A color space-based framework for enhancing low-light images using CIELAB transformation

Image processing dates to the 1960s when it was first applied to improve image quality. With the increased use of digital products in the form of smartphones and cameras, low-light image improvement has come into sharp focus. Several methods have been adopted such as histogram equalization, illumination map estimation, normalizing flows, neural networks, and dark region aware enhancement. This study offers a function for RGB to CIELAB color space transformation and a step-by-step improvement process. Transformation into CIELAB color space offers the feature of separating brightness and color details and improving contrast and image quality. The device independent CIE 1976 (L*, a*, b*) formula that is well adapted to improve images from different sources is employed. An easy-to-use interface has been implemented, enabling users to download low-light photos and restore the improved ones.