Segmentation based denoising using multiple compaction domains

In this paper, we propose a novel segmentation-based denoising algorithm. Segmentation yields intrinsically homogeneous and extrinsically heterogeneous regions. A denoising algorithm that uses Multiple Compaction Domains (MCD) is then applied on each of the resulting segments. Such a scheme retains important perceptual information in the segment boundaries while the denoising algorithm operates only on homogeneous segments. Further, the MCD algorithm is demonstrably superior to the classical denoising algorithms using transform domain thresholding. Our algorithm yields better perceptual quality and superior PSNR as compared to MATLAB's adaptive Wiener filter.