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Over the last decade image processing has emerged as a fledging field of research and development in the context of procedures of processing image towards enhancement and restoration of degraded or blurred images. Digital image processing encompasses two tasks: (i) improvement of information presented by the picture for a clear interpretation and (ii) processing of a picture data for automatic machine recognition. Today’s digital image processing offers a broad range of applications such as remote sensing, image and data storage for transmission in business applications, medical imaging, acoustic imaging, forensic sciences and industrial automation. In medical imaging, an important task is to post processing image as regards detection/isolation of disorders (e.g. Tumours etc.) in subjects (patients) for screening. The present project work is to study a few different image processing operations namely, image histogram equalization that improves the image contrast and image filtering operation which enables restoration of some degraded image. While improving a degraded image that consists of pepper salt noise, a suitable filtering scheme is applied to restore them. Typical example cases are studied in this approach and results are illustrated. The next part of the project deals with another very useful image processing operation that involves translating a grayscale image to the corresponding binary image format. The enhancement is recorded in terms of sharpness of the edge of the image under test. Typical example cases are studied in this work to demonstrate the efficacy of the approach. All the codes applied to validate the image processing for the present project work are written in C- platform and are cited in the report.