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首页> 外文期刊>Pattern Analysis and Machine Intelligence, IEEE Transactions on >Estimating Information from Image Colors: An Application to Digital Cameras and Natural Scenes
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Estimating Information from Image Colors: An Application to Digital Cameras and Natural Scenes

机译：从图像颜色估计信息：在数码相机和自然场景中的应用

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摘要

The colors present in an image of a scene provide information about its constituent elements. But the amount of information depends on the imaging conditions and on how information is calculated. This work had two aims. The first was to derive explicitly estimators of the information available and the information retrieved from the color values at each point in images of a scene under different illuminations. The second was to apply these estimators to simulations of images obtained with five sets of sensors used in digital cameras and with the cone photoreceptors of the human eye. Estimates were obtained for 50 hyperspectral images of natural scenes under daylight illuminants with correlated color temperatures 4,000, 6,500, and 25,000 K. Depending on the sensor set, the mean estimated information available across images with the largest illumination difference varied from 15.5 to 18.0 bits and the mean estimated information retrieved after optimal linear processing varied from 13.2 to 15.5 bits (each about 85 percent of the corresponding information available). With the best sensor set, 390 percent more points could be identified per scene than with the worst. Capturing scene information from image colors depends crucially on the choice of camera sensors.
机译：场景图像中显示的颜色提供有关其组成元素的信息。但是，信息量取决于成像条件以及信息的计算方式。这项工作有两个目标。首先是明确推导可用信息的估计量，以及在不同光照条件下从场景图像中每个点的色值中检索出的信息。第二是将这些估计器应用于由五组数码相机中使用的传感器以及人眼的锥形感光器获得的图像的模拟。在相关色温分别为4,000、6,500和25,000 K的日光光源下，获得了50个自然场景的高光谱图像的估计值。根据传感器的不同，在最大照度差异的图像上可获得的平均估计信息范围从15.5到18.0位，并且经过最佳线性处理后检索到的平均估计信息在13.2位到15.5位之间变化（每个信息约占相应可用信息的85％）。使用最佳传感器集，与最差传感器相比，每个场景可以识别出390％的点。从图像颜色中捕获场景信息主要取决于相机传感器的选择。

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