed; Abul Bashar M. Ishteak Hossain

doi:10.1117/12.582144

8 February 2005 Image compression using frequency-sensitive competitive neural network

Choudhury A. Al Sayeed, Abul Bashar M. Ishteak Hossain

Author Affiliations +

Proceedings Volume 5637, Electronic Imaging and Multimedia Technology IV; (2005) https://doi.org/10.1117/12.582144
Event: Photonics Asia, 2004, Beijing, China

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.

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Choudhury A. Al Sayeed and Abul Bashar M. Ishteak Hossain "Image compression using frequency-sensitive competitive neural network", Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); https://doi.org/10.1117/12.582144

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