Linearisation of RGB camera responses for quantitative image analysis of visible and UV photography: a comparison of two techniques.
Linearisation of RGB camera responses for quantitative image analysis of visible and UV photography: a comparison of two techniques.
复制标题
DOI：
10.1371/journal.pone.0079534
复制
发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Wilksch PA
中科院分区：
文献类型：
--
作者：
Garcia JE;Dyer AG;Greentree AD;Spring G;Wilksch PA
线性相机响应需要恢复入射辐照度的总量，定量图像分析，光谱重建相机响应和光谱灵敏度曲线的特性。两个市售的数码相机配备拜耳过滤器阵列和敏感的可见光和近紫外线辐射的特点是使用双指数和贝塞尔曲线。这两种方法都成功地拟合了被测器件的整个特性曲线，从而可以准确地恢复线性相机响应，特别是那些对应于曝光范围中间的响应。尽管如此，这两种方法在所需输入参数的性质以及与在曝光范围极端获得的恢复线性相机响应相关的不确定性方面有所不同。在这里，我们演示了使用这两种方法来检索有关场景辐照度的信息，描述和量化的线性相机响应的估计中所涉及的不确定性。
Linear camera responses are required for recovering the total amount of incident irradiance, quantitative image analysis, spectral reconstruction from camera responses and characterisation of spectral sensitivity curves. Two commercially-available digital cameras equipped with Bayer filter arrays and sensitive to visible and near-UV radiation were characterised using biexponential and Bézier curves. Both methods successfully fitted the entire characteristic curve of the tested devices, allowing for an accurate recovery of linear camera responses, particularly those corresponding to the middle of the exposure range. Nevertheless the two methods differ in the nature of the required input parameters and the uncertainty associated with the recovered linear camera responses obtained at the extreme ends of the exposure range. Here we demonstrate the use of both methods for retrieving information about scene irradiance, describing and quantifying the uncertainty involved in the estimation of linear camera responses.
登录
查看更多内容
影响因子：
2
作者：
Lahuerta Zamora, L.;Mellado Romero, A. M.;Martinez Calatayud, J.
通讯作者：
Martinez Calatayud, J.
DOI：
10.1364/josaa.27.000251
发表时间：
2010-02-01
影响因子：
1.9
作者：
Shimano, Noriyuki;Hironaga, Mikiya
通讯作者：
Hironaga, Mikiya
影响因子：
1.4
作者：
Barnard, K;Funt, B
通讯作者：
Funt, B
DOI：
10.1111/j.1095-8312.2012.01877.x
发表时间：
2012-07-01
影响因子：
1.9
作者：
Cassey, Phillip;Thomas, Gavin H.;Miksik, Ivan
通讯作者：
Miksik, Ivan
影响因子：
48
作者：
Schneider CA;Rasband WS;Eliceiri KW
通讯作者：
Eliceiri KW