Spatial images are inevitably mixed with different levels of noise and distortion. The contourlet transform can provide multidimensional sparse representations of images in a discrete domain. Because of its filter structure, the contourlet transform is not translation-invariant. In this paper, we use a nonsubsampled pyramid structure and a nonsubsampled directional filter to achieve multidimens...

The image retrieval problem has recently become more important and necessary because of the rapid growth of multimedia databases and digital libraries. Different search engines use different features to retrieve images from the database. In this paper, the Contourlet Transform is developed to retrieve similar images from the image database. By combining the Laplacian pyramid and the Directional...

The aim of this paper is improving the iris segmentation with the Contourlet transform. At first iris segmentation performed by canny edge detector and Hough Transform. By this approach some images don’t segmented properly, so we want to find a way to correct the image segmentation failures. Before applying edge detector, Contourlet transform applied for image denoising. By this approach, %100 ...

The key to medical image denoising technique is to remove the noise while preserving important features. Non-local mean filtering and bilateral filtering are commonly used procedures for medical image denoising. In this paper analysis and comparison of spatial as well as frequency domain methods including bilateral filtering , non-local mean filtering, wavelet thresholding, contourlet threshold...

Contourlet is a new image representation method, which can efficiently represent contours and textures in images. In this paper, we analyze the distribution of significant contourlet coefficients in different subbands and propose a contourlet image coding algorithm by constructing a virtual low frequency subband and adjusting coding method of SPIHT (Set Partitioning in Hierarchical Trees) algor...

This paper presents a parallel implementation of color image segmentation algorithm using multiresolution technique. The idea is to achieve the complete and significant objects in the image using contourlet transform based image segmentation and to explore current multi-core architectures present in commercial processors in order to speed up the segmentation process for large size images. The a...

The authors propose a new hybrid watermarking scheme for copyright protection of color images using contourlet transform and singular value decomposition. The host color image and color watermark images are decomposed into directional sub-bands using contourlet transform and then applied Singular value decomposition to mid frequency sub-band

We propose a new method for image de-noising based on the contourlet transform, which has been recently introduced. Image de-noising by means of the contourlet transform introduces many visual artifacts due to the Gibbs-like phenomena. Due to the lack of translation invariance of the contourlet transform, we employ a cycle-spinning-based technique to develop translation invariant contourlet de-...

To suppress the Pseudo-Gibbs phenomena caused by the Contourlet, the Nonsubsampled Pyramids Filter Banks and the Nonsubsampled Directional Filter Banks are combined to construct the nonsubsampled Contourlet transform (NSCT). Hence, The NSCT not only possess the main features of multi-scale, multi-directional and timefrequency localization, but also offer the property of the shift-invariant whic...

This paper presents a novel non-blind watermarking algorithm using contourlet transform. The contourlet transform is preferred for watermarking because of its ability to capture the directional edges and contours superior to other transforms such as cosine transform, wavelet transform, etc. Watermark is encrypted and embedded into high frequency directional subband, which is obtained by perform...