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Satellite Image Denoising using Hybrid Cuckoo Search-Grey Wolf Algorithm with Edge Preservation

Author(s):

C. S. Manju , Dr.N.G.P.Institute Of Technology; S. Priyanka, Dr.N.G.P.Institute Of Technology; V. Sruthi, Dr.N.G.P.Institute Of Technology; K. Venkatesan, Dr.N.G.P.Institute Of Technology; R. Vishnu Priya, Dr.N.G.P.Institute Of Technology

Keywords:

Gaussian Noise, Optimized Adaptive Thresholding, Denoising, Edge Preservation, Wavelets

Abstract

A satellite image is used for analyzing what is happening around the world, but these images are often corrupted by different noises during acquisition and transmission. The main objective of noise reduction technique is to reduce the noise without degrading important features in the images. The conventional denoising methods can reduce the Gaussian noise but fails to maintain the quality of the images and blurs the edges in an image. To overcome these drawbacks an optimized adaptive thresholding function based framework for edge preserved satellite image denoising using Hybrid cuckoo search and grey-wolf algorithm which is capable of effectively removing Gaussian noise from the images without over smoothening the edge details.

Other Details

Paper ID: IJSRDV5I120346
Published in: Volume : 5, Issue : 12
Publication Date: 01/03/2018
Page(s): 1091-1093

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