Due to the restrictions of image-catching gadgets or the presence of a non-ideal environment, the quality of digital images may get corrupted. Much of the time, these images might demand a certain level of enhancement for satisfactory visual representation. Image enhancement is a procedure to evacuate the undesirable distortion due to deterioration in contrast, unwanted noise, improper intensity saturation, blurring effect, etc., and determine the hidden information that are contained in images. The main goal of Image enhancement is to process an image so that the result is more suitable than original image for particular application. Many image enhancement techniques are based on spatial operations performed on local neighborhoods of input pixels. Conventional global histogram equalization few times becomes a reason for immoderate contrast enhancement, thus local histogram equalization may cause block effect. Therefore to conquer these problems, a new way for image contrast enhancement is presented in this research work. The curiosity of the proposed strategy is that the weighted average of the histogram equalized, gamma corrected, and the original image are combined to obtain the enhanced processed image. The proposed algorithm not only achieves contrast enhancement, but also preserves a sufficient level of brightness level. This study will highlight various image enhancement techniques along with their benchmark results. Empirical study results demonstrate that the proposed algorithm has good performance on enhancing contrast and clarity for a larger part of images.