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
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
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...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


