Two-dimensional, transform-domain, least-square techniques for accurate representation of dominant transform components and noise cancellation

Accurate and efficient representation of 2D signals in the transform domain is very useful for image processing and coding. The authors present a least-square transform domain technique to accurately represent the dominant complex transform components of 2D signals and 2D systems. The algorithm derived here is based on the equationary model (recursive-like structure) which can accurately match the location, magnitude, and phase of complex transform components in the least square sense for the unknown signal. The technique is applied successfully in noise cancellation for image restoration. Examples are given to illustrate the performance of this method in both spectral representation and noise cancellation applications