Low Lightness Image Enhancement Using Modified DCP Based Lightness Mapping in Lab Color Space

Enhancement of images with low light has become an important role in the field of digital image processing, especially when you take the image at low or irregular lighting levels. In this study, a new algorithm was proposed to enhance images with low light based on the development of the Dark Chanel Prior (DCP), Where the image was first improved using this DCP then the lightness component in (Lab) space was improved using the sigmoid mapping. The proposed method was compared with several algorithms by using non-reference quality measures as naturalness image quality evaluator and image quality evaluator using LIME data. By analyzing the results we note the success of the proposed method in improving images with low light, with obtaining the best contrast and lightness compared to the rest of the methods, where the proposed method obtained the best quality values of natural image quality evaluator (3.462) and perception image quality evaluator (35.714).