Mohammad saleh Miri - Tarbiat Modares University
Ali Mahloojifar - Tarbiat Modares University

Medical images typically own characteristics, due to the acquistion process or the intrinsic attribute of the type of modality , which make them improper for subsequence processing . Having low dynamic ronge , improper image contrast and presence of noise are some example of these characteristics. Hence , pre - processing algorithms are necessary to apply. curvelet transfum , a new geometric multi- scale transform, is well adapted to represent the images containing edges ;so that , it can be a proper candidote to enhance the medical images based on modification of the curvelet transform coefficients by a nonlinear function. Function parameters are defined based on the statistic features of the input image in order to better adopt the function with the input image . the method was applies to several modalities and results showed high performance in enhancing the image contrast and improving the image representation.

Digital Curvelet Transform, medical images , image enhancement