Image compression based on wavelet transform and vector quantization

This paper presents an image compression scheme that uses the wavelet transform and neural network. Firstly, image is decomposed at different scales by using the wavelet transform. Then, the different quantization and. coding schemes for each sub-image are carried out in accordance with its statistical properties and distributed properties of the wavelet coefficients. The wavelet coefficients in low frequency subimage are. transformed by DCT and then they are compressed by using DPCM while the wavelet coefficients in high frequency sub-images are compressed and vector quantized by using Kohonen neural network on SOFM algorithm. Using these compressing techniques, we can obtain rather satisfactory reconstructed images with large compress ratio.