Image Fusion is a combination of two or more different images. It extracts the information from multiple source images. Wavelet based image fusion is suitable for representing the point singularities in one dimensions, but it fails to represent the edges across the curves in two dimensions. In this method, pixel level fusion based on curvelet transform detects the discontinuities across the cur...

Localization and detecting weak signal are the challenging tasks in radar systems. Radar performance can be enhanced by mounting the receiver output signal-to-noise ratio (SNR). In this paper, a novel approach based on Curvelet transform for detecting weak radar signal is proposed. We applied the curvelet transform and modulus maximum to detect the locations of laser radar echo signal. Localizi...

We present in this paper new multiscale transforms on the sphere, namely the isotropic undecimated wavelet transform, the pyramidal wavelet transform, the ridgelet transform and the curvelet transform. All of these transforms can be inverted i.e. we can exactly reconstruct the original data from its coefficients in either representation. Several applications are described. We show how these tra...

When an image is captured by CCD device, only the objects at focus plane would appear sharp. A practicable way to get an image with all objects in focus is to fuse images acquired with different focus levels of the scene. In this paper, we propose a multifocus image fusion algorithm based on combination of wavelet and curvelet transform. Although the fused results obtained by wavelet or curvele...

We develop a unifying perspective on several decompositions exhibiting directional parabolic scaling. In each decomposition, the individual atoms are highly anisotropic at fine scales, with effective support obeying the parabolic scaling principle length ≈ width. Our comparisons allow to extend Theorems known for one decomposition to others. We start from a Continuous Curvelet Transform f → Γf ...

This paper presents feature level fusion approach using multi resolution Curvelet transform for face and palm biometrics.In this paper feature extraction has been done by taking the curvelet transform of bit quantized images.The curvelet coefficient thus obtained acts as feature set for classification.The five sets of coefficients from five different versions of images are used to train five SV...

In this Letter, a new face recognition approach based on curvelets and local ternary patterns (LTP) is proposed. First, we observe that the curvelet transform is a new anisotropic multi-resolution transform and can efficiently represent edge discontinuities in face images, and that the LTP operator is one of the best texture descriptors in terms of characterizing face image details. This motiva...

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...