Image processing is an essential element in current computer vision, which provides the computational framework necessary for the analysis, enhancement, and interpretation of visual data. Because it facilitates the transformation of raw image data into structured, meaningful outputs, thereby supporting a wide range of applications in fields such as agriculture, medical imaging, surveillance, remote sensing, and biometric systems. This review provides an in-depth exploration of key techniques in digital image processing, including enhancement, restoration, compression, object recognition, and segmentation. Each technique is explored concerning its theoretical foundations and practical significance, highlighting its contribution to enabling accurate and efficient interpretation of visual data.