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Contrast optimization by region adaptation (COBRA) for grey scale images

Medical images form a part of real world images which come with a wide variety of contrast and brightness. The acquired images almost invariably require contrast enhancement. Some of the underlying contrast enhancement methods do not produce predictable results. Contemporary contrast enhancement fre...

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Main Author: Ahmed, Muhammad Mahmood
Format: Thesis
Language:English
Published: 2013
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/37082/1/Contrast%20optimization%20by%20region%20adaptation%20%28COBRA%29%20for%20grey%20scale%20images.pdf
http://umpir.ump.edu.my/id/eprint/37082/
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spelling my.ump.umpir.370822023-02-22T02:22:07Z http://umpir.ump.edu.my/id/eprint/37082/ Contrast optimization by region adaptation (COBRA) for grey scale images Ahmed, Muhammad Mahmood QA76 Computer software Medical images form a part of real world images which come with a wide variety of contrast and brightness. The acquired images almost invariably require contrast enhancement. Some of the underlying contrast enhancement methods do not produce predictable results. Contemporary contrast enhancement frequently relies on histogram equalization (HE). In practice, HE produces unexpected results. Such, inconsistent results make reliability of HE questionable. As a result HE is unacceptable in sensitive areas like medical field. The situation leads to a detailed analysis of HE, which brings out that foundation of HE is based on density not contrast. As this foundation is unrelated to contrast, resulting contrast changes are unpredictable. As a solution, a novel method based on factors directly related to contrast is proposed. This method separates the image into dark and bright regions. Based on this concept the proposed method named Contrast Optimization by Region Adaptation (COBRA) is developed by optimizing the contrast ratio of separated regions. To achieve this optimization, the whole image is shrunk to a lower scale which provides necessary space for readjustment of contrast ratio. Then the constituents grey levels are raised exponentially to revert back to original scale. This exponential reversion, adjusts the contrast ratio of separated regions to optimum. This contrast optimization fulfills deficiency in real world images. Due to contrast based foundation of the proposed method, the resultant enhancement in similar type of images is consistent. These predictable results, yield high reliability which makes the proposed method trustworthy for critical areas like medical field. Additionally the results reveal that the histogram of the enhanced image represents similarity with the original image. This similarity is measured using DICE and Jaccard methods. Based on the similarity figures, comparative analysis was carried out between the proposed method and HE. The analysis verified that the proposed method achieves excellent results on brain MRIs, additionally it performs well on general medical and common bench mark images. 2013-04 Thesis NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/37082/1/Contrast%20optimization%20by%20region%20adaptation%20%28COBRA%29%20for%20grey%20scale%20images.pdf Ahmed, Muhammad Mahmood (2013) Contrast optimization by region adaptation (COBRA) for grey scale images. Masters thesis, Universiti Malaysia Pahang (Contributors, Thesis advisor: Jasni, Mohamad Zain).
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Ahmed, Muhammad Mahmood
Contrast optimization by region adaptation (COBRA) for grey scale images
description Medical images form a part of real world images which come with a wide variety of contrast and brightness. The acquired images almost invariably require contrast enhancement. Some of the underlying contrast enhancement methods do not produce predictable results. Contemporary contrast enhancement frequently relies on histogram equalization (HE). In practice, HE produces unexpected results. Such, inconsistent results make reliability of HE questionable. As a result HE is unacceptable in sensitive areas like medical field. The situation leads to a detailed analysis of HE, which brings out that foundation of HE is based on density not contrast. As this foundation is unrelated to contrast, resulting contrast changes are unpredictable. As a solution, a novel method based on factors directly related to contrast is proposed. This method separates the image into dark and bright regions. Based on this concept the proposed method named Contrast Optimization by Region Adaptation (COBRA) is developed by optimizing the contrast ratio of separated regions. To achieve this optimization, the whole image is shrunk to a lower scale which provides necessary space for readjustment of contrast ratio. Then the constituents grey levels are raised exponentially to revert back to original scale. This exponential reversion, adjusts the contrast ratio of separated regions to optimum. This contrast optimization fulfills deficiency in real world images. Due to contrast based foundation of the proposed method, the resultant enhancement in similar type of images is consistent. These predictable results, yield high reliability which makes the proposed method trustworthy for critical areas like medical field. Additionally the results reveal that the histogram of the enhanced image represents similarity with the original image. This similarity is measured using DICE and Jaccard methods. Based on the similarity figures, comparative analysis was carried out between the proposed method and HE. The analysis verified that the proposed method achieves excellent results on brain MRIs, additionally it performs well on general medical and common bench mark images.
format Thesis
author Ahmed, Muhammad Mahmood
author_facet Ahmed, Muhammad Mahmood
author_sort Ahmed, Muhammad Mahmood
title Contrast optimization by region adaptation (COBRA) for grey scale images
title_short Contrast optimization by region adaptation (COBRA) for grey scale images
title_full Contrast optimization by region adaptation (COBRA) for grey scale images
title_fullStr Contrast optimization by region adaptation (COBRA) for grey scale images
title_full_unstemmed Contrast optimization by region adaptation (COBRA) for grey scale images
title_sort contrast optimization by region adaptation (cobra) for grey scale images
publishDate 2013
url http://umpir.ump.edu.my/id/eprint/37082/1/Contrast%20optimization%20by%20region%20adaptation%20%28COBRA%29%20for%20grey%20scale%20images.pdf
http://umpir.ump.edu.my/id/eprint/37082/
_version_ 1758578274966962176
score 13.211869

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