In this paper, a novel feature extraction scheme is proposed, based on multiresolution fast discrete curvelet transform for computer-aided diagnosis of liver diseases. The liver is segmented from CT images using adaptive threshold detection and morphological processing. The suspected tumour region is extracted from the segmented liver using FCM clustering. The textural information obtained from...

Multiresolution methods are deeply related to image processing, biological and computer vision, scientific computing, etc. The curvelet transform is a multiscale directional transform which allows an almost optimal nonadaptive sparse representation of objects with edges. It has generated increasing interest in the community of applied mathematics and signal processing over the past years. In th...

A new theory named compressed sensing for simultaneous sampling and compression of signals has been becoming popular in the communities of signal processing, imaging and applied mathematics. In this paper, we present improved/accelerated iterative curvelet thresholding methods for compressed sensing reconstruction in the fields of remote sensing. Some recent strategies including Bioucas-Dias an...

We present in this paper new multiscale transforms on the sphere, namely the isotropic undecimated wavelet transform, the pyramidal wavelet transform, the ridgelet transform and the curvelet transform. All of these transforms can be inverted i.e. we can exactly reconstruct the original data from its coefficients in either representation. Several applications are described. We show how these tra...

In this paper, a random sampling scheme based on Compressive Sensing (CS) is used in order to reduce the acquisition time of wavefield signals by means of a scanning laser Doppler vibrometer (SLDV) for Structural Health Monitoring (SHM) applications. The sampling process is indeed quite time consuming, because of noise sources and reduced amplitude of acquired signals. By virtue of the sparse c...

In this paper, a novel face recognition approach based on wavelet-curvelet technique, is proposed. This algorithm based on the similarities embedded in the images, That utilize the wavelet-curvelet technique to extract facial features. The implemented technique can overcome on the other mathematical image analysis approaches. This approaches may suffered from the potential for a high dimensiona...

White Blood Cancer is one of the deadliest diseases for human being and its presence can be early diagnosed by detecting the existence of nucleolus in White Blood Cells (WBC) of peripheral blood smear images. In this paper, the author would like to compare the performance of nucleolus candidate zone extraction algorithm by utilizing Wavelet transforms and Curvelet transform. The result confirms...

This paper provides a comparative study of the performance of different Transform Domain filters like Wavelet, Contourlet, Bandelet and Curvelet with Firefly Algorithm (FA) applied to despeckle Synthetic Aperture Radar (SAR) images. Initially the feature enhancement and edge detection of speckled SAR image are integrated with improved gain function by shrinking and stretching the Wavelet Co-eff...

Super resolution is the process of reconstructing high resolution(HR) image from multiple low resolution(LR) images of a scene . LR images are at a specific pixel shift from each other. High Resolution(HR) grids are formed from these LR images using Stationary Wavelet Transform (SWT) by image registration. Interpolation of the missing pixel in the HR grid is done using Curvelet Transform(CT). E...