Abstract or Keywords
Transform-based image coders exploit the information packing ability of some mathematical transforms in order to reduce the number of significant transform coefficients needed to accurately represent an image. Large coefficients are often associated with those regions where an image changes a lot, such as the boundaries between objects with differing visual characteristics. One way to reduce the number of significant transform coefficients is to segment an image into regions of similarity and then apply the transform to each region separately. We propose a novel image compression technique which first segments an image into arbitrary regions and then applies a region-adapted wavelet transform to each region.