Image compression using frequency-sensitive competitive neural network
Choudhury A. Al Sayeed, Abul Bashar M. Ishteak Hossain · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
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.