Weak and small infrared target strengthening method based on image geometric separation

Abstract

The invention relates to a weak and small infrared target strengthening method based on image geometric separation. Firstly, according to the distribution characteristics of weak and small targets and background clutters in an infrared image, a spectrogram wavelet transform dictionary and a non-subsampled shearlet transform dictionary are adopted for carrying out sparse representation on the weak and small targets and the background clutter constituents in the image respectively; then, the two unrelated sparse dictionaries are introduced to a image geometric separation framework, total variation penalty factors are utilized for obtaining more background clutter constituent information so that images can be separated more effectively, and therefore the purpose of strengthening weak and small target signals is achieved. The method has the better effects of strengthening the weak and small targets and suppressing the background clutters; compared with classical filtering methods such as the maximum mean method, the morphological filtering method and the two-dimensional minimum mean square error method, background suppression factors are improved, and false alarms caused by strong edges are well reduced.

Description

technical field [0001] The invention belongs to the field of infrared image processing, in particular to a method for enhancing weak and small infrared targets in a complex background. Background technique [0002] In the field of infrared technology application, weak and small target detection is a very critical technology in infrared tracking and identification systems, infrared early warning systems and precision guidance systems. Due to the complexity and harshness of the infrared imaging environment and the limitations of the hardware conditions of the detector, the contrast and signal-to-noise ratio of the obtained infrared image are very low. In addition, when the target is relatively far away from the infrared detection system, the imaging area of ​​the target on the detector is small. Basically point-like, so the target is easily overwhelmed by the strongly undulating background clutter. [0003] At present, in view of the technical problem of infrared weak and sma...

AI Technical Summary

Problems solved by technology

In this method, the threshold function is used to distinguish the same sparse dictionary in the selection of two sub-dictionaries representing the target and background components, so the correlation between the two is very large. A single background environment (such as deep space) with complex edges and texture details, these factors lead to poor adaptability of the method to complex background environments, and limited ability to detect faint targets

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