Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization

We present a wavelet based non-linear interpolative vector quantization scheme for joint compression and restoration of images; two tasks which are traditionally regarded as having conflicting goals. Vector quantizer codebook training is done using a training set consisting of pairs of the original image and its diffraction-limited counterpart. The designed VQ is then used to compress and simultaneously restore diffraction-limited images. Results from simulations indicate that the image produced at the output of the decoder is quantitatively and visually superior to the diffraction-limited image at the input to the encoder. We also compare the performance of several wavelet filters in our algorithm