The Retinex enhancement algorithm for low‐light intensity image based on improved illumination map

Autor: Ruidi Weng, Ya Zhang, Hanyang Wu, Weiyong Wang, Dongyun Wang
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IET Image Processing, Vol 18, Iss 12, Pp 3381-3392 (2024)
Druh dokumentu: article
ISSN: 1751-9667
1751-9659
DOI: 10.1049/ipr2.13180
Popis: Abstract Taken in low‐light intensity conditions, image with low brightness affects processing precision. In this article, the Gamma Function based on the brightness average and weighted fusion method according to gray entropy is proposed, which is combined with the improved Retinex algorithm. First, the maximum values of R, G, and B channels in original image are extracted to generate the primary illumination map. Second, the illumination map is optimized and adjusted via the Gamma correction function based on the average brightness value. Finally, the illumination map and detail layer are fused by a weighted fusion algorithm of gray entropy to obtain the reflection map. Reflection maps are used as enhancement. The algorithm proposed in this article can improve the brightness and maintain light distribution in the original image with higher precision and less color distortion.
Databáze: Directory of Open Access Journals
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