Residual heterogeneous noise elimination method for aiming at thermal infrared image after heterogeneous correction

Abstract

The invention discloses a residual heterogeneous noise elimination method for aiming at thermal infrared image after heterogeneous correction. The method comprises the following steps of 1), imaging a black body by means of an infrared imaging system at different temperature for obtaining an infrared image; 2), performing heterogeneous correction on the obtained black body image; 3), calculating a pixel mean value of the black body image after correction; 4), subtracting the pixel mean value from each pixel value in the black body image after correction and storing results; 5), photographing an outdoor scene image and performing heterogeneous correction; and 6), comparing the image pixel value after correction with the image mean values at different temperatures for finding out a subtraction number array which corresponds with a nearest value, and subtracting the value of the corresponding position in the array from the pixel value for obtaining a new image. According to the residual heterogeneous noise elimination method, defects in a traditional infrared image noise elimination method are settled, and furthermore the residual heterogeneous noise is more effectively and more accurately eliminated. According to the residual heterogeneous noise elimination method, the residual heterogeneous noise in the infrared image can be effectively eliminated without original information loss of the image, and furthermore a high-quality restored image is obtained.

Description

Technical field: [0001] The invention belongs to the technical field of high-sensitivity infrared imaging and its application, is based on a cooling type infrared imaging hardware system, and relates to the removal of residual spatial noise after non-uniform correction of infrared images. Background technique: [0002] With the development of infrared imaging technology, people have higher and higher requirements for the sensitivity level of thermal infrared imaging systems, and the demand for obtaining higher-sensitivity infrared images is also more urgent. Needed, because even after non-uniformity correction, the infrared image still has residual non-uniform spatial noise, which will greatly affect the resolution of the signal in high-sensitivity occasions, and new measures must be taken to further improve the sensitivity of the infrared image Level. High-sensitivity infrared imaging systems generally use cooled infrared focal plane devices. Since the response characteris...

AI Technical Summary

Problems solved by technology

[0002] With the development of infrared imaging technology, people have higher and higher requirements for the sensitivity level of thermal infrared imaging systems, and the demand for obtaining higher-sensitivity infrared images is also more urgent. Needed, because even after non-uniformity correction, the infrared image still has residual non-uniform spatial noise, which will greatly affect the resolution of the signal in high-sensitivity occasions, and new measures must be taken to further improve the sensitivity of the infrared image Level

High-sensitivity infrared imaging systems generally use cooled infrared focal plane devices. Since the response characteristics of each detector element in the focal plane array are not completely consistent, different detection photosensitive elements will produce different output signals for the same infrared radiation, making the infrared image appear abnormal. uniform noise

The conventional non-uniformity correction algorithm cannot completely remove the noise, but the residual noise does not affect the image quality in general applications, so it can be seen that there is no method to further remove the non-uniform noise in the infrared image after non-uniform processing

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