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Image Enhancement through Contrast Improvement in ROI using Local PGI Model

by I. Suneetha, T. Venkateswarlu
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 4
Year of Publication: 2012
Authors: I. Suneetha, T. Venkateswarlu
10.5120/8558-2136

I. Suneetha, T. Venkateswarlu . Image Enhancement through Contrast Improvement in ROI using Local PGI Model. International Journal of Computer Applications. 54, 4 ( September 2012), 47-53. DOI=10.5120/8558-2136

@article{ 10.5120/8558-2136,
author = { I. Suneetha, T. Venkateswarlu },
title = { Image Enhancement through Contrast Improvement in ROI using Local PGI Model },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 4 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 47-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number4/8558-2136/ },
doi = { 10.5120/8558-2136 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:52.836267+05:30
%A I. Suneetha
%A T. Venkateswarlu
%T Image Enhancement through Contrast Improvement in ROI using Local PGI Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 4
%P 47-53
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Images are very powerful tools to provide information to the viewers in every field i. e. medical images for doctors, forensic images for police investigation, text images for readers etc. In the process of image acquisition, image clarity is affected by lighting, weather, distance, or equipment used for image capture. Sometimes quality of the image may be corrupted differently in various regions of an image. As contrast is one of the assessment factors for determining an image quality, it is necessary to develop a better and faster algorithm for contrast improvement in regions of interest. This paper proposes a method for image enhancement through contrast improvement in regions of interest using a Local Parameterized Gradient Intercept (LPGI) Model in spatial domain. The proposed method provides good results subjectively as well as objectively for both gray scale and true color images. The proposed method is useful for interactive image processing applications as it has a family of possible transformations for various enhancement levels in different regions of interest.

References
  1. Ms. I. Suneetha and Dr. T. Venkateswarlu, "Enhancement Techniques for Gray scale Images in Spatial Domain", International Journal of Emerging Technology and Advanced Engineering, website: www. ijetae. com(ISSN 2250-2459) Volume 2, Issue 4, April 2012, pp. 13-20.
  2. Ms. I. Suneetha and Dr. T. Venkateswarlu, "Enhancement Techniques for True Color Images in Spatial Domain", International Journal of Computer Science & Technology (IJCST), Website: www. ijcst. com(ISSN Online 0976-8491, ISSN Print 2229-4333) Volume 3, Issue 2, Version 5, April to June 2012, PP. 814-820.
  3. Ms. I. Suneetha and Dr. T. Venkateswarlu, "Image Enhancement Through Noise Suppression Using Nonlinear Parameterized Adaptive Recursive Model", International Journal of Engineering Research and Applications (IJERA), Website: www. ijera. com (ISSN 2248-9622), Volume 2, Issue 4,July-August 2012, pp. 1129-1136.
  4. Ms. I. Suneetha and Dr. T. Venkateswarlu, "Image Enhancement Through Contrast Improvement Using Linear Parameterized Gradient Intercept Model", ARPN Journal of Engineering and Applied Sciences (ARPN-JEAS), Website:www. arpnjournals. com (ISSN 1819-6608), Volume 7, No. 8, August 2012.
  5. Ms. I. Suneetha and Dr. T. Venkateswarlu, "Spatial Domain Image Enhancement Using Parameterized Hybrid Model", International Journal of Electronics and Communication Engineering (IJECET), Website:www. iaeme. com (ISSN Print 0976-6464, ISSN Online 0976-6472), Volume 3, Issue 2, July-September (2012), pp. 209-216.
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Index Terms

Computer Science
Information Sciences

Keywords

Global Histogram Equalization (GHE) Local Histogram Equalization (LHE) Global Adaptive Equalization (GAE) Local Adaptive Equalization (LAE) and Global Parameterized Gradient Intercept (GPGI) Local Parameterized Gradient Intercept (LPGI) Region Of Interest (ROI)

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