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Superpixel-Guided Dark Channel Prior for Efficient Single Image Dehazing | ||
| Journal of Algorithms and Computation | ||
| دوره 57، شماره 2، اسفند 2025، صفحه 170-186 اصل مقاله (2.23 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jac.2025.400037.1239 | ||
| نویسندگان | ||
| Hossein Noori* 1؛ Mohammad Hossein Gholizadeh2؛ Gholamreza Memarzadeh2 | ||
| 1Vali-e-Asr university of rafsanjan | ||
| 2Department of electrical engineering | ||
| چکیده | ||
| Outdoor cameras play a vital role in security and social governance systems. However, bad weather can significantly reduce image quality. This can hinder the effectiveness of these systems. This study proposes a new method to remove fog from images captured by outdoor cameras. Unlike traditional methods that analyze small square areas of the image, our approach works with superpixels, which are smarter groupings of pixels. The algorithm first calculates the ”dark channel” for each superpixel. The proposed method then merges superpixels with close dark channel values. To prevent unwanted halos around objects after removing the fog, the algorithm applies ”guided filtering” to the merged dark channel. The effectiveness of this new approach is compared to existing methods using various tests that measure image quality. The results show that the proposed method outperforms existing algorithms. This allows for clearer images and improved performance of security and social governance systems. Details and numerical rsults might be seen at https://my.uupload.ir/dl/v9EnmnBr. | ||
| کلیدواژهها | ||
| Defogging/dehazing؛ superpixel segmentation؛ visibility enhancement؛ dark channel improvement؛ region aggregating | ||
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آمار تعداد مشاهده مقاله: 94 تعداد دریافت فایل اصل مقاله: 54 |
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