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8 February 2005 Image compression using frequency-sensitive competitive neural network
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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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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