Multi-view ISAR image fusion method

Abstract

The invention discloses a multi-view ISAR image fusion method, which mainly solves the problems of redundancy of feature points extracted by the prior art, complexity of processing and large operationamount. The scheme is as follows: a series of N ISAR images are segmented by superpixel simple linear iterative clustering to obtain superpixel coordinates X, Y and brightness information L; a brightness threshold is set, and the super pixel information whose L is larger than the threshold is retained; the first ISAR image is selected as the reference image, and the rigid transformation relationship between the nth ISAR image and the reference image is established by using the reserved parameters, and the transformation matrix Bn is obtained; a cost function Jn between the nth ISAR map and the reference map is set; the rigid transformation matrix Bn' which minimizes Jn is solved, and the inverse matrix An of Bn' is obtained; the n-th ISAR map is transformed into the reference map coordinate system according to the inverse matrix An, and all the transformed ISAR maps and the reference maps are superposed to obtain the fusion map. The feature points extracted by the invention are refined, and the operation amount is small, and can be used for three-dimensional image reconstruction, target recognition and attitude estimation.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image fusion method, which can be used for three-dimensional image reconstruction, target recognition and pose estimation. Background technique [0002] Digital image fusion is a basic problem in computer vision, and it is widely used in 3D image reconstruction, object recognition and pose estimation. Digital image registration is a preprocessing stage of digital image fusion. Digital image registration technology can match and superimpose different images of the same target acquired under different imaging angles to generate a new interpretation of the target. This interpretation is not available from the image information of a single capture. The research on digital image registration is of great significance and value to promote the development of multi-view image fusion technology. [0003] At present, ISAR image fusion methods for space targets main...

AI Technical Summary

Problems solved by technology

[0004] One is the RELAX algorithm, which can relax the system error and environmental additive noise distribution assumptions represented by the signal processing level, and extract the scattered points for feature point matching and fusion. The disadvantage of this method is that it requires the knowledge of the ISAR imaging signal processing level. The processing is complex and the amount of calculation is large;

[0005] The other is the scale-invariant feature transformation algorithm SIFT represented by the information processing level, extracting feature points for matching and fusion, but this method only needs to process the information level of the image and does not use the structural information of the image, resulting in The extracted feature points are redundant, and the algorithm has a large amount of calculation

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