Title :
Image data processing in the compressed wavelet domain
Author :
Tian, Jun ; Wells, Raymond O., Jr.
Author_Institution :
Comput. Math. Lab., Rice Univ., Houston, TX, USA
Abstract :
A new embedded image coding method, the wavelet-difference-reduction algorithm, was introduced by Jun Tian et al. (see Proceedings of the IEEE Data Compression Conference, Snowbird, Utah, 1996). It combines the discrete wavelet transform, differential coding, binary reduction, order bit plane transmission, and adaptive arithmetic coding. It is a simple and efficient way to successively approximate the image source and is very suitable for progressive image transmission. In addition, this algorithm provides a clear geometric structure in the compressed wavelet domain, which enables us to process the image data in compressed form. We discuss three aspects of this problem, namely denoising, speckle reduction, and zooming. These outline some ideas of how to facilitate image data processing in the compressed wavelet domain
Keywords :
adaptive codes; adaptive signal processing; arithmetic codes; image coding; image representation; image resolution; speckle; transform coding; wavelet transforms; adaptive arithmetic coding; binary reduction; compressed wavelet domain; denoising; differential coding; discrete wavelet transform; embedded image coding method; geometric structure; image data processing; image source; multiresolution image representation; order bit plane transmission; progressive image transmission; speckle reduction; successive approximation; wavelet difference reduction algorithm; zooming; Data processing; Discrete wavelet transforms; Frequency; Image coding; Image resolution; Signal resolution; Spatial resolution; Vectors; Wavelet domain; Wavelet transforms;
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2912-0
DOI :
10.1109/ICSIGP.1996.566254
