An Improved Retinex Method for Low Light Image Enhancement - Keerthi , Halaharvi; B., Sreepathi (International Journal of Intelligent Systems and Applications in Engineering, 2022)
Enhancement of low-light image is difficult because it must account for not just brightness recovery but also more sophisticated concerns such as colour distortion and noise that are often hidden in dark. Increasing the brightness of a low-light image, even slightly, can make these artefacts more noticeable. Image enhancement in low-light circumstance from the surveillance system plays a very important role for the security purpose. This is an active research topic, where many algorithms are proposed for magnifying the intensity of dark images. To overcome this issue a unique end-to-end attention-guided technique based on retinex is proposed. Here many effective image enhancement methods are ground on retinex theory. Subsequently diverse algorithms are used such as single scale retinex (SSR), multiscale retinex (MSR), multiscale retinex with color restoration (MSRCR) models. color space model is applied with retinex algorithm. To boost the quality and brightness of image; gamma correction with multiple values are used before applying Improved Multi Scale Retinex with CIELAB color (IMSRLab) on image. Extensive testing on standard LOL datasets demonstrates that our method is capable of delivering high fidelity enhancement outcomes for lowlight images, and that it outperforms existing state-of-the-art methods both statistically and visually. These findings were gleaned from comparisons of the two methods using the LOL datasets.