A special member of the emerging family of multiscale geometric transforms is the curvelet transform which was developed in the last few years in an attempt to overcome inherent limitations of traditional multistage representations such as wavelets. Mathematical is a set and lattice theoretic methodology for image analysis, which aims at quantitatively describing the geometrical structure of im...

Throughout the world the common cause of death in humans is lung cancer. It is necessary to detect cancer as early as possible to increase the survival rate. Lung cancer in CT scan images can be classified easily and efficiently using digital image processing techniques. Curvelet transform can extract the features of lung cancer CT scan images proficiently. All extracted feature by curvelet tra...

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...

In this paper, we propose a distance measure to evaluate visual similarity between two images. The algorithm searches for adaptive curvelet parameters that better represent a reference image. Next, the distance between the reference image and other images is computed as a weighted sum of distances between histograms of adaptive curvelet coefficients. The algorithm is tested on a data set of exe...

Image fusion is the process of integration of two or more source images into a single fused image. The resultant fused image is used to retain the important features of the source images. Color image fusion is the process of integrating one or more color images to enhance clarity of the image. The application of color image fusion simplifies object identification and helps in better cognition. ...

It is widely believed that to efficiently represent an otherwise smooth object with discontinuities along edges, one must use an adaptive representation that in some sense ‘tracks’ the shape of the discontinuity set. This folk-belief — some would say folk-theorem — is incorrect. At the very least, the possible quantitative advantage of such adaptation is vastly smaller than commonly believed. W...

Counting people and estimating their densities over a certain area is a fundamental task for many artificial intelligence systems. In this study, sub-difference images of curvelet transform are postulated as an efficient source for effective crowd estimation features. The new algorithm is described in detail in the form of a case study conducted at the Holy Haram in Madinah. The application of ...

Malayalam, the official language of Kerala, a southern state of India has been accorded the honour of language of eminence. Hence the researches in recognition and related works in Malayalam language is gaining more prominence in the current scenario. This paper proposes the use of Curvelet transform and neural network for the recognition of handwritten Malayalam character. Curvelet transform i...

Compressive Sensing Deconvolution (CS-Deconvolution) is a new challenge problem encountered in a wide variety of image processing fields. Since CS is more efficient for sparse signals, in our scheme, the input image is firstly sparse represented by curvelet frame system; then the curvelet coefficients are encoded by a structurally random matrix based CS sampling technique. In order to improve t...

This paper presents a novel approach for enhancing palmprint image. Enhancement is a preprocessing step used to modify the contrast of the image and remove the noise. Traditional Histogram equalization techniques improve the contrast of the image but introduce spurious noise. Palmprint consists of fine features. In order to extract fine features from the palmprint image, enhancement has to be d...