为适应人眼的感知能力,伪彩色编码技术常被用于处理红外探测系统输出的灰度图像.较于灰度图像,计算机对彩色图像处理所需的存储量与计算量较大.鉴于某些红外设备只提供伪红外图像的输出,因此伪红外图像的去彩色化算法成为该文的主要研究目标.除利用最大值分解、平均值与光亮度法3种常见灰度化算法对伪红外图像的处理外,直接对伪彩色图像进行解码的方式也在文中被用于红外图像的去彩色化.实验基于上述两类方法,对线性与正弦非线性彩虹伪彩色图像的去彩色化进行了研究,并对处理后图像的质量进行了比较.实验结果表明,常规灰度算法处理后的伪彩色图像质量较差,而线性伪彩色图像经解码处理后可完全恢复出原图,实现0均方差;对于正弦非线性算法,虽然存在由量化误差引起的损失,但与原图像比仍有非常低的均方差(0.309 4)与高的峰值信噪比(101.356 0).

Considering the human eyes' perception capability,the pseudo color coding technology is usually adopted to colorize the output gray image of infrared systems.Comparing to gray images,computers need more memory and calculation to process color images.Since some infrared equipments only provide pseudo color images,the grayscale conversion of pseudo color image was studied.Besides the 3 common algorithms,maximum decomposition,average and luminance,a decoding method was presented to decolorize infrared images.Based on the 2 kinds of methods above,decolorizing for both linear and sinusoidal nonlinear pseudo color images were studied in experiment;furthermore,image quality was also compared.The experiment result demonstrates that the decoding method is a kind of lossless algorithm for linear pseudo color image with 0 mean squared error.For sinusoidal nonlinear algorithm,loss due to quantization errors are inevitable,it still has a quite low mean square error(0.309 4)and high peak signal noise ratio(101.356 0).