Abnormal element detection method for infrared array detector

Abstract

The invention discloses an abnormal element detection method for an infrared array detector. The method comprises the following steps of: 1, selecting a sampling point from each row in an input imagesequence; 2, calculating difference values of the gray value of each sampling point and pixels of upper and lower adjacent rows of the sampling point respectively, and summing the absolute values of all the difference values to obtain gray step values of the row and the upper and lower adjacent rows; 3, setting a gray level step threshold, comparing gray level step values obtained by traversal statistics of all rows with the gray level step threshold, and taking pixels with the gray level step values exceeding the gray level step threshold as quasi-abnormal elements; and 4, sorting and listingthe quasi-abnormal elements according to the gray step values, and taking a specified number of quasi-abnormal elements from the list as final abnormal elements. According to the invention, through real-time image analysis and data analysis, blind pixel detection is solved, an algorithm is easy to realize for randomly occurring flash elements, automatic real-time detection can be realized, and the debugging efficiency, the adaptability and the product quality of a thermal imager are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of infrared image processing, and relates to an abnormal element detection method for an infrared line array detector, in particular to automatic real-time detection of abnormal elements such as blind elements and flash elements of an infrared line array detector. Background technique [0002] As the main sensor of the fire weapon system, the thermal imager is mainly used to realize the functions of target detection, tracking, and identification. The infrared detector of its core device is limited by the current material preparation and technology level, as well as the complex working environment and observation scene. Changeable, and the influence of its own temperature and aging, when some pixels are imaged, there will be abnormal responses that have nothing to do with the scene, collectively referred to as abnormal elements. Among them, for the anomalous elements that respond to stable gray levels during ...

AI Technical Summary

Problems solved by technology

Existing scene-based flash element detection methods, some need to accumulate a large amount of sampling data, lack real-time performance; some need to establish data sets, and the degree of automation is low

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