Image noise suppression method for laser active imaging

Abstract

The invention relates to an image noise suppression method for laser active imaging, and belongs to an image noise suppression method. Structural elements of different scales are used to carry out morphological opening-closing operation and morphological closing-opening operation on an image formed by laser active imaging, and the results of multi-scale morphological filtering are fused according to the homogeneity of the local areas of the image. Multi-scale morphological image de-noising refers to weighted averaging of the morphological filtering results of the structural elements of all scales. Based on a morphological filtering method, a hardware logic structure is easy to implement. The image edge can be processed in real time and maintained properly. By using structural elements of multiple scales in morphological filtering and de-noising and taking the homogeneity of the local areas of the image as the basis for the fusion of results of image filtering by structural elements of different scales, a better laser image de-noising effect can be obtained. The method can be applied to laser active imaging systems, synthetic aperture radars, infrared medical imaging and other image de-noising occasions with speckle noise.

Description

technical field [0001] The invention relates to an image noise suppression method, in particular to a laser image denoising method for fusing multi-scale morphological filtering results by utilizing the homogeneity of image regions. Background technique [0002] In recent years, laser active imaging technology has developed rapidly, because this technology can provide more stable and clear target images, and can provide richer information for accurately describing the target geometry, so in radar reconnaissance, target detection and tracking, precision guidance, etc. It has broad application prospects in the military field. However, the target image under laser irradiation will be modulated by laser speckle, and the existence of speckle noise will seriously degrade the image quality, which will inevitably affect the recognition and tracking accuracy of the target, so the research is applicable to the speckle noise in laser image Noise suppression methods have important prac...

AI Technical Summary

Problems solved by technology

Classic algorithms include Lee, Kuan, SBF, and wavelet filtering, etc. While these methods suppress speckle noise, a lot of edge detail information is also lost

Non-local mean filtering (NLM) can make full use of the information contained in the entire image, effectively suppress the noise and preserve the texture structure of the image, but its execution computational complexity is large, and the algorithm runs slowly

[0004] Morphology-based filtering methods are easy to implement in hardware logic structures, and have the advantages of real-time processing and better preservation of image edges. However, when traditional morphological filtering algorithms are used for laser image denoising, their noise compression ability is poor, so if If the traditional morphological filtering algorithm can be improved, the speckle noise suppression ability in the laser image can be improved under the premise of maintaining the edge of the image

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