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  Edge Preserved and Segmented Image Denoising  
  Authors : Renju Mohan; Sruthy M. S; Dr. D. Loganathan
  Cite as:


Denoising of images has been a successful research topic for various image processing applications. Image denoising is basically restoration of images, where the unwanted noises causing degradations are removed to obtain a visually effectual high quality image. The majority existing image denoising algorithms failed to focus on the diminishing edges whilst noise reduction. The net effect is the low quality denoised image. This paper tackle the edge preserving problem by presenting SAIST (Spatially Adaptive Iterative Singular-value Thresholding) image denoising algorithm incorporating bilateral filtering. In this work a two-fold approach is adapted. First is preserving edges through bilateral filtering. A non- maximum suppression on the smoothed image and morphological dilation to stretch the edges are performed. Second is image denoising using iterative regularization and singular valued decomposition (SVD) for estimating signal variances. The pragmatic results and better computational efficiency do better than several state-of-theart image denoising algorithms.


Published In : IJCSN Journal Volume 6, Issue 3

Date of Publication : June 2017

Pages : 320-324

Figures :05

Tables : 01


Renju Mohan : received the B. Tech degree in Computer Science and Engineering from Kerala University, India, in 2011, and currently doing M. Tech in Computer Science and Engineering in MET’S School of Engineering, Mala – APJ Abdul Kalam Technological University, Kerala, India.

Sruthy M . S : is an Assistant professor in MET’S School of Engineering Mala, Thrissur, Kerala. Received the B.Tech degree from Matha Engineering College Paravur, Kerala and M.E from Maharaja Institute of Technology. She has more than 4 years of teaching experience. Subject of interest are Parallel Processing and Architecture, Programming, Computer-Organization.

Dr. D. Loganathan : is a Professor and Head of Computer Science and Engineering department in MET’S School of Engineering, Mala, Trissur, Kerala. After his B.E., and M.E degree, he accomplished a doctoral degree from Anna University, Chennai, India. He has more than 20 years of teaching experience and having 8 years of research experience in engineering field. His research interest includes Wireless Communication, Wireless Ad hoc Networks and Image Processing. He has published several research papers in various international journals.


Image denoising, bilateral filtering, iterative regularization, singular valued decomposition

An improved method of image denoising while preserving edges is proposed here. In this method the Canny edge detection with Bilateral filtering is used to extract and preserve edges respectively. Bilateral filtering includes smoothing whilst preserving edge, which is non-iterative in manner. This particular technique defines weights based on the chosen pixel and nearby pixel. A well-known segmentation method called mean shift segmentation is used for clustering pixels into different patches. For performing denoising after preserving edges, SAIST (Spatially adaptive iterative singular-value thresholding) is used. The iterative regularization technique, noise variance update, singular-value decomposition (SVD) is collaborated to get desired result. Excellent experimental results have been obtained for proposed image denoising.


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