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SAR image despeckling method based on SVD dictionary and linear minimum mean square error estimation

A minimum mean square error, image technology, applied in the field of image processing, can solve problems such as Gibbs phenomenon

Inactive Publication Date: 2014-06-04
XIDIAN UNIV
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Problems solved by technology

However, the transform domain despeckling algorithm is still essentially a filter based on a fixed window, and Gibbs phenomenon will occur in areas such as edges and lines of the image.

Method used

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  • SAR image despeckling method based on SVD dictionary and linear minimum mean square error estimation
  • SAR image despeckling method based on SVD dictionary and linear minimum mean square error estimation
  • SAR image despeckling method based on SVD dictionary and linear minimum mean square error estimation

Examples

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Embodiment 1

[0060] This example refers to figure 1 , a SAR image speckle removal method based on SVD dictionary and linear minimum mean square error estimation, specifically includes the following steps:

[0061] 1) Perform Lee filtering with a window size of 3×3 on the input image v to obtain the preprocessed image v 0 ;

[0062] 2) Sampling an image block every 5 pixels in the image as the center block, and calculating each center block according to the distance formula

[0063] The distance between the heart block and all image blocks in its search neighborhood:

[0064] d ( v ( x i ) , v ( x j ) ) = Σ m = 1 M ...

Embodiment 2

[0089] The images used in this embodiment are shown in Fig. 2(a), Fig. 2(b), Fig. 2(c), and Fig. 2(d).

[0090] In this embodiment, various filtering methods are realized by programming in matlab language.

[0091] There are two experimental groups in this embodiment. In the first group of experiments, first add multiplicative speckle noise with view numbers L=1, 2, 4, and 16 to the natural image, and then use Frost, SA-WBMMAE, MAP -S, PPB, SAR-BM3D method and the method of embodiment 1 of the present invention despeckle them, calculate the PSNR of despeckling result; , using the PPB, SAR-BM3D method and the method of Example 1 of the present invention to remove speckle on them, and compare the visual effect of the speckle-removed image.

[0092] For the first set of experiments, the PSNR of the images obtained by the above various denoising methods are calculated, as shown in Table 1. The denoising results of the PPB method, the SAR-BM3D method and the method of the present...

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Abstract

The invention relates to an SAR image despeckling method based on an SVD dictionary and linear minimum mean square error estimation. The method includes the following steps that firstly, the distance between each image block in an input SAR image and all image blocks within a search region is worked out according to a distance formula; secondly, a similar set is built according to the minimum distance principle; thirdly, the similar set is subjected to SVD to acquire the SVD dictionary and is projected to the SVD dictionary to acquire a transformation coefficient; fourthly, the transformation coefficient is subjected to contraction according to the linear minimum mean square error principle; fifthly, the processed transformation coefficient is subjected to inverse transformation to acquire a denoised similar set, and denoised images are reconstructed through the similar set; sixthly, the processes are iterated to acquire final denoised results. By means of the method, the problem of the contradiction between detail keeping and the smoothness degree in prior SAR image despeckling results is effectively solved, speckle noise is better smoothed, and feature information of the SAR image is kept at the same time.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a SAR image speckle removal method based on SVD dictionary and linear minimum mean square error estimation. Background technique [0002] The image formed by Synthetic Aperture Radar (SAR) has the characteristics of all-weather, all-time, high resolution and strong penetrating ability, and is widely used in target recognition, transformation detection and water surface surveillance. Speckle noise is a major feature of the SAR imaging system, which originates from the random scattering of ground objects in the basic resolution unit, and appears as signal-related small spots on the image, which not only reduces the image quality of the image, but also seriously affects the automatic segmentation of the image. Classification, target detection, and other quantitative thematic information extraction, therefore, need to suppress and remove speckle noise. The goal ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 钟桦焦李成武忠王爽侯彪马晶晶马文萍
Owner XIDIAN UNIV
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