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- Li, Dayi, et al.
(författare)
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Adaptive weighted multiscale retinex for underwater image enhancement
- 2023
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Ingår i: Engineering applications of artificial intelligence. - Amsterdam : Elsevier. - 0952-1976 .- 1873-6769. ; 123
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Tidskriftsartikel (refereegranskat)abstract
- Vision-dependent underwater vehicles are widely used in seabed resource exploration. The visual perception system of underwater vehicles relies heavily on high-quality images for its regular operation. However, underwater images taken underwater often have color distortion, blurriness, and poor contrast. To address these degradation issues, we develop an adaptive weighted multiscale retinex (AWMR) method for enhancing underwater images. To utilize the local detail features, we first divide the image into multiple sub-blocks and calculate the detail sparsity index for each one. Then, we combine the global detail sparsity index with the local detail sparsity indices to determine the optimal scale parameter and corresponding weights for each sub-block. We apply retinex processing to each sub-block using these parameters and then subject the processed sub-blocks to detail enhancement, color correction, and saturation correction. Finally, we use a gradient domain fusion method based on structure tensors to fuse the corrected and enhanced sub-blocks and obtain the final output image. Our approach improves underwater images through comparisons with current state-of-the-art (SOTA) techniques on several open-source datasets, both quality, and performance. © 2023 Elsevier Ltd
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| 2. |
- Liu, Wei, Assistant Professor, 1987-, et al.
(författare)
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Inverse design of a thermally comfortable indoor environment with a coupled CFD and multi-segment human thermoregulation model
- 2023
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Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323 .- 1873-684X. ; 227
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Tidskriftsartikel (refereegranskat)abstract
- A thermally comfortable indoor environment is critical for ensuring the health and productivity of the occupants. To design a thermally comfortable environment, CFD-based methods assume the occupants' surface temperature to be fixed values for simplicity and use PMV to estimate thermal comfort level. The constant surface temperature assumption would lead to inaccurate prediction of the indoor environment and the use of PMV would lead to a waste of the rich spatial information calculated by CFD. Therefore, this study developed and validated a coupled CFD and multi-node human thermoregulation model (HTM). The CFD and HTM synchronize data during the simulation and the occupant skin temperature could be updated. The final skin temperature could be used to quantify the thermal comfort level. The accuracy of the coupled model in predicting the skin temperature was validated by experimental data from literature. The coupled model was further integrated with genetic algorithm for inverse design. The inverse design of thermal environment in an office with two occupants and displacement ventilation was used for demonstration. With the CFD-HTM model, genetic algorithm was able to identify an optimal condition that leads to the least deviation of skin temperature of local body parts from the neutral values. The developed CFD-HTM coupling scheme can be used to effectively design indoor environment with improved thermal comfort.
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