A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement
Image Enhancement is one of the mainly significant with complex techniques in image study. The purpose of image enhancement is to advance the optical presence of an image, or to support a “improved convert representation for future mechanized image processing. Various images similar medical images,...
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| Format: | Article |
| Language: | English |
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College of Computer and Information Technology – University of Wasit, Iraq
2024-04-01
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| Series: | Wasit Journal of Computer and Mathematics Science |
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| Online Access: | https://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/202 |
| _version_ | 1797198900423032832 |
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| author | Ahmed Naser |
| author_facet | Ahmed Naser |
| author_sort | Ahmed Naser |
| collection | DOAJ |
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Image Enhancement is one of the mainly significant with complex techniques in image study. The purpose of image enhancement is to advance the optical presence of an image, or to support a “improved convert representation for future mechanized image processing. Various images similar medical images, satellite images, natural with even real life photographs which have a lowly contrast and noise. This study presents a new enhancement technique based on standard contrast limited adaptive histogram equalization (CLAHE) technique for image enhancement which its name CLCOA. The suggested technique depends on augmentation of swarm intelligence via using Cat Swarm Optimization algorithm (CSO). The swarm intelligence is used to obtain the optimal structure of CLAHE technique. Tomato plant images have used and applied as dataset because of its important and influence in our life. For fair analysis of two techniques, Absolute Mean Brightness Error (AMBE), peak signal-to-noise ratio (PSNR), entropy and Contrast Gain of fundus images are analyzed by using MATLAB. The results show that performance of the proposed technique reveals the efficiently and robustness when compared results of standard technique.
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| first_indexed | 2024-04-24T07:07:12Z |
| format | Article |
| id | doaj.art-1357067f0b3c4017ae572464f4019cef |
| institution | Directory Open Access Journal |
| issn | 2788-5879 2788-5887 |
| language | English |
| last_indexed | 2024-04-24T07:07:12Z |
| publishDate | 2024-04-01 |
| publisher | College of Computer and Information Technology – University of Wasit, Iraq |
| record_format | Article |
| series | Wasit Journal of Computer and Mathematics Science |
| spelling | doaj.art-1357067f0b3c4017ae572464f4019cef2024-04-21T17:26:17ZengCollege of Computer and Information Technology – University of Wasit, IraqWasit Journal of Computer and Mathematics Science2788-58792788-58872024-04-013110.31185/wjcms.202A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images EnhancementAhmed Naser0University of Basrah - Department of Management Information Systems Image Enhancement is one of the mainly significant with complex techniques in image study. The purpose of image enhancement is to advance the optical presence of an image, or to support a “improved convert representation for future mechanized image processing. Various images similar medical images, satellite images, natural with even real life photographs which have a lowly contrast and noise. This study presents a new enhancement technique based on standard contrast limited adaptive histogram equalization (CLAHE) technique for image enhancement which its name CLCOA. The suggested technique depends on augmentation of swarm intelligence via using Cat Swarm Optimization algorithm (CSO). The swarm intelligence is used to obtain the optimal structure of CLAHE technique. Tomato plant images have used and applied as dataset because of its important and influence in our life. For fair analysis of two techniques, Absolute Mean Brightness Error (AMBE), peak signal-to-noise ratio (PSNR), entropy and Contrast Gain of fundus images are analyzed by using MATLAB. The results show that performance of the proposed technique reveals the efficiently and robustness when compared results of standard technique. https://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/202CLAHE 2peak signal-to-noise ratio (PSNR) Cat Swarm Optimization algorithm image enhancement |
| spellingShingle | Ahmed Naser A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement Wasit Journal of Computer and Mathematics Science CLAHE 2 peak signal-to-noise ratio (PSNR) Cat Swarm Optimization algorithm image enhancement |
| title | A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement |
| title_full | A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement |
| title_fullStr | A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement |
| title_full_unstemmed | A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement |
| title_short | A proposed CLCOA Technique Based on CLAHE using Cat Optimized Algorithm for Plants Images Enhancement |
| title_sort | proposed clcoa technique based on clahe using cat optimized algorithm for plants images enhancement |
| topic | CLAHE 2 peak signal-to-noise ratio (PSNR) Cat Swarm Optimization algorithm image enhancement |
| url | https://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/202 |
| work_keys_str_mv | AT ahmednaser aproposedclcoatechniquebasedonclaheusingcatoptimizedalgorithmforplantsimagesenhancement AT ahmednaser proposedclcoatechniquebasedonclaheusingcatoptimizedalgorithmforplantsimagesenhancement |