Infrared small target detection method based on adaptive peak gradient descent filter

Abstract

The invention discloses an infrared small target detection method based on an adaptive peak gradient descent filter, and solves the problems that irregular clutters cannot be suppressed and weak target detection performance is low due to the fact that a rectangular window is used for extracting local features of an infrared image in an existing infrared weak target detection method. According to the method, the characteristic that the local pixel gray value gradient in an infrared image is reduced and the characteristic that the local contrast difference exists between an infrared weak and small target and a background are fully utilized. Irregular clutters can be inhibited; a rectangular window does not need to be set according to target size; the invention is beneficial for detecting targets with pixels smaller than 9 * 9, improves the performance of infrared weak and small target detection, and achieves the effect of early detection.

Description

technical field [0001] The invention belongs to the technical field of image target detection, and in particular relates to an infrared small target detection method based on an adaptive peak gradient descent filter. Background technique [0002] Infrared small target detection plays a key role in the infrared early warning system. The target appears as a point with a small amount of structural information and shape features in the infrared image, so that the target cannot be segmented and extracted with detailed features. In a real infrared image, due to the performance of the infrared focal plane and the environment in which the target is located, small targets are easily overwhelmed by noise and clutter. Therefore, how to detect weak infrared targets from infrared images full of noise and complex clutter without generating false alarms is still a challenging problem. [0003] In the past decade, researchers have proposed single-frame detection methods and multi-frame de...

AI Technical Summary

Problems solved by technology

Since the rectangular windows used in these methods may contain both irregular clutter and the background, they cannot effectively suppress irregular clutter

When the window cell contains both clutter and objects smaller than the cell size, the detection performance of weak and small objects degrades

Images