(Received: 14-Jan.-2024, Revised: 11-Mar.-2024 , Accepted: 13-Mar.-2024)
Nowadays, people are active during the nighttime and take many photos to record their activities. Due to the low- light nature of the environment at nighttime, captured images tend to appear with dimmed and imbalanced illumination, limited contrast, covert noise and diminished colors. Thus, this paper presents a practical algorithm to improve the illumination of nighttime images based on the single-scale retinex model, image processing methods and certain statistical functions. The developed algorithm initiates by converting the image from the RGB into the HSV model. Then, it enhances only the value (V) channel while preserving the H and S channels. Next, estimating the illumination version of the image and calculating the logarithms of both the illumination and original image are performed. Afterward, a logarithmic subtraction occurs and a modified cumulative distribution function of Gumble probability is applied and the result is further enhanced using a logarithmic transform method. These operations produce the processed V channel and a conversion to the RGB format occurs to generate the final output. The proposed algorithm is experimented with by using two datasets, compared to ten different contemporary algorithms and outcomes are evaluated via three sophisticated metrics. Based on the attained results, promising performances by the developed algorithm have been recorded, surpassing the performance of many existing algorithms in various objective, subjective and runtime terms.

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