Preserving brightness in histogram equalization based contrast enhancement techniques
Histogram equalization (HE) has been a simple yet effective image enhancement technique. However, it tends to change the brightness of an image significantly, causing annoying artifacts and unnatural contrast enhancement. Brightness preserving bi-histogram equalization (BBHE) and dualistic sub-image...
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Elsevier Inc.
2023
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| author | Chen S.-D. Ramli A.R. |
| author2 | 7410253413 |
| author_facet | 7410253413 Chen S.-D. Ramli A.R. |
| author_sort | Chen S.-D. |
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| content_provider | Universiti Tenaga Nasional |
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| continent | Asia |
| country | Malaysia |
| description | Histogram equalization (HE) has been a simple yet effective image enhancement technique. However, it tends to change the brightness of an image significantly, causing annoying artifacts and unnatural contrast enhancement. Brightness preserving bi-histogram equalization (BBHE) and dualistic sub-image histogram equalization (DSIHE) have been proposed to overcome these problems but they may still fail under certain conditions. This paper proposes a novel extension of BBHE referred to as minimum mean brightness error bi-histogram equalization (MMBEBHE). MMBEBHE has the feature of minimizing the difference between input and output image's mean. Simulation results showed that MMBEBHE can preserve brightness better than BBHE and DSIHE. Furthermore, this paper also formulated an efficient, integer-based implementation of MMBEBHE. Nevertheless, MMBEBHE also has its limitation. Hence, this paper further proposes a generalization of BBHE referred to as recursive mean-separate histogram equalization (RMSHE). RMSHE is featured with scalable brightness preservation. Simulation results showed that RMSHE is the best compared to HE, BBHE, DSIHE, and MMBEBHE. � 2004 Elsevier Inc. All rights reserved. |
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| id | my.uniten.dspace-29874 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Elsevier Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-298742023-12-28T16:58:01Z Preserving brightness in histogram equalization based contrast enhancement techniques Chen S.-D. Ramli A.R. 7410253413 26428905000 Bi-histogram equalization Dualistic sub-image Histogram equalization Mean separate Minimum mean brightness error Recursive Algorithms Computer simulation Entropy Image analysis Probability Statistical methods Virtual reality Bi-histogram equalization Dualistic sub-image Histogram equalization Mean separate Minimum mean brightness error Recursive Digital signal processing Histogram equalization (HE) has been a simple yet effective image enhancement technique. However, it tends to change the brightness of an image significantly, causing annoying artifacts and unnatural contrast enhancement. Brightness preserving bi-histogram equalization (BBHE) and dualistic sub-image histogram equalization (DSIHE) have been proposed to overcome these problems but they may still fail under certain conditions. This paper proposes a novel extension of BBHE referred to as minimum mean brightness error bi-histogram equalization (MMBEBHE). MMBEBHE has the feature of minimizing the difference between input and output image's mean. Simulation results showed that MMBEBHE can preserve brightness better than BBHE and DSIHE. Furthermore, this paper also formulated an efficient, integer-based implementation of MMBEBHE. Nevertheless, MMBEBHE also has its limitation. Hence, this paper further proposes a generalization of BBHE referred to as recursive mean-separate histogram equalization (RMSHE). RMSHE is featured with scalable brightness preservation. Simulation results showed that RMSHE is the best compared to HE, BBHE, DSIHE, and MMBEBHE. � 2004 Elsevier Inc. All rights reserved. Final 2023-12-28T08:58:01Z 2023-12-28T08:58:01Z 2004 Article 10.1016/j.dsp.2004.04.001 2-s2.0-4544281066 https://www.scopus.com/inward/record.uri?eid=2-s2.0-4544281066&doi=10.1016%2fj.dsp.2004.04.001&partnerID=40&md5=03b3dd716b6c87cb1a5de873fe3fa8b1 https://irepository.uniten.edu.my/handle/123456789/29874 14 5 413 428 All Open Access; Green Open Access Elsevier Inc. Scopus |
| spellingShingle | Bi-histogram equalization Dualistic sub-image Histogram equalization Mean separate Minimum mean brightness error Recursive Algorithms Computer simulation Entropy Image analysis Probability Statistical methods Virtual reality Bi-histogram equalization Dualistic sub-image Histogram equalization Mean separate Minimum mean brightness error Recursive Digital signal processing Chen S.-D. Ramli A.R. Preserving brightness in histogram equalization based contrast enhancement techniques |
| title | Preserving brightness in histogram equalization based contrast enhancement techniques |
| title_full | Preserving brightness in histogram equalization based contrast enhancement techniques |
| title_fullStr | Preserving brightness in histogram equalization based contrast enhancement techniques |
| title_full_unstemmed | Preserving brightness in histogram equalization based contrast enhancement techniques |
| title_short | Preserving brightness in histogram equalization based contrast enhancement techniques |
| title_sort | preserving brightness in histogram equalization based contrast enhancement techniques |
| topic | Bi-histogram equalization Dualistic sub-image Histogram equalization Mean separate Minimum mean brightness error Recursive Algorithms Computer simulation Entropy Image analysis Probability Statistical methods Virtual reality Bi-histogram equalization Dualistic sub-image Histogram equalization Mean separate Minimum mean brightness error Recursive Digital signal processing |
| url_provider | http://dspace.uniten.edu.my/ |