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Author  |
Patricia Suarez; Dario Carpio; Angel Sappa; Henry Velesaca | ||||
| Title | Transformer based Image Dehazing | Type | Conference Article | ||
| Year | 2022 | Publication | 16th IEEE International Conference on Signal Image Technology & Internet Based System | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | atmospheric light; brightness component; computational cost; dehazing quality; haze-free image | ||||
| Abstract | This paper presents a novel approach to remove non homogeneous haze from real images. The proposed method consists mainly of image feature extraction, haze removal, and image reconstruction. To accomplish this challenging task, we propose an architecture based on transformers, which have been recently introduced and have shown great potential in different computer vision tasks. Our model is based on the SwinIR an image restoration architecture based on a transformer, but by modifying the deep feature extraction module, the depth level of the model, and by applying a combined loss function that improves styling and adapts the model for the non-homogeneous haze removal present in images. The obtained results prove to be superior to those obtained by state-of-the-art models. | ||||
| Address | Dijon; France; October 2022 | ||||
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| Area | Expedition | Conference | SITIS | ||
| Notes | MSIAU; no proj | Approved | no | ||
| Call Number | Admin @ si @ SCS2022 | Serial | 3803 | ||
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