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Image Restoration: Design of Non-Linear Filter (LR)


Affiliations
1 Department of Computer Science and Engineering, P.S.R. Rengasamy College of Engineering for Women, India
2 Department of Computer Science and Engineering, P.S.R. Engineering College, India
     

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In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.

Keywords

Noises, Non Linear Filter, Restoration, Convolution.
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  • Image Restoration: Design of Non-Linear Filter (LR)

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Authors

Shenbagarajan Anantharajan
Department of Computer Science and Engineering, P.S.R. Rengasamy College of Engineering for Women, India
A. Siva Ganesh
Department of Computer Science and Engineering, P.S.R. Engineering College, India
V. Rajesh Kumar
Department of Computer Science and Engineering, P.S.R. Rengasamy College of Engineering for Women, India
C. Balasubramanian
Department of Computer Science and Engineering, P.S.R. Engineering College, India

Abstract


In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.

Keywords


Noises, Non Linear Filter, Restoration, Convolution.