Agent-Based Image Contrast Enhancement Algorithm
One crucial step in several image processing and computer vision applications is Image Contrast Enhancement (ICE), whose main objective is to improve the quality of the information contained in the processed images. Most of the proposed schemes attack the problem by redistributing the pixel intensit...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10017284/ |
| _version_ | 1797945078107340800 |
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| author | Alberto Luque-Chang Erik Cuevas Angel Chavarin Marco Perez |
| author_facet | Alberto Luque-Chang Erik Cuevas Angel Chavarin Marco Perez |
| author_sort | Alberto Luque-Chang |
| collection | DOAJ |
| description | One crucial step in several image processing and computer vision applications is Image Contrast Enhancement (ICE), whose main objective is to improve the quality of the information contained in the processed images. Most of the proposed schemes attack the problem by redistributing the pixel intensities in a histogram, leading to undesirable effects such as noise amplification, over-saturation, and lousy human perception. On the other hand, Agent-Based Models (ABM) are computational models that allow describing the behavior and interactions of autonomous agents when they operate cooperatively. These agents follow behavioral rules rather than mathematical formulations. This mechanism allows the implementation of complex behavioral patterns in agents through their interactions. This paper proposes a two-step method where pixels in the processed image are considered agents whose behavioral rules permit to enhance significatively the contrast. In our approach, the interactions among the agents are characterized by the differences in intensity values among the pixels or agents. In the first step, pixels or agents that present enough high differences in their intensity are modified to increase even more their differences. In the second step, pixels or agents that maintain a very small difference are altered to assume a homogeneous intensity value. The proposed approach has been tested considering different public datasets commonly used in the literature. Its results are also compared with those produced by other well-known ICE techniques. Evaluation of the experimental results demonstrates that the proposed approach highlights the important details of the image taking a lower computational execution time. |
| first_indexed | 2024-04-10T20:49:35Z |
| format | Article |
| id | doaj.art-d816a4fac3ad44ac89fc73c79f9700d4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-10T20:49:35Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d816a4fac3ad44ac89fc73c79f9700d42023-01-24T00:00:54ZengIEEEIEEE Access2169-35362023-01-01116060607710.1109/ACCESS.2023.323708610017284Agent-Based Image Contrast Enhancement AlgorithmAlberto Luque-Chang0https://orcid.org/0000-0001-9636-4850Erik Cuevas1https://orcid.org/0000-0002-0358-6049Angel Chavarin2https://orcid.org/0000-0002-7915-1885Marco Perez3https://orcid.org/0000-0001-6493-0408Departamento de Ingeniería Electro-Fotónica, CUCEI, Universidad de Guadalajara, Guadalajara, MexicoDepartamento de Ingeniería Electro-Fotónica, CUCEI, Universidad de Guadalajara, Guadalajara, MexicoDepartamento de Ingeniería Electro-Fotónica, CUCEI, Universidad de Guadalajara, Guadalajara, MexicoDepartamento de Ingeniería Electro-Fotónica, CUCEI, Universidad de Guadalajara, Guadalajara, MexicoOne crucial step in several image processing and computer vision applications is Image Contrast Enhancement (ICE), whose main objective is to improve the quality of the information contained in the processed images. Most of the proposed schemes attack the problem by redistributing the pixel intensities in a histogram, leading to undesirable effects such as noise amplification, over-saturation, and lousy human perception. On the other hand, Agent-Based Models (ABM) are computational models that allow describing the behavior and interactions of autonomous agents when they operate cooperatively. These agents follow behavioral rules rather than mathematical formulations. This mechanism allows the implementation of complex behavioral patterns in agents through their interactions. This paper proposes a two-step method where pixels in the processed image are considered agents whose behavioral rules permit to enhance significatively the contrast. In our approach, the interactions among the agents are characterized by the differences in intensity values among the pixels or agents. In the first step, pixels or agents that present enough high differences in their intensity are modified to increase even more their differences. In the second step, pixels or agents that maintain a very small difference are altered to assume a homogeneous intensity value. The proposed approach has been tested considering different public datasets commonly used in the literature. Its results are also compared with those produced by other well-known ICE techniques. Evaluation of the experimental results demonstrates that the proposed approach highlights the important details of the image taking a lower computational execution time.https://ieeexplore.ieee.org/document/10017284/Agent-based modelingalgorithmscomplex systemsimage contrast enhancementimage processing |
| spellingShingle | Alberto Luque-Chang Erik Cuevas Angel Chavarin Marco Perez Agent-Based Image Contrast Enhancement Algorithm IEEE Access Agent-based modeling algorithms complex systems image contrast enhancement image processing |
| title | Agent-Based Image Contrast Enhancement Algorithm |
| title_full | Agent-Based Image Contrast Enhancement Algorithm |
| title_fullStr | Agent-Based Image Contrast Enhancement Algorithm |
| title_full_unstemmed | Agent-Based Image Contrast Enhancement Algorithm |
| title_short | Agent-Based Image Contrast Enhancement Algorithm |
| title_sort | agent based image contrast enhancement algorithm |
| topic | Agent-based modeling algorithms complex systems image contrast enhancement image processing |
| url | https://ieeexplore.ieee.org/document/10017284/ |
| work_keys_str_mv | AT albertoluquechang agentbasedimagecontrastenhancementalgorithm AT erikcuevas agentbasedimagecontrastenhancementalgorithm AT angelchavarin agentbasedimagecontrastenhancementalgorithm AT marcoperez agentbasedimagecontrastenhancementalgorithm |