We reconsider the continuous curvelet transform from a signal processing point of view. We show that the analyzing elements of the curvelet transform, the curvelets, can be understood as analytic signals in the sense of the partial Hilbert transform. We then generalize the usual curvelets by the monogenic curvelets, which are analytic signals in the sense of the Riesz transform. They yield a ne...

Curvelet transform is the new member of the evolving family of multiscale geometric transforms. It offers an effective solution to the problems associated with image denoising using wavelets. Finger prints possess the unique properties of distinctiveness and persistence. However, their image contrast is poor due to mixing of complex type of noise. In this paper an attempt has been made to prese...

A new method which is suitable for enhancing the color microscopic image quality based on HSV color space and curvelet transform is presented in this paper. The color microscopic image is firstly divided into hue, saturation and value components from RGB color space to HSV color space through the color space conversion. The value component is decomposed by the curvelet transform. A modulus squa...

Abstract Surface Related Multiple Elimination (SRME) usually suffers the issue of either over-attenuation that damages primaries or under-attenuation leaves strong residual multiples. This dilemma happens commonly when SRME is combined with least-squares subtraction. Here we introduce a more sophisticated subtraction approach facilitates better separation multiples from primaries. Curvelet-doma...

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Face Recognition using Wrapping Curvelet Transform (FRWCT). The Wrapping Curvelet Transform (WCT) is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT featu...

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...

This paper addresses the problem of Bangla basic character recognition. Multi-font Bangla character recognition has not been attempted previously. Twenty popular Bangla fonts have been used for the purpose of character recognition. A novel feature extraction scheme based on the digital curvelet transform is proposed. The curvelet transform, although heavily utilized in various areas of image pr...

Motion blur can significantly degrade the quality of an image. The images become blurred due to camera movements, object movements or displacements of pixels. Deblurring of an image is done by processing an image through curvelet transform and removal of noise by median filter. Experimental results show that proposed deblurring technique and accuracy measurement using peak signal to noise ratio...

For the ultrasound images accurate segmentation problem, this paper proposes a novel SVM semi-supervised segmentation method based on major features in curvelet domain. Firstly, ultrasound images were decomposed into different directions and frequencies in the curvelet domain, then the cauchy model was used to simulate curvelet coefficients distribution, thus the main distribution of the curvel...

The curvelet transform is a recently introduced non-adaptive multi-scale transform that have gained popularity in the image processing field. In this paper, we study the effect of customized tiling of frequency content in the curvelet transform. Specifically, we investigate the effect of the size of the coarsest level and its relationship to denoising performance. Based on the observed behavior...