In this paper, a method aimed at optimizing contrast of mammographic features is presented. Contrast enhancement is accomplished by applying local range modification on curvelet coefficients. The standard deviation of coefficient values for each scale/angle pair (j,l) is calculated as an index to increase the gain of subband curvelet coefficients. The processed image is derived by reconstructio...

This paper presents a comparison of wavelet and curvelet for lung cancer in term of diagnostic accuracy when each one is applied separately to the cluster K-Nearest neighbor classifier. Lung cancer is among the diseases that lead to high mortality rate globally. The computer aided diagnoisis system that is shown in this paper consists of a preprocessing state, a feature extraction stage (wavele...

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...