A novel method of Synthetic Aperture Radar (SAR) image despeckling using the contourlet transform representation is presented. Justification for the use of the contourlet signal representation, originally developed for natural images, is given. Methods of evaluating the despeckling performance of various algorithms are provided. Finally, a comparison of performance of multilook processing, wave...

We describe a method for removing acoustic-optical image noise, based on a statistical model of the decomposed contourlet coefficients. This method proposes an alpha-stable multivariate shrinkage (MS) probability density function to model neighborhood contourlet coefficients. Then, according to the proposed PDF model, we design a maximum a posteriori (MAP) estimator, which relies on a Bayesian ...

This paper proposes a novel progressive image compression algorithm using the nonlinear contourlet transform. Contourlets are effective in capturing directional information in images using a flexible set of basis functions that are elongated and directional. Since the contourlet transform is redundant, a wavelet based contourlet transform has been applied on the image. The wavelet based contour...

The contourlet transform can deal effectively with images which have directional information such as contour and texture. In contrast to wavelets for which there exists many good filters, the contourlet filter design for image processing applications is still an ongoing work. Therefore, this paper presents an approach for designing the contourlet filter based on the Chebyshev best uniform appro...

In this paper, a watermarking algorithm that uses the wavelet transform with Multiple Description Coding (MDC) and Quantization Index Modulation (QIM) concepts is introduced. Also, the paper investigates the role of Contourlet Transform (CT) versus Wavelet Transform (WT) in providing robust image watermarking. Two measures are utilized in the comparison between the waveletbased and the contourl...

Image noise always affects the clarity of the image and leads to blurring. However, the traditional de-noising methods cannot effectively remove the image noise especially the noise in regions contains rich detail information. In order to eliminate the noise, preserve better detail information of the images and enhance the de-noising effect of Contourlet wavelet transformation for images and cu...

Since interference noise and limited imaging algorithm etc caused low-quality images, continuous contour information on targets was difficult to extract, and ISAR imaging on aerial targets wasn’t ideal. On this basis, a new method of image processing is proposed to achieve clearer continuous contour features on targets. The method combines denoising technique based on Contourlet transform with ...

In this paper, we introduce a SAR images target recognition approach based on the contourlet transform and support vector machine (SVM), which takes technological advantages of both SVM and the contourlet transform for feature extraction.

The contourlet transform is a new directional transform, which is capable of capturing contours and fine details in images. We recently introduced the wavelet-based contourlet transform (WBCT) that is a non-redundant version of the contourlet transform, and appropriately used this transform for image coding. In this paper, we introduce the concept of wavelet-based contourlet packets (WBCP), whi...

In all methods of image denoising there is a problem always exists that is how to distinguish noise and edge. Now wavelet and contourlet are main tools in image denoising, but threshold is the key in wavelet and contourlet denoising. In order to distinguish noise and edge well, most methods in wavelet denoising are about the improvement of threshold. Aiming to resolve this problem, a new method...