A new image denoising method based on curvelet transform is proposed. The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. Here, we pursue "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. Deno...

In this paper, we propose a new no-reference VQA metric, called Video Hybrid No-reference (VHNR) method. It is based on natural video statistics built from the coefficients of 3D curvelet and cosine transforms. VHNR can blindly predict the quality of noisy, blurry, or MPEG2 compressed videos and requires no original reference video. The 3D curvelet transform is known to be sensitive to surface ...

The uniform discrete curvelet transform (UDCT) is a novel tool for multiscale representations with several desirable properties compared to previous representation methods. A novel algorithm based on UDCT is proposed for the fusion of multi‐source images. A novel fusion rule for different subband coefficients obtained by UDCT decomposition is discussed in detail. Low‐pass ...

In this article a new method is introduced for distinguishing roots and background based on their digital curvelet transform in minirhizotron images. In the proposed method, the nonlinear mapping is applied on sub-band curvelet components followed by boundary detection using energy optimization concept. The curvelet transform has the excellent capability in detecting roots with different orient...

In this paper, an automatic support system for brain tumor stage classification using learning machine and for detecting brain tumor during early stages using fuzzy clustering methods is proposed. The fuzzy clustering method is a segmentation technique presented to segment the Magnetic Resonance images for detecting the Brain Tumor during early stages and for examining anatomical structures. Fa...

We describe approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform and the curvelet transform. Our implementations offer exact reconstruction, stability against perturbations, ease of implementation, and low computational complexity. A central tool is Fourier-domain computation of an approximate digital Radon transform. We introduce a very simple ...

This paper proposes a new method for face recognition based on a multiresolution analysis tool called Digital Curvelet Transform. Multiresolution ideas notably the wavelet transform have been profusely employed for addressing the problem of face recognition. However, theoretical studies indicate, digital curvelet transform to be an even better method than wavelets. In this paper, the feature ex...

We revisit Smith’s frame of curvelets and discretize it making use of the USFFT as developed by Dutt and Roklin, and Beylkin. In the discretization, we directly approximate the underlying dyadic parabolic decomposition, its (rotational) symmetry, and approximate all the necessary decay estimates in phase space with arbitrary accuracy. Numerically, our transform is unitary. Moreover, if we apply...

A fast discrete curvelet transform based focus-stacking algorithm for extending the depth of focus of a transmission x-ray microscope (TXM) is presented. By analyzing an image stack of a sample taken in a Z-scan, a fully in-focus image can be generated by the proposed scheme. With the extended depth of focus, it is possible to obtain 3D structural information over a large volume at nanometer re...