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Non-local mean speckle reduction algorithm based on L1/2 norm for high-resolution three-dimensional SAR images

A non-local mean and image technology, applied in the field of image processing, can solve the problems of non-sparseness, unsatisfactory effect of spot reduction in high-resolution three-point SAR images, etc., and achieve the effect of improving the effect of spot reduction

Inactive Publication Date: 2018-12-21
SHAANXI NORMAL UNIV
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Problems solved by technology

The speckle reduction effect of this method is not ideal for high-resolution triple SAR images, mainly because the non-local mean filter algorithm uses Gaussian weighted L 2 The norm is used as the similarity measure between image blocks, while the high-score three SAR images have obvious sparsity, L 2 Norm does not have good sparsity

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  • Non-local mean speckle reduction algorithm based on L1/2 norm for high-resolution three-dimensional SAR images
  • Non-local mean speckle reduction algorithm based on L1/2 norm for high-resolution three-dimensional SAR images
  • Non-local mean speckle reduction algorithm based on L1/2 norm for high-resolution three-dimensional SAR images

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Embodiment Construction

[0035] In order to further illustrate the technical means and effects taken by the present invention to achieve the predetermined purpose, the specific implementation, structural features and effects of the present invention will be described in detail below in conjunction with the accompanying drawings and examples.

[0036] It is known that the high-resolution triple SAR image v={v(x)|x∈I}, where I represents the entire image space, and the non-local mean filter algorithm performs speckle reduction on the image according to the self-similarity of the image. By selecting an image block with a fixed size, and then selecting an image block with greater similarity to this image block in the entire image, and then assigning corresponding weights according to the similarity to perform filtering. Based on L 1 / 2 The non-local mean filtering algorithm of norm is:

[0037]

[0038] Among them, NL[v](i) is the speckle reduction result, i, j are arbitrary pixel points, and w(i, j) i...

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Abstract

The invention relates to a non-local mean speckle reduction algorithm of a high-score three SAR image based on L1 / 2 norm, in particular comprising the following steps: step one, inputting a known high-score three SAR image; step two, inputting the known high-score three SAR image; step three, inputting the known high-score three SAR image. The invention designs a speckle reduction algorithm according to the characteristic that the high-score three SAR images have good sparsity, and adopts the L1 / 2 norm with better sparsity to replace the L2 norm as the standard of similarity measurement to improve the non-local average filtering algorithm, thereby improving the image speckle reduction effect.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a 1 / 2 Norm's high-scoring three-point non-local mean speckle reduction algorithm for SAR images. Background technique [0002] The Gaofen-3 satellite is not restricted by weather conditions such as cloud and rain, and can monitor and monitor global ocean and land resources around the clock. Serving the ocean, disaster reduction, water conservancy, meteorology and many other fields, it provides important technical support for marine surveillance and monitoring, maintenance of marine rights and interests, and emergency disaster prevention and mitigation. GF-3 satellite is my country's first C-band multi-polarization synthetic aperture radar satellite with a resolution of 1m, with 12 imaging modes. However, due to the coherent imaging method, the high-resolution three-dimensional SAR image will also produce bright and dark spots, which seriously affect the interpretation ...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/20024G06T2207/10044G06T5/70
Inventor 孙增国师蕊宋云静闫晓鹏
Owner SHAANXI NORMAL UNIV