红外成像系统的非均匀性实时校正

针对红外相机系统响应非均匀性所产生的竖条纹固定噪声,提出了基于多线程优化的单帧红外图像非均匀性实时校正算法。该算法参考全变分理论的非均匀性校正算法确定噪声与图像输出之间的加性校正关系,建立了描述条纹噪声的数学模型;通过滤波算法将图像分为高频分量和低频分量,运用建立的条纹噪声模型,基于最小二乘法从高频部分中拟合出条纹噪声。最后,使用全变分理论确定的加性关系对图像进行校正。为了提高算法的计算速度,运用多线程技术对算法进行了优化。对提出的算法与MIRE(Midway Infrared Equalization)算法及传统双边滤波算法进行了图像质量评价和性能对比。结果显示:本文算法使图像非均匀性较原图降低了3%;算法效率与MIRE算法无异,系统运行时间在320×256的14位红外图像上为1.5ms/frame,达到了工程标准。

Real-time non-uniformity correction of infrared imaging system

A real-time Non-Uniformity Correction(NUC) algorithm for a single-frame infrared image was proposed based on multi-thread optimization to correct the strip-type Fixed Pattern Noise (FPN ) generated by non-uniformity response from an infrared camera .Firstly ,the plus-relationship of the output value and the noise was determined by NUC algorithm based on total variation theory and a mathematical model was established to describe the strip noise . The image was split into a high-frequency component and a low-frequency component by filters ,and the strip noise was fitted from the high-frequency component by the mathematical model .Finally ,the real infrared image was restored by the plus-relationship obtained from the total variation theory .To improve the computing speed , the proposed algorithm was optimized with the multi-thread . The image quality evaluation of the proposed algorithm was carried out and its performance was compared with the Midway Infrared Equalization(MIRE) and the bilateral filter methods .Experimental results indicate that the proposed algorithm has reduced the response non-uniformity by 3% as compaired with original image according to national standard GB/T 17444-1998 , and its efficiency is no difference with that of the MIRE . Moreover ,system running time for an 14 bit infrared image with a resolution of 320 × 256 is 1 .5 ms/frame , which meets the engineering requirements .