An adaptive image enhancement method for a recirculating aquaculture system
Abstract Due to the low and uneven illumination that is typical of a recirculating aquaculture system (RAS), visible and near infrared (NIR) images collected from RASs always have low brightness and contrast. To resolve this issue, this paper proposes an image enhancement method based on the Multi-S...
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| Autores principales: | , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2017
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/d979efcdac8c4589a09c2ffa8c508711 |
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| Sumario: | Abstract Due to the low and uneven illumination that is typical of a recirculating aquaculture system (RAS), visible and near infrared (NIR) images collected from RASs always have low brightness and contrast. To resolve this issue, this paper proposes an image enhancement method based on the Multi-Scale Retinex (MSR) algorithm and a greyscale nonlinear transformation. First, the images are processed using the MSR algorithm to eliminate the influence of low and uneven illumination. Then, the normalized incomplete Beta function is used to perform a greyscale nonlinear transformation. The function’s optimal parameters (α and β) are automatically selected by the particle swarm optimization (PSO) algorithm based on an image contrast measurement function. This adaptive image enhancement method is compared with other classic enhancement methods. The results show that the proposed method greatly improves the image contrast and highlights dark areas, which is helpful during further analysis of these images. |
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