Title :
Segmentation based denoising using multiple compaction domains
Author :
Singh, Maneesh ; Ishwar, Prakash ; Ratakonda, Krishna ; Ahuja, Narendra
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
fDate :
6/21/1905 12:00:00 AM
Abstract :
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
Keywords :
image segmentation; Multiple Compaction Domains; denoising algorithm; segmentation; transform domain thresholding; Additive noise; Additive white noise; Compaction; Computer languages; Gaussian noise; Image segmentation; Mathematical model; Noise reduction; PSNR; Wiener filter;
Conference_Titel :
Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-5467-2
DOI :
10.1109/ICIP.1999.821633