Improving Low-Light Images Using an Advanced Histogram Equalization Method and a Self-Calibrated Illumination Technique

The main purpose of this paper is to implement an image enhancement technique which is widely used in various fields such as agriculture, industry, military, and medicine. In all these fields, image contrast plays a crucial role. The main approach which has been applied to enhance grayscale images is the hybrid effect of histogram equalization (HE) and self-calibrated illumination method (SCIM). The main task is to apply Histogram Equalization (HE) to the input image as a result the brightness of the image gets improved. Following this SCIM is employed to the equalized image. The effect of applying SCIM is to recover the details which has been lost in low-light condition. The main parameters which are used are the intensity of picture element called pixels and frequency. The suggested method is compared with other previous methods like CUCKOO Search method, Linear Regression, CLAHE and BPDHE, and BBHE. The Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), and Contrast Improvement Ratio (CIR) of the enhanced image obtained by various methods, and our method is calculated and compared. The analysis of this comparison is made in the result and discussion section. From these analyses, it has been found that our proposed method is superior to all the state-of-the-art methods. The suggested hybrid method not only gives the aesthetically pleasing result but also helps in maintaining contrast and original details, thus proving its authenticity.