A Fast Filtering Method for Polarimetric SAR Image

Abstract

The invention relates to a quick filtering processing method for a polarized SAR (synthetic aperture radar) image. The filtering processing speed for the polarized SAR image can be effectively improved, and cost is saved. The quick filtering processing method has the technical scheme that the quick filtering processing method comprises the following steps: 1) loading and expanding polarized SAR image data to make preparations for filtering; 2) calculating through the expanded polarized SAR image to obtain a total-power image; 3) on the basis of a search window[omega] in non-local means, calculating by an integral image to realize quick filtering processing; and 4) composing a pseudo-color image to a whole polarized covariance matrix C by a Pauli vector method, and outputting a filtering result. A traversal calculation range is greatly lowered, computation overheads are effectively reduced, and polarized SAR filtering processing speed is quickened. An applicable range of non-local means filtering processing is expanded, an integrogram is utilized, on one hand, calculation frequencies of similarity measurement are reduced, and on the other hand, rectangular window integral calculation frequencies are reduced. Speckle inhibition effect on the SAR image is better than that of the prior art.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a fast filtering processing method for polarimetric SAR images, which can be used for preprocessing of scene analysis and image understanding of polarimetric SAR images. Background technique [0002] Synthetic Aperture Radar (SAR) is a radar that uses the relative motion of the radar and the target to synthesize a smaller real antenna aperture into a larger equivalent antenna aperture by data processing, also known as synthetic aperture radar. SAR is not limited by weather, light and other conditions, and can observe the earth continuously and in real time. Polarization SAR provides richer target information for information acquisition and processing in remote sensing images, making it play an increasingly important role in the application of collecting physical and electromagnetic structure information of the ground surface or ground cover. Because polarimetric SAR is ...

AI Technical Summary

Problems solved by technology

However, an important problem of the non-local mean algorithm is the amount of calculation. In the NLM algorithm, the calculation of the similarity measure between pixels is the most time-consuming, because the similarity between any two image blocks must be calculated by calculating the corresponding pixel. The difference between them is then accumulated to obtain

It is conceivable that with the sliding of the filtering window, there are a large number of repeated operations in the similarity measurement operation between pixels, which makes it difficult for the existing non-local mean algorithm to be applied to engineering practice. The application area is small, the calculation rate is low, and the cost is high. This needs to provide a non-local mean filtering fast algorithm for polarimetric SAR, but there is no public report so far

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