Contourlet

About: Contourlet is a research topic. Over the lifetime, 3533 publications have been published within this topic receiving 38980 citations.

Comparative analysis of transform based image fusion techniques for medical applications

Abstract: Medical imaging is the process of creating images of the human body for the purpose of diagnosis and treatment. In medical imaging various modalities provide different features of body because they use different principles of imaging. Since no single image modality provides a complete information in all cases, fusion will be very useful. The objective of image fusion is to improve the image content, by combining information from multiple images. In this paper three transform based fusion rules, The Wavelet transform(WT), Contourlet transform(CT) and Nonsubsampled contourlet transform(NSCT) are compared. Experimental results show that the image fusion method based on NSCT performs better than the other two methods.

An M-channel directional filter bank compatible with the contourlet and shearlet frequency tiling

Abstract: In this work, we present new methods for creating M -channel directional “lters to construct multiresolutionand multidirectional orth ogonal/biorth ogonal transforms. A key feature of these methods is the ability to solvethe polynomial Bezout equation in higher dimensions by taking advantage of solutions that have been proposedfor solving a related equation known as the analytic Bezout equation . These new techniques are capable ofcreating directional “lters that yield spatial-frequency tilings equivalent to those of the contourlet and theshearlet transforms. Such directional “lter banks can create sparse representations for a large class of imagesand can be used for various restoration problems, compression schemes, and image enhancements.Keywords: directional “lter, wavelet, shearlet, multichannel deconvolution. 1. INTRODUCTION In recent years there has been consider able interest in obtaining directiona lly-oriented image decompositions.Many of these decompositions (e.g. curvelets

Research on millimeter-wave image denoising method based on contourlet and compressed sensing

Abstract: In this paper, we analyze the general properties of passive millimeter-wave (PMMW) imaging system, then the denoising principle of contourlet and compressed sensing is briefly described. With both denoising advantages of contourlet and compressed sensing, a PMMW image denoising algorithm is designed. And, in the process of compressed sensing denoising, a new type of observation matrix, which is called amplitude-matching variable density measurement matrix, is proposed utilizing the priority information of low-pass property of system. Experiments demonstrate that this improvement can eliminate the “scratches” parts which the contourlet denosing produces. PSNR of image is enhanced and subjective visual feeling of millimeter-wave image is obviously improved.

A New Contourlet Transform With Adaptive Directional Partitioning

Abstract: A new image sparse representation tool—adaptive contourlet transform (ACT) is introduced in this letter. Adaptive directional partitioning schemes in ACT can match the arbitrary orientation distribution of natural image, which brings sparser representation. The proposed ACT is based on pseudopolar Fourier transform that has similar geometrical structure to fan filter. This characteristic helps ACT out of the difficulty of designing traditional directional filter bank. Simulation results demonstrate that ACT can provide more efficient image sparse representation compared to contourlet transform.