Area array infrared camera quick scaling and heterogeneity calibrating method based on variant integral time

Abstract

The invention provides an area array infrared camera quick scaling and heterogeneity calibrating method based on the variant integral time, which includes the following steps: electrifying an infrared area array camera imaging system, and then shielding an optical path by an anti-dazzling screen driven by a micro motor; generating 3 kinds of integral time T1, T2 and T3 by a timing sequence drive module, simultaneously collecting response data X1<n>(i,j), X2<n>(i,j) and X3<n>(i,j) of F (F is not smaller than 50) frames through an image acquisition module at different kinds of integral time, and calculating out the respective mean values: X1(i,j), X2(i,j) and X3(i,j), wherein n=1-50, and (i,j) is the pixel coordinate. The area array infrared camera quick scaling and heterogeneity calibrating method based on the variant integral time is simple in implementation process, does not depend on a black body and a temperature control device thereof, needs less integral time points, and the integration with an infrared imaging process hardware system is easy.

Description

Technical field [0001] The invention belongs to the technical field of image processing in the imaging technology of an area array infrared camera, in particular to a rapid calibration and non-uniformity correction method for an area array infrared camera based on a variable integration time. Background technique [0002] Because of the advantages of staring imaging and high frame rate, red outer array cameras are widely used in various infrared imaging systems such as surveying and mapping, remote sensing, night vision reconnaissance, and temperature monitoring. Due to the limitation of the manufacturing level at this stage, the non-uniformity of the response between the detection elements of the infrared area scan camera generally exists. This non-uniformity forms a fixed pattern noise and affects the imaging quality of the system. The non-uniformity correction of each detection element of the area array infrared camera is a necessary measure to improve the image quality and th...

AI Technical Summary

Problems solved by technology

The shortcomings of this method are that firstly, the least squares method requires too many integration time points, and secondly, the detection and compensation of IRFPA blind elements are not considered in the algorithm.

Its disadvantage is that the selection of integration time depends on the result of blackbody calibration, and has not gotten rid of the dependence on blackbody

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