Some studies using curvelet transform in image processing
have been done. Ali et al. presented a curvelet approach
for the fusion of Magnetic Resonance (MR) and Computed
Tomography (CT) images. They found that curvelet transform
achieved good results in their fusion. Bind and Tahan
presented a method for object detection of speckle image
based on curvelet transform. They constructed a segmentation
method which provides a sparse expansion for typical images
having smooth contours. Murtagh and Stark used second,
third and fourth order moment of Multiresolution transform
(wavelet and curvelet) coefficients as features, and K-nearest
neighbors supervised classifier for image classification
process.