Parallel real-time SAR image spot and noise reducing method based on multiple DSPs

Abstract

The invention discloses a parallel real-time SAR image spot and noise reducing method based on multiple DSPs. The parallel real-time SAR image spot and noise reducing method based on the multiple DSPs mainly solves the problems that large-scale SAR image spot reducing operation is large in time complexity and low in processing speed. The parallel real-time SAR image spot and noise reducing method based on the multiple DSPs comprises the implementation steps that (1) a main processor and an auxiliary processor are initialized; (2) an upper computer divides a large-scale SAR image into a plurality of sub-images and transmits the sub-images to the main processor and the auxiliary processor; (3) the main processor and the auxiliary processor carry out boundary extension and floating-point type transformation, then calculate the expectation filter weight of a central image block and the expectation filter weights of neighborhood image blocks and obtain an estimation result of the central image block according to the weight; (4) aggregation, boundary clipping and integer transformation are carried out on the estimation result in sequence, and sub-image spot reduction results are obtained; (5) all the sub-image spot reduction results are transmitted back to the upper computer and spliced, and thus a spot reduction result image of the original large-scale SAR image is obtained. The parallel real-time SAR image spot and noise reducing method based on the multiple DSPs greatly improves spot reduction speed, can meet the real-time performance requirement of image spot reduction, and can be used for large-scale SAR image fast spot reduction processing and SAR image target recognition.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a method for real-time speckle reduction and denoising of synthetic aperture radar SAR images based on an embedded digital signal processor DSP, which can be applied to target recognition of SAR images in embedded systems. Background technique [0002] Synthetic Aperture Radar (SAR) image is a kind of high-resolution radar image, which is widely used in many fields such as military, agriculture, forestry, and geology. However, due to the defects of its own coherent imaging system, speckle noise is always inevitable in SAR images. The existence of coherent speckle noise will weaken the characteristics of the target, and may submerge the real target in severe cases, and seriously interfere with the subsequent understanding and interpretation of SAR images. Therefore, speckle reduction and denoising are the most basic and important image processing methods in SAR imag...

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Problems solved by technology

However, the disadvantage of this method is that weak target points are not ideally maintained, and the algorithm is complex and time-complex, which cannot meet the real-time requirements of large-scale SAR images, and it is difficult to implement on the embedded digital signal processor DSP.

[0005] In 2012, Xidian University proposed "SAR image denoising method based on GPU programming" in its patent application with application number: 201210414683.6 and publication number: CN102903087A. Although this method improves the PPB denoising method for large-scale SAR images The speed can be used to quickly denoise large-scale SAR images, but there are still shortcomings that this method needs to run on high-performance computing servers or even clusters, which requires high investment costs, high power consumption, and large volume, which is inconvenient to machine. onboard or onboard applications

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