Small object detection method based on random sampling and sparse matrix restoration under infrared scene

Abstract

The invention provides a small object detection method based on random sampling and sparse matrix restoration in infrared scene. The method includes the following steps: conducting random sampling at the position of each pixel of a single frame infrared image, acquiring an infrared image having random characteristics; conducting patch transformation on the infrared image after random sampling, segmenting the infrared image after random sampling into a plurality of small images having no overlapped regions, and conducting 1 dimensional vectorization processing to obtain a 2 dimensional matrix after patch transformation; analyzing main components of the 2 dimensional matrix after patch transformation to obtain a sparse matrix and a low-rank matrix; conducting image restoration on the sparse matrix by applying patch inverse transformation, and separately obtaining a corresponding infrared small object image and an infrared image background; using the low-rank matrix to determine a segmentation threshold of the infrared small object detection, and conducting image segmentation on the infrared small object image based on the segmentation threshold to detect the infrared small object. According to the invention, the method is simple and requires short time to operate.

Description

technical field [0001] The invention belongs to the technical field of image detection and processing, and in particular relates to a small target detection method based on random sampling and sparse matrix restoration in an infrared scene. Background technique [0002] The small target detection technology in the infrared scene is mainly divided into two categories, one is to analyze the imaging characteristics of small infrared targets in a single frame image, and the other is to use a set of infrared image sequences, according to the movement of small infrared targets, Combined with the way of track correlation for analysis. At present, the detection technology of small targets in single-frame infrared images mainly focuses on the research on the imaging characteristics of the target, and marks the targets that meet the characteristics in the infrared image according to the imaging characteristics, and finally obtains the infrared target. There is less analysis of the lo...

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Problems solved by technology

There is less analysis of the low-rank characteristics combined with the infrared background, especially in the previous sparse matrix recovery method, the interception of small images requires overlapping areas to ensure strong correlation in the algorithm, but it will increase during the target detection process The amount of calculation of the algorithm, and the influence of noise interference cannot be well overcome in the detection, the work of preprocessing the infrared image is required, and there is a large time consumption. In addition, for small infrared targets using the track correlation method In the detection method, the main idea is single-frame detection, and the single-frame target is screened through the method of track correlation between frames, so as to obtain the detection result of small targets, which can improve the accuracy of the algorithm to a certain extent, but there are algorithms The calculation process takes a long time and the system complexity is high

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