Infrared dim small target detection method of constructing entropy contrast ratios by utilizing directional derivatives

Abstract

The invention relates to an infrared dim small target detection method of constructing entropy contrast ratios by utilizing directional derivatives. The method comprises the four main steps of: based on least square surface fitting, quickly solving first-order derivatives, which are in four directions respectively, of each pixel of an infrared image by using a facet model and convolution operations; redesigning, starting from a mathematical imaging model of a dim small target, information entropy calculation formulas at a central area in a small-range neighborhood based on directional derivative features combined with gray-scale distribution information; similarly redesigning information entropy calculation formulas for a surrounding area of the small-range neighborhood, utilizing a characteristic of strong contrasts between the center area of the dim small target and the surrounding area to construct the entropy contrast ratios, utilizing the measures to suppress backgrounds in derivative subgraphs of each direction, and enhancing the target; and fusing the entropy contrast ratios of the derivative subgraphs of each direction by means of multiplication, further suppressing the edge clutter backgrounds, and highlighting the dim small target. The method can be widely used in dim small target detection of infrared images, and has a broad market prospect and application value.

Description

(1) Technical field [0001] The invention relates to an infrared weak and small target detection method using directional derivatives to construct entropy contrast, belongs to the field of digital image processing, and mainly relates to facet models and weak and small target detection technologies. It has broad application prospects in various image-based application systems. (2) Background technology [0002] In the infrared-related early warning system, some suspicious targets such as ships, aircraft and missiles appear as bright areas on the infrared image due to their high temperature characteristics. Early detection of these suspicious objects can take countermeasures in advance to provide for subsequent strategic deployment, etc. Buy your precious time. However, when the imaging distance is long, these objects become some weak point targets in the image, and lose the features such as structure and texture that can be used. In addition, in contrast, the infrared backgro...

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Problems solved by technology

Based on some small target detection methods based on morphological processing, such as hit-to-miss transformation, top-hat transformation, etc. : 43(7): 1084-1090. (Bai X, Zhou F. Hit-or-miss transform based infrared dim small target enhancement[J]. Optics&Laser Technology, 2011, 43(7): 1084-1090.)) Utilization Hit-to-miss transformation is used to enhance weak targets and suppress complex backgrounds. Mathematical operations based on morphology are relatively simple and fast, but they are easily interfered by noise and edge clutter and cause excessive false alarms.

A detection method based on the human visual system (see literature: Han Jinhui et al., A small infrared target detection algorithm based on the human visual system, Institute of Electrical and Electronics Engineers Geology and Remote Sensing Letters, 2016, 13(3):452-456.( Han J, Ma Y, Huang J, et al.An infrared small target detecting algorithm based on human visual system[J].IEEE Geoscience and Remote Sensing Letters,2016,13(3):452-456.)) using DoG to enhance the target Suppress the background and increase the direction information to overcome the disadvantage of DoG being sensitive to edges, and reduce the false alarm in the detection results. However, because some background edges in the infrared scene are not only along a fixed direction, the edge suppression effect is limited.

Considering that the target may have varying shapes and sizes when constructing local contrast measures, some methods add multi-scale information (see literature: Wei Yantao et al., Infrared Small Target Detection Based on Multi-scale Block Contrast Measure, Pattern Recognition, 2016,58 :216-226.(Wei Y,You X,LiH.Multiscale patch-based contrast measure for small infrared target detection[J].Pattern Recognition,2016,58:216-226.)), results from multiple scales Select the appropriate one as the final result, but the local contrast method itself is sensitive to noise, and the simple maxima-minimum scale selection method cannot avoid the influence of noise, so there are still many clutter false alarms in the final result

Most algorithms are still unable to obtain satisfactory results in target detection under low signal-to-noise ratio and false alarm suppression under complex background

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