基于伽马压缩的红外图像非均匀性校正算法研究

Nonuniformity Correction of Infrared Image Based on Gamma Compression

摘要:

针对红外探测器输出12位像素深度响应,而数字图像显示通常为8位的情况,提出一种基于伽马压缩的非均匀性校正算法。该算法利用自适应伽马曲线将探测器输出的响应进行压缩,然后基于两点校正对中低温图像和高温图像运用不同的校正系数进行校正。实验结果表明:该算法的非均匀性校正效果好,能够将传统两点校正方法校正后的残余非均匀性降低20%左右,校正后的中低温图像细节信息丰富,层次感强。

Abstract:

Aiming at the response with 12bit pixel depth outputted by the infrared detector, while the digital image displayed on the screen is usually 8 bit, a nonuniformity correction algorithm of infrared image based on Gamma compression is proposed. This algorithm uses adaptive Gamma curves to compress the response of detector, and then corrects the medium-low temperature images and high temperature images with different calibration coefficients by using two-points correction. The experimental results show that the algorithm obtains good effect for nonuniformity correction, which can reduce the nonuniformity of the images corrected by traditional two-points correction by about 20%, and the medium-low temperature image after correction has rich detail information and good layering.