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Reseach Article

Efficient Contrast Enhancement using Kernel Padding and DWT with Image Fusion

by Deepak Kumar Pandey, Rajesh Nema
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 15
Year of Publication: 2013
Authors: Deepak Kumar Pandey, Rajesh Nema
10.5120/13563-1417

Deepak Kumar Pandey, Rajesh Nema . Efficient Contrast Enhancement using Kernel Padding and DWT with Image Fusion. International Journal of Computer Applications. 77, 15 ( September 2013), 37-48. DOI=10.5120/13563-1417

@article{ 10.5120/13563-1417,
author = { Deepak Kumar Pandey, Rajesh Nema },
title = { Efficient Contrast Enhancement using Kernel Padding and DWT with Image Fusion },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 15 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 37-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number15/13563-1417/ },
doi = { 10.5120/13563-1417 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:50:21.286416+05:30
%A Deepak Kumar Pandey
%A Rajesh Nema
%T Efficient Contrast Enhancement using Kernel Padding and DWT with Image Fusion
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 15
%P 37-48
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Contrast enhancement algorithms for varying intensity distribution Images creates intensity distortion in some regions, over enhancement & unnatural effects in other regions of Images. The main reason of this effect is due to not consideration of image edges & sharp details during enhancement process. On the other hand, the human visual system is more sensitive to edges and sharp details of image. In this paper we are proposing a method titled efficient contrast Enhancement using Kernel Padding and DWT with Image Fusion that Enhances the contrast of Images that has varying intensity distribution specially satellite images, preserve the brightness of images, sharpens the edges and remove the blurriness of images. Basically this is a pixel based edge guided image fusion technique. In this method LL sub band of Image DWT is processed by contrast enhancement section where based on image brightness level image is decomposed in different layers and then each layers intensity is stressed or compressed by generated intensity transformation function. The decomposed intensity layers are also processed by canny edge detection method as all the satellite images contains the noise due to atmospheric turbulence and this is Gaussian by nature. Canny edge detector is the best method for detecting edges of image in the presence of Gaussian noise. Finally the contrast enhanced images are fused according to the weight map determined by edge map of image.

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Index Terms

Computer Science
Information Sciences

Keywords

Digital Image Processing Canny Edge Detection Kernel Filtering Image Fusion Weighting Map Determination DWT Contrast Enhancement