郭惠楠, 曹剑中, 王华, 张建, 杨洪涛. 高动态范围数字相机sRGB色彩空间颜色管理[J]. 红外与激光工程, 2014, 43(S1): 238-242.
引用本文: 郭惠楠, 曹剑中, 王华, 张建, 杨洪涛. 高动态范围数字相机sRGB色彩空间颜色管理[J]. 红外与激光工程, 2014, 43(S1): 238-242.
Guo Huinan, Cao Jianzhong, Wang Hua, Zhang Jian, Yang Hongtao. Color management of sRGB color space for HDR digital camera[J]. Infrared and Laser Engineering, 2014, 43(S1): 238-242.
Citation: Guo Huinan, Cao Jianzhong, Wang Hua, Zhang Jian, Yang Hongtao. Color management of sRGB color space for HDR digital camera[J]. Infrared and Laser Engineering, 2014, 43(S1): 238-242.

高动态范围数字相机sRGB色彩空间颜色管理

Color management of sRGB color space for HDR digital camera

  • 摘要: 数字成像设备在传输、显示图像时需要进行设备的特性化处理,该过程是设备颜色管理中的重要环节.为了保证输出图像的色彩复现能力,高动态范围数字相机需要根据设备自身特性进行特性化.现有特性化过程一般针对8位数字相机,并且转换矩阵的标定较为复杂,容易产生系统误差,矩阵精度易受影响.针对上述问题,提出了一种高动态范围彩色数字相机颜色管理方法,利用相机输出图像与被摄目标的色彩属性建立了RGB色彩空间到CIE1931 XYZ色彩空间的映射关系,并采用最小二乘拟合法对映射矩阵进行标定,最终将相机的RGB色彩空间转换至sRGB标准色彩空间,解决了高动态相机的特性化问题.实验证明,该方法操作简单,设备通用性较强,拟合均方误差优于0.08,具有较好的鲁棒性.

     

    Abstract: Digital imaging devices require color space characterization while transferring or showing image between various devices which is a crucial part of color management for digital devices. In order to keep the color reproduction ability for output image, a high dynamic range digital(HDR) camera requires characterization based on the device properties. For existing characterization algorithms, which are in most cases for 8-bit-digital cameras, the processes of transformation matrix calibration are involved in some complex approaches, which are easy to cause system errors and influence the precision of color space transformation matrix. Accordingly, a color management approach was proposed for a high dynamic range colorful digital camera that using a color space mapping from camera RGB space to CIE1931 XYZ color space to estimate the function relation between two color spaces and using the least square method to achieve color matrix calibration. Eventually the camera RGB color space was transformed to sRGB standard color space which achieves characterization for HDR camera. Experimental results show that this method is of good robustness and easy to realize as well as the mean square error is less than 0.08.

     

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