Resolving Images In Multiple Transform Domains With Applications
Abbreviated Journal Title
Digit. Signal Prog.
Engineering, Electrical & Electronic
A technique is presented to represent images employing two or more mutually non-orthogonal transforms. First, the image is divided into smaller non-overlapping subimages. Then, each subimage is resolved into two-dimensional subsignals such that each subsignal is compactly represented in a particular transform domain. This leads to an efficient representation of the subimage by superimposing the dominant coefficients corresponding to each subsignal. The residual error, which is the difference between the original subimage and the reconstructed subimage, is properly formulated. Adaptive algorithms in conjunction with an optimization strategy are developed to minimize this error. Finally, results are presented where first the feasibility of the method is established through a synthetic image example and then applications to compactly represent test images are presented. The number of transform coefficients is reduced by a factor ranging from 5 to 40. It is verified that, for a given coefficient reduction factor, the direct cosine transform (DCT)-Haar representation of test images yields a more compact representation than using DCT or Haar alone. It is shown that the DCT-Haar combination offers a reduction of up to 15.0 to 17.0% in the root mean square error as compared to the DCT alone. (C) 1995 Academic Press, Inc.
Digital Signal Processing
"Resolving Images In Multiple Transform Domains With Applications" (1995). Faculty Bibliography 1990s. 767.