It has been found that wavelet representations of an image generally perform than DCT representations for lossy image compression, as there is less perceptual loss for the same bit rate. This is the case even when performed on the same block size. We will investigate this further in the second part of our report. This is useful, because we may care more about detail in some portions of an image than in others. We've all experienced the unreadable text in the Stanford online videos.
Similar applications exist in medical imaging, etc.
We first start with a ROI mask, which marks out a region of the image we wish to store at higher quality. We can do this by applying the transform to the mask, and looking at which coefficients fall in the mask. There can be more than one ROI in the image. Note that disjoint masks can overlap in the wavelet domain due to filtering. This allows for progressive transmission and display of the image.