Topic
Contourlet
About: Contourlet is a research topic. Over the lifetime, 3533 publications have been published within this topic receiving 38980 citations.
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Papers
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01 Jan 2011
12 citations
TL;DR: In this article, a depeckling method for SAR images based on stationary wavelet transform combining with directional filter banks is presented, which not only suppresses the speckle noise effectively, but also preserves as many target characteristics of original images as possible.
12 citations
12 Dec 2008
TL;DR: A new reduced- reference IQA metric to calculate the diversifications based on contourlet transform is proposed and results illustrate that even with low data rate, the presented metric has still good consistency with the subjective perception.
Abstract: In reduced-reference (RR) image quality assessment (IQA), the visual quality of distorted images is evaluated with only partial information extracted from original images. In this paper, by considering the information of textures and directions during image distortion, we propose a new reduced- reference IQA metric to calculate the diversifications based on contourlet transform Experimental results illustrate that even with low data rate, the presented metric has still good consistency with the subjective perception.
12 citations
12 Dec 2008
TL;DR: An adaptive threshold estimation method for image denoising based on nonsubsampled contourlet transform (NSCT) which can adapt different thresholds on different scales and different directions depend upon the subband size and number of decompositions.
Abstract: In this paper, we propose an adaptive threshold estimation method for image denoising based on nonsubsampled contourlet transform (NSCT). The NSCT is developed because of the lack of translation invariance of the contourlet transform. It is good at isolating the smoothness along the contours and can overcome the Gibbs-like phenomena around singularities. The proposed algorithm can adapt different thresholds on different scales and different directions depend upon the subband size and number of decompositions. After determining the thresholds, we adopt a new thresholding function which is continuous around the threshold and reduces the deviation between the coefficients and the original ones. The experiments show that the proposed approach can improve the SNR values, especially for the images that include mostly contours.
12 citations
TL;DR: The experimental results have shown that the fused images using the method proposed provided a better understanding of the reality, enhanced images’ clarity and eliminated factors which provided shelters for targets.
Abstract: In this paper the image fusion algorithm based on Contourlet transform and Pulse Coupled Neural Network PCNN was proposed to improve the performance of the image fusion in the detection accuracy of obstacles in forests. At the same time, the wavelet transform and the Principal Component Analysis PCA were simulated for comparison with the proposed algorithm. Then visible and infrared thermal images were collected in a forest. The experimental results have shown that the fused images using the method proposed provided a better understanding of the reality, enhanced images' clarity and eliminated factors which provided shelters for targets.
12 citations