In this paper, we present the first 3D discrete curvelet transform. This transform is an extension to the 2D transform described in Candès et al.. The resulting curvelet frame preserves the important properties, such as parabolic scaling, tightness and sparse representation for singularities of codimension one. We describe three different implementations: in-core, out-of-core and MPI-based para...

Curvelet transform is a multidirectional multiscale transform that enables sparse representations for signals. Curvelet-based feature extraction for Synthetic Aperture Radar (SAR) naturally enables utilizing spatial locality; the use of curvelet-based feature extraction is a novel method for SAR clustering. The implemented method is based on curvelet subband Gaussian distribution parameter esti...

An approach of palmprint feature extraction based on the second frequency band curvelet coefficients is proposed in this paper. As we all know, the veins of the palmprint are the important factors to recognize the palmprint. Because curvelet transform can effectively presents the lines and curvilinear structure, we perform the curvelet transform to the palmprint image. By analyzing the features...

Curvelet is often used in image multi-scale analysis for its description ability to the image edges such as curve and line characteristics. On the basis of analyzing several common algorithms of image fusion, a new multi-focus image fusion method based on Curvelet transform is proposed according to the question of image fusion. The principle of Curvelet transform is described and the fusion rul...

This study presents a framework for gray texture classification based on wavelet and curvelet features. The two main frequency domain transformations Discrete Wavelet Transform (DWT) and Discrete Curvelet Transform (DCT) are analyzed. The features are extracted from the DWT and DCT decomposed image separately and their performances are evaluated independently. The performance metric used to ana...

Image Fusion is a combination of two or more different images. It extracts the information from multiple source images. Wavelet based image fusion is suitable for representing the point singularities in one dimensions, but it fails to represent the edges across the curves in two dimensions. In this method, pixel level fusion based on curvelet transform detects the discontinuities across the cur...

In real time applications Image Compression plays a major role in storage memory and transmission bandwidth. As many compression methods are existing, selection of compression methods depends upon the quality in image reconstruction. Two popular compression methods are Wavelet and Ridgelet methods. Wavelet method has affected by the blocking artifacts and Ridgelet is designed to handle only lin...

Localization and detecting weak signal are the challenging tasks in radar systems. Radar performance can be enhanced by mounting the receiver output signal-to-noise ratio (SNR). In this paper, a novel approach based on Curvelet transform for detecting weak radar signal is proposed. We applied the curvelet transform and modulus maximum to detect the locations of laser radar echo signal. Localizi...

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...