This paper deals with cutting-edge techniques in image processing, addressing critical aspects such as edge detection, noise cancellation, histogram analysis, image compression, and upgradation using MATLAB. Evaluating both traditional and deep learning approaches, the study explores methods to enhance image quality, reduce noise, optimize contrast through histogram manipulation, and implement efficient compression algorithms. MATLAB’s image processing toolbox facilitates the implementation and validation of these techniques, with results demonstrating significant improvements in various aspects of image enhancement. This research contributes a versatile toolkit for researchers, practitioners, and enthusiasts in the field of digital image processing, catering to diverse applications from medical imaging to computer vision.