Medical X-ray images are widely used for clinical diagnosis, providing crucial information for healthcare professionals. However, the quality of these images can be compromised due to factors such as human body structure, equipment limitations, and environmental interferences. This study focuses on enhancing the quality of X-ray images using various techniques. In this research, we suggest a novel approach BBHE-DSIHE method aimed at improving the quality of chest X-ray. It is a two-step approach for enhancing medical X-ray images, specifically focusing on dehazing techniques. The effectiveness of these techniques is evaluated through experiments conducted with different parameter settings. The BBHE-DSIHE method aims to improve image clarity and contrast, facilitating better diagnostic accuracy. The efficiency of the suggested approach is evaluated using the NIH Chest X-ray dataset. Our objective is to identify the most optimal methods for chest X-ray image. After analysing the experimental results, we found that our method demonstrates superior performance for PSNR parameter falling within the range of 30-50dB. Our method has slightly less Structural Similarity Index (SSIM) value as compared to DSIHE but it compensates that loss for the reduction in Mean Square Error (MSE) value. By employing this technique, we aim to improve the standard of medical X-rays images, thereby assisting healthcare professionals in accurate diagnosis and treatment planning.