A Novel Gabor Filtering and Adaptive Histogram Equalization Method for Improving Images

Abstract

The correct information may only sometimes be effectively conveyed by images due to various factors, such as excessively bright or dark lighting and low or high contrast. As a result, picture improvement has become an essential part of digital image processing. This proposed method aims to develop an algorithm for improving photos captured in dark environments. This letter presents a new picture-enhancing approach that combines median and Gabor filtering using the wavelet domain with histogram equalization working over a spatial domain. The proposed method in this paper combines spatial and transformed domains for image enhancement and has been simulated using MATLAB. The simulation results of two different photos show that the suggested approach extends the histogram over a wide range of grayscale, offering a superior improvement to the original image. The novel proposed algorithm aims to improve image quality and visibility, making identifying essential details within the image easier. Further, the proposed technique's success is manifested by examining the produced photos' contrast and brightness. The findings reveal that the suggested technique beats the other strategies for improving low-contrast photos.