Early detection of breast cancer play an important role in reducing mortality due to breast cancer so the enhancement process for mammogram image is necessary to reach the best contrast to enable the radiologist to detect the breast cancer in early stage and reduce the mortality. In breast cancer diagnosis, radiologists use their eyes to detect the cancer in mammogram images, but in many cases cancer is not easily detected by eyes because of the bad imaging quality. In addition, the minor difference between the normal tissue and the malignant disease makes the differentiation very difficult. So it is necessary to find a solution for this problem and reduce the error percentage in the tumor diagnosis, hence, help in the early detection of the breast cancer. Therefore, contrast enhancement of the mammogram images is the subject of this thesis. The aim of this thesis is the development of a reliable algorithm to enhance early signs of breast cancer in mammogram images. The research in this thesis aims to help radiologists to detect breast cancer at early stage. The proposed image-enhancement algorithms have promising performance that would improve the accuracy of cancer breast diagnosis and detection, especially in the case of small tumor detection at early stages. The proposed techniques enhance the suspicious region only on the mammogram image. Thus an expert can determine whether an image is a cancerous image or not by determining if it includes calcification regions or mass regions. All the mammographic images used in this thesis correspond to real cases and were obtained from the department of Radiodiagnosis in Faculty of Medicine at Zagazig University and from the Egyptian Cancer Institute.