Nonuniformity correction method and system of infrared image

Abstract

The invention, which relates to the field of infrared image processing, discloses a nonuniformity correction method and system of an infrared image. The method comprises: carrying out primary correction on a to-be-corrected image to obtain a first image; collecting uniform background images of the to-be-corrected image at a plurality of different radiation intensities and carrying out correction on the uniform background images at different radiation intensities to obtain a plurality of auxiliary images at different radiation intensities; and calculating offset backgrounds of the auxiliary images, establishing a compensation correction model at a current scene based on a weighing method, calculating weighting coefficients of the auxiliary images in the compensation correction model by enabling a quadratic sum of a pixel difference between the image after compensation correction and an expected image to be minimized, obtaining a compensation correction formula at the current scene, and carrying out compensation correction on the first image to obtain a second image. With the method provided by the invention, the influence on infrared imaging by the temperature change of the detector and the scene change can be eliminated and the infrared imaging quality can be improved.

Description

Technical field [0001] The invention relates to the field of infrared image processing, in particular to a method and system for correcting infrared image non-uniformity. Background technique [0002] With the continuous development of infrared imaging technology, it has been widely used in civilian, military and other fields. In the infrared imaging process, the non-uniformity of the infrared image is easily affected by the temperature of the detector and the change of the image scene, which seriously reduces the imaging quality of the infrared detector. Therefore, it is necessary to correct the non-uniformity of the infrared image to eliminate external factors for imaging The impact of quality. [0003] Infrared image non-uniformity correction usually uses shutterless calibration algorithm. There are many existing shutterless calibration algorithms. Refer to the patent number GB2445254A based on the minimum square sum of adjacent pixel difference correction algorithm. This algor...

AI Technical Summary

Problems solved by technology

In the process of infrared imaging, the non-uniformity of the infrared image is easily affected by the temperature of the detector and the change of the image scene, which seriously reduces the imaging quality of the infrared detector. Therefore, it is necessary to correct the non-uniformity of the infrared image to eliminate the influence of external factors on the imaging quality impact

[0003] Infrared image non-uniformity correction usually adopts a shutterless calibration algorithm, and there are many existing shutterless calibration algorithms, refer to the shutterless correction algorithm based on the minimum square sum of adjacent pixel differences proposed by the patent number GB2445254A, the algorithm first needs Dozens of images of uniform background are collected within the working temperature range of the detector, and then the corresponding offset background is calculated. During real-time correction, the real-time offset correction parameters are obtained by calculating the weighted sum of all offset backgrounds. The weighted The coefficients can be continuously adaptively updated according to the changes of the image scene, but this algorithm only considers the influence of the detector temperature on the image quality, and does not consider the influence of the external scene change on the image non-uniformity, and only realizes the effect based on the detector temperature. The non-uniformity correction of the infrared image, the image quality after the correction of the algorithm is poor

[0004] Also refer to a shutterless non-uniformity correction algorithm based on the template method proposed by the patent No. CN201210232737.7. This algorithm selects a fixed bias background to calculate the correction parameters. With the actual temperature of the detector and the bias The detector temperature difference corresponding to the background is getting bigger and bigger, and the calculation error will be bigger and bigger, resulting in worse image quality after correction.

[0005] The infrared image quality obtained by the shutterless correction algorithm in the prior art is poor, and a new algorithm needs to be proposed to improve the infrared imaging quality

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