A novel joint histogram equalization based image contrast enhancement
The limitation to the most commonly used histogram equalization (HE) technique is the inconsideration of the neighborhood info near each pixel for contrast enhancement. This gives rise to noise in the output image. To overcome this effect, a novel joint histogram equalization (JHE) based technique i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-04-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157819303635 |
| _version_ | 1828134438699008000 |
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| author | Sanjay Agrawal Rutuparna Panda P.K. Mishro Ajith Abraham |
| author_facet | Sanjay Agrawal Rutuparna Panda P.K. Mishro Ajith Abraham |
| author_sort | Sanjay Agrawal |
| collection | DOAJ |
| description | The limitation to the most commonly used histogram equalization (HE) technique is the inconsideration of the neighborhood info near each pixel for contrast enhancement. This gives rise to noise in the output image. To overcome this effect, a novel joint histogram equalization (JHE) based technique is suggested. The focus is to utilize the information among each pixel and its neighbors, which improves the contrast of an image. The suggested method is developed in a truly two-dimensional domain. The joint histogram is constructed using the original image and its average image. Further, it does not require a target uniform distribution for generating the output. The two-dimensional cumulative distribution function (CDF) is utilized as a mapping function to get the output pixel intensity. Extensive experiments are performed using 300 test images from BSD database. The experimental analysis indicates that the procedure produces better results than the state-of-the-art HE based contrast enhancement algorithms. More significantly, it produces the best results even for images having a narrow dynamic range. The implementation simplicity of the proposed algorithm may attract researchers to explore the idea for new applications in image processing. |
| first_indexed | 2024-04-11T17:34:23Z |
| format | Article |
| id | doaj.art-4f753a2af4a0457cabe7d779efd7d10e |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-11T17:34:23Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-4f753a2af4a0457cabe7d779efd7d10e2022-12-22T04:11:39ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782022-04-0134411721182A novel joint histogram equalization based image contrast enhancementSanjay Agrawal0Rutuparna Panda1P.K. Mishro2Ajith Abraham3Department of Electronics and Telecommunication Engineering, Veer Surendra Sai University of Technology, Burla, IndiaDepartment of Electronics and Telecommunication Engineering, Veer Surendra Sai University of Technology, Burla, India; Corresponding author.Department of Electronics and Telecommunication Engineering, Veer Surendra Sai University of Technology, Burla, IndiaMachine Intelligence Research Labs, Washington, USAThe limitation to the most commonly used histogram equalization (HE) technique is the inconsideration of the neighborhood info near each pixel for contrast enhancement. This gives rise to noise in the output image. To overcome this effect, a novel joint histogram equalization (JHE) based technique is suggested. The focus is to utilize the information among each pixel and its neighbors, which improves the contrast of an image. The suggested method is developed in a truly two-dimensional domain. The joint histogram is constructed using the original image and its average image. Further, it does not require a target uniform distribution for generating the output. The two-dimensional cumulative distribution function (CDF) is utilized as a mapping function to get the output pixel intensity. Extensive experiments are performed using 300 test images from BSD database. The experimental analysis indicates that the procedure produces better results than the state-of-the-art HE based contrast enhancement algorithms. More significantly, it produces the best results even for images having a narrow dynamic range. The implementation simplicity of the proposed algorithm may attract researchers to explore the idea for new applications in image processing.http://www.sciencedirect.com/science/article/pii/S1319157819303635Contrast enhancementHistogram equalizationJoint histogramImage processing |
| spellingShingle | Sanjay Agrawal Rutuparna Panda P.K. Mishro Ajith Abraham A novel joint histogram equalization based image contrast enhancement Journal of King Saud University: Computer and Information Sciences Contrast enhancement Histogram equalization Joint histogram Image processing |
| title | A novel joint histogram equalization based image contrast enhancement |
| title_full | A novel joint histogram equalization based image contrast enhancement |
| title_fullStr | A novel joint histogram equalization based image contrast enhancement |
| title_full_unstemmed | A novel joint histogram equalization based image contrast enhancement |
| title_short | A novel joint histogram equalization based image contrast enhancement |
| title_sort | novel joint histogram equalization based image contrast enhancement |
| topic | Contrast enhancement Histogram equalization Joint histogram Image processing |
| url | http://www.sciencedirect.com/science/article/pii/S1319157819303635 |
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