Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Marko...

This paper proposes a new method of medical image denoising based on a new nonlinear thresholding function in Nonsubsampled Contourlet Transform (NSCT) domain. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image ...

Advance medical imaging requires storage of large quantities of digitized clinical data. Due to the bandwidth and storage limitations, medical images must be compressed before transmission and storage. Diagnosis is effective only when compression techniques preserve all the relevant and important image information needed. There are basically two types of image compression: lossless and lossy. L...

Considering of the human visual system and the characteristics of remote sensing images, a novel image fusion strategy is presented for panchromatic high resolution image and multispectral image in nonsubsampled contourlet (NSCT) domain. The NSCT can give the asymptotic optimal representation of the edges and contours in image by virtue of the characteristics of good multiresolution, shift-inva...

The dyadic wavelet has good multi-scale edge detection and sub-band correlation features. Contourlet transformation has multi-directional characteristics. So a new dyadic nonsampling contourlet transformation is constructed. Firstly, multi-scale decomposition is performed on source images using dyadic contourlet transform to get high-frequency and low-frequency images. And then, according to th...

Combined with image processes under microbeam analysis,and based on analyzing the feature of electron probe deeply,the paper presents an optimized method based on Contourlet-lifting wavelet transform and regional variance.firstly,to get the fused image before Contourlet fusion based on regional variance,and then the processing image and the target image will be fused under lifting wavelet trans...

Aiming at the problem that how to improve the accuracy of image registration, this paper presents an approach for image registration based on mutual information and non-subsampled contourlet transform. First of all, the reference image and the floating image are decomposed with nonsubsampled contourlet transform. Secondly, register approximate component of the floating image from the highest le...

Palmprint recognition is an accepted and widely used biometric. Richness of feature and the less cost involved in acquisition make it more reliable and user friendly. The region of interest is extracted from the palmprint image as a preprocessing step. Contourlet transform, a pyramidal directional filter bank is then applied to capture both local and global details of the palmprint. The large n...

In this paper, a new multi-resolution tool, namely contourlet transform, is used to extract features for face recognition, which efficiently exploits the local spatial variations in a face image. Multi-resolution ideas, notably the wavelet transform, have been profusely employed for addressing the problem of face recognition. However, theoretical studies indicate that digital contourlet transfo...

In this paper, a new bivariate shrinkage denoising method is proposed to model statistics of shearlet coefficients of images. Using Bayesian estimation theory we derive from this model a simple non-linear shrinkage function for shearlet denoising, which generalizes the soft threshold approach. Experimental results show that the proposed method can remove Gaussian white noise while effectively p...