Segmentation based denoising using multiple compaction domains

Maneesh Singh, Prakash Ishwar, Krishna Ratakonda, Narendra Ahuja

Research output: Contribution to conferencePaperpeer-review

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.

Original languageEnglish (US)
Pages372-375
Number of pages4
StatePublished - 1999
EventInternational Conference on Image Processing (ICIP'99) - Kobe, Jpn
Duration: Oct 24 1999Oct 28 1999

Other

OtherInternational Conference on Image Processing (ICIP'99)
CityKobe, Jpn
Period10/24/9910/28/99

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Segmentation based denoising using multiple compaction domains'. Together they form a unique fingerprint.

Cite this