A contourlet domain sparse component analysis for blind image separation is proposed. An estimation algorithm for separation matrix is given based on the sparse description of the contourlet transform. The proposed algorithm is used to separate the mixed images. Simulation results show that the proposed approach is able to yield better separation performance for convergence speed, and the order...

In this paper, a novel algorithm for face recognition with one sample per person is proposed. The proposed algorithm is based on contourlet. Multiple training images for each class are constructed through the decomposition and reconstruction of original training images by contourlet. Thus neighborhood discriminant nearest feature line analysis can be performed on the new database. The experimen...

Palmprint recognition is gaining grounds as a biometric system for forensic and commercial applications. Palmprint recognition addressed the recognition issue using low and high resolution images. This paper uses PolyU hyperspectral palmprint database, and applies back-propagation neural network for recognition, linear discriminate analysis for dimensionality reduction, and 2D discrete wavelet,...

In the contourlet transform (CT), the Laplacian pyramid (LP) decomposes an image into a low-frequency (LF) subband and a high-frequency (HF) subband. The LF subband is created by filtering the original image with 2-D low-pass filter. However, the HF subband is created by subtracting the synthesized LF subband from the original image but not by 2-D high-pass filtering the original image. In this...

The aim of this study is to propose a suitable and reliable system for better diagnosis and treatment of carotid diseases. In this study, Computer Aided Diagnosis (CAD) system has been proposed for classifying carotid artery plaques using Contourlet features. Carotid images have been acquired for 124 subjects with symptoms (Amaurosis Fugax, Stroke or Transient Ischemic Attack) and 133 subjects ...

-The proposed method presents a new classification approach to microcalcification detection in mammograms using morphology, Contourlet Transform and Artificial Neural Network. Early detection of breast cancer is possible by enhancing microcalcification features obtained using morphology and singularities of Contourlet Transform. The significant edge information indicating the relevant features ...

Facial expression is one of the most significant ways to express the intention, emotion and other nonverbal messages of human beings. A computerized human emotion recognition system based on Contourlet transformation is proposed. In order to analyze the presented study, seven kind of human emotions such as anger, fear, happiness, surprise, sadness, disgust and neutral of facial images are taken...

This paper constructs a dyadic non-subsampled Contourlet transform for denoising on the image. The transformation has more directional subband, using the non-subsampled filter group for decompositing of direction, so it has the translation invariance, eliminated image distortion from Contourlet transform’s lack of translation invariance. Non-subsampled filter reduces noise interference and data...

In this study, new method for enhancing color image based on contourlet transform and human visual system proposes. The color image is converted to HSV (Hue , Saturation, Value) values. The V, which represents the luminance value of color image, decomposed to its coefficients by nonsubsampling contourlet transform, then applying grey-level contrast enhancement technique on some of the coefficie...

Calcification detection in mammogram is important in breast cancer diagnosis. A super-resolution reconstruction method is proposed to reconstruct mammogram image from one single low resolution mammogram based on the compressed sensing by the contourlet transform. The initial estimation of the super-resolution mammogram is obtained by the interpolation method of the low resolution mammogram reco...