Low-Light Image Enhancement with Optimized Gamma Correction using Guided Filter

In recent days, with the increasing use of images in various applications such as surveillance and medical diagnosis, the need for efficient Low-Light (LL) image enhancement techniques has become more pressing. However, the existing methods struggled to improve the brightness of an image and suppress noise effectively. Hence, this research proposes Optimized GC using Guided Filter (OGC-GF) for LL image enhancement. Initially, the input data is collected from Digital Image Contrast Modulation (DICM) dataset, which contains LL images that are captured with digital cameras. Then, a gamma correction map is generated as a LL image with similar size by encompassing gamma correction single global parameter. After that, the gamma correction map is optimized by using GF to smooth the map while providing a guidance image to compute the filtering output by preserving edges. Finally, the OGC map is applied to the enhanced image, as it results in a reduced noise and brightness and detail preserved output. From the results, the proposed OGC-GF model attained better results when compared to existing Edge Preserving Method (EPM) in terms of Text Preservation and Noise Suppression (TPNS) metric as 0.113 respectively.