Detection of weak and small infrered targets under complicated background

Abstract

The technique of weak small target detection and recognition has been the key technique of the electro-optical detecting system, many scholars are engaging the research of detection for weak and small targets. The effective detection for small targets in low SNR images is still a hot research field. Because infrared sensor is easily affected by atmosphere hot radiation, long distance and sensor noise, the detected targets in infrared images often present like small targets and drowned in noise. The basic problem inherent to extent the detection range is the detection of small, low observable, no obvious structural information in images and complicated background. In order to improve the detection ratio of weak small targets and decrease the false alarming ratio in the condition of complicated background, the paper presents the technology of pretreatment of infrared images and the technology of detection for weak small targets, mainly including the technology of Sobel edge algorithm and multi-degree and multi-orientation gradient. Based upon horizon-correlative characteristic of infrared images which were gotten by scanning, considering of the target properties in complicated background, an algorithm of weak and small target detection is presented. Because the images appear horizon-correlative characteristic, Sobel horizontal operator is adopted. By this algorithm, the background clutter was suppressed. Then an adaptive threshold was proposed to extract the precise location of small target. Incorporated with the two methods, a single frame weak and small target detection algorithm was built. Its high performance was then proved in a serial of experiments. In order to solve the detection problems of weak and small infrared targets under complicated background, a detection algorithm integrating with multi-degree and multi-orientation gradient fusion is proposed. Based on the principle of infrared radiation property of target, i.e., the gradient variations of pixel gray scale in horizontal and vertical directions, the algorithm handles the property of weak and small target into analysis of image singularity and detects targets by means of multi-degree gradient step length. Then the detected results show this method can remove most false targets. As a result, the algorithms have fulfilled the engineering demands for reliability and real-time property.