MRI Edge Detection And Noise Reduction With Curvelet Transform

In recent years multi scale transform application in image processing especially for magnetic resonance (MR) images has been raised. Wavelet transform is introduced as a useful tool in image processing and it is capable of effectively removing noise from magnetic resonance images. The main problem with wavelet transform is that it is not able to distinguish one dimensional or higher dimentional discontinuities in images. A proposed solution for this issue is an inseparable transform which is named Curvelet. Time frequency transform based noise elimination methods, usually rely on thresholding. In curvelet method, by setting a hard threshold at low levels of noise the obtained similarity index is 0.9254. which on average leads to 5 percent improvement compared with wavelet method. The results show the efficiency of this method in different parts of image processing on simulated and actual MR images.