We then show how to derive simple operations (image shift, rotation and stretch) directly in the curvelet domain. The basic transforms are needed for subsequent seismic migration. We demonstrate how to interpolate in the curvelet domain, using the Shannon interpolation formula. It appears that the interpolation scheme imposes some specific conditions on the shapes of the filters used for the cu...

The emergence of multimedia technology and the rapid growth in the number and type of multimedia assets controlled by several entities, yet because the increasing range of image and video documents showing on the Internet, have attracted vital analysis efforts in providing tools for effective retrieval and management of visual data. So the need for image retrieval system arose. Out of many exis...

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...

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...

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...

In this paper, a novel image denoising algorithm using M-band ridgelet transform is proposed for image denoising. The performance of the proposed method is tested on ultrasound images which are corrupted with Gaussian noise. The performance of the proposed method is compared with the existing ridgelet and curvelet transform in terms of peak-signal to noise ratio (PSNR) and mean square error (MS...

For image processing, it is very necessary that the selection of transform. In this paper, a comparative analysis of curve let transform with other transform for image processing .In this we proposed the applications of curve let transform in the field of image Compression ,phase recognition and feature extraction. For higher compression with quality reconstruction .The Wavelets gave a differen...