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Synthetic Aperture Radar (SAR) images despeckling technique has been developed for many years. Most methods cannot strike a good balance between smoothing speckle noise and preserving structure. In order to both smoothing speckle and preserving structure, we proposed a despeckling method using singular value thresholding and iterative regularization which inspires from spatially adaptive iterative...
Synthetic Aperture Radar (SAR) systems have been widely used to estimate the various features on the ground. However, the images are often corrupted by noise that can impede further investigation of SAR images. Therefore, the extraction of features from SAR images with noisy backgrounds becomes a challenging issue in SAR image processing. The goal of this paper is to develop and implement a more robust...
In this paper, a new SAR image despeckling method based on the improved Directionlet domain Gaussian Mixture Model (GMM) is proposed. Firstly, the cartoon texture model is used to decompose the SAR image to a cartoon part and a texture part. Secondly, the cartoon part is kept unchanged, the coefficients of the texture part in the improved Directionlet domain are modeled by the Gaussian Mixture Model...
We propose a novel and efficient SAR image despeckling via Bayesian shrinkage based on nonsubsampled contourlet transform, which has been recently introduced. Despeckling by means of contourlet transform introduce many visual artifacts due to the Gibbs-like phenomena. Nonsubsampled contour let transform is a flexible multiscale, multidirection and shift-invariant image decomposition that can be efficiently...
As speckle noise suppression is important for Synthetic aperture radar (SAR) images processing, this paper presents an approach for SAR image despeckling based on nonsubsampled directionlets. Firstly, images are partitioned into subbands using nonsubsampled directionlets. Then, the coefficients of subbands are modeled with Gaussian scale mixtures (GSM). Besides, for reducing the speckle noise, coefficients...
The reduction of speckle in SAR image is necessary for processing of SAR image such as feature detection and extraction. In Contourlet transform, a drawback of Laplacian pyramid (LP) is implicit oversampling and non-orthogonal decomposition, Wavelet transform is a critically sampled scheme but it only generated three direction. Taking advantage of Wavelet and Contourlet, the proposed method is complemented...
In order to speed up the segmentation procedure and solve the problem of noise-sensibility in image segmentation, the paper suggests a fast SAR (Synthetic Aperture Radar image) image segmentation method, which integrates SWT (Stationary Wavelet Transform) and AFSA (Artificial Fish Swarm Algorithm). In the method, an original image is decomposed by multilevel SWT firstly. And then, approximation coefficients...
The SAR remote sensing images are interfered by noises during the detection and transmission, a method based on wavelet packet and level dependent adaptive threshold is proposed in this paper. By using this method, the SAR images can be decomposed in a more elaborate method compared to the traditional wavelet transform, and the noises in the SAR images are eliminated by the adaptive threshold method...
Although some of the traditional methods of image fusion such as wavelet transform fusion and Laplacian pyramid fusion have good effect on most visible images, it is not suitable for SAR image fusion. Because the speckle noise in SAR images is multiplicative and coherent. In this paper, we propose a method called local non-negative matrix factorization (LNMF) for SAR image fusion. LNMF uses multiplicative...
According to the different characteristics that signal and noise exhibit during the wavelet decomposition, a new denoising method based on the second wavelet packet decomposition is presented. In this paper, by using the best wavelet packet, the synthetic aperture radar (SAR) images are decomposed and the norm of each sub-band is calculated. Then signals and noise can be discriminated and the images...
We propose a novel and efficient SAR image despeckling via bivariate shrinkage based on contourlet transform, which has been recently introduced. Contourlet transform is a flexible multi-scale, multi-direction and multi-resolution image decomposition that can be efficiently implemented via transform. A bivariate shrinkage with local variance estimation is applied to the decomposed contourlet coefficients...
This paper presents a technique for speckle reduction in SAR images by using the interscale multiplication in Mallat wavelet transform (MWT) and stationary wavelet transform (SWT). The edge and non-edge regions can be detected from median of squared amplitude in each scale. Applying this technique, the large wavelet coefficients generated by edge region and the small wavelet coefficients or speckle...
The paper presents the wavelet shrinkage and the image compression for SAR images, based on discrete wavelet transform (DWT). It is very efficient to integrate these two procedures in a single process. First, a speckled SAR image is transformed by using multiple level wavelet decomposition. The variance of noise is estimated from wavelet coefficients to determine the threshold, which is used for soft...
A novel SAR image denoising scheme based on the quad-tree complex wavelet packets transform (QCWPT) was presented to achieve the tradeoff between details retainment and noise removal. A new threshold method was used in the proposed scheme, and the QCWPT detail coefficients were shrunk via calculating the locally adaptive shrinkage factors with reference to the QCWPT coefficients within the neighborhood...
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