Using S-Curve Transforms and Gamma Correction for MR Images Contrast Enhancement

Facilitating diagnosis and therapy. A common degradation in MR images is deficient contrast. This degradation affects the image with a layer of murkiness, reducing the clarity of details. Various contrast enhancement (CE) methods produce unsatisfactory results due to brightness amplification or artifact generation. Therefore, an effective CE algorithm called (WRGC) is introduced, which depends on two transformations of Weibull (W) and Rayleigh (R) distribution with modified gamma correction (GC), applied separately. The three resulting images are combined to obtain the features of all three images using an adapted logarithmic addition method. Finally, the output image is acquired by applying the normalization method. The proposed algorithm is tested with many degraded MR images obtained from the CTisus website. Moreover, it was compared with four different CE approaches and evaluated using three measures. The results showed that the proposed method outperformed many existing CE algorithms and provided satisfactory visual details and contrast-adjusted results.