Aim. This paper describes the digital implementation of a mathematical transform namely 2D Fast Discrete Curvelet Transform (FDCT) via UnequiSpaced Fast Fourier Transform (USFFT) in combination with the novel segmentation method for effective detection of breast cancer. Methods. USFFT performs exact reconstructions with high image clarity. Radon, ridgelet and Cartesian filters are included in t...

In this paper, we propose a novel image denoising method by incorporating the dual-tree complex wavelets into the ordinary ridgelet transform. The approximate shift invariant property of the dual-tree complex wavelet and the high directional sensitivity of the ridgelet transform make the new method a very good choice for image denoising. We apply the digital complex ridgelet transform to denois...

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 ...

Image denoising is basic work for image processing, analysis and computer vision. This Work proposes a Curvelet Transformation based image denoising, which is combined with the low pass filtering and thresholding methods in the transform domain. Through simulations with images contaminated by white Gaussian noise, this scheme exhibits better performance in both PSNR (Peak Signal-to-Noise Ratio)...

Aim. This paper describes the digital implementation of a mathematical transform namely 2D Fast Discrete Curvelet Transform (FDCT) via UnequiSpaced Fast Fourier Transform (USFFT) in combination with the novel segmentation method for effective detection of breast cancer. Methods. USFFT performs exact reconstructions with high image clarity. Radon, ridgelet and Cartesian filters are included in t...

Seismic data recovery from data with missing traces on otherwise regular acquisition grids forms a crucial step in the seismic processing flow. For instance, unsuccessful recovery leads to imaging artifacts and to erroneous predictions for the multiples, adversely affecting the performance of multiple elimination. A non-parametric transform-based recovery method is presented that exploits the c...

We propose in this paper a new deconvolution approach, which uses both the wavelet transform and the curvelet transform in order to bene2t from the advantages of each. We illustrate the results with simulations. ? 2003 Elsevier B.V. All rights reserved.

The prevalent cause of death in human being is brain tumor. A brain tumor is a mass or growth of anomalous cells in brain. The detection of brain tumor is difficult task. Image processing provides relevant techniques for efficient detection. In the proposed technique, first the features of MRI (Magnetic Resonance Imaging) images are extracted with curvelet transform, and then these features are...