A Detail Preserved Compression Based on Contourlet Transform

It is well known that the commonly used separable extensions of one-dimensional transforms, such as the wavelet transform, have limitations in capturing the geometry of image edges. But natural scene images always have geographic lines, such as textures, edges which can not be well reconstructed when compressed by using one-dimensional transform. So in lossy compression of images, it is important to find a method which can best preserve the image by using a small description. To solve this problem, in this paper, we present a new compression method which can preserve one of the most important cues of image: the directional details. In order to show the ability of detail preserving lossy coder we present tests using typical images with much directional information, and a comparison between wavelets and the new wavelet based contourlet transform(WBCT) is made. Finally, we present the results obtained by using image quality assessment method. Our experiments demonstrate that the decompressed images based on WBCT can preserve more directional information than wavelet transform, which can be used efficiently in future image processing such as classification, edge detecting and so on. 1 This work was supported by China National “863” Foundation. No. 2006AA12Z136 and the National Natural Foundation of China under Grant 40601055.