Intrinsic Images by Entropy Minimization
Intrinsic Images by Entropy Minimization
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DOI：
10.1007/978-3-540-24672-5_46
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发表时间：
2004-05
期刊：
影响因子：
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通讯作者：
G. Finlayson;M. S. Drew;Cheng Lu
中科院分区：
文献类型：
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作者：
G. Finlayson;M. S. Drew;Cheng Lu
最近提出了一种从3波段彩色图像中恢复不变图像的方法。不变图像最初是一维灰度级，但这里导出为2D色度，它与照明无关，并且也去掉了阴影：它形成了一种本征图像，可以用作恢复与照明条件无关的彩色图像的指南。照明颜色和强度的不变性意味着这些图像在很大程度上也没有阴影。设计的方法基于朗伯反射率、近似普朗克照明和相当窄带的相机传感器的假设来寻找本征反射率图像。然而，当这些假设不成立时，该方法运行良好。一条重要的信息是对数色度空间中“不变方向”的角度。到目前为止，我们通过初步的校准程序收集了这些信息，使用所涉及的相机来捕捉不同光线下的彩色目标的图像。在这篇文章中，我们证明，通过认识到一个简单但重要的事实，我们实际上可以省去校准步骤：正确的投影是使得到的不变图像中的熵最小的投影。为了证明这一点，我们首先考虑合成图像，然后将该方法应用于真实图像。我们表明，不仅出现了正确的无阴影图像，而且所找到的角度与从校准中恢复的角度一致。结果表明，对于未知摄像机的图像，我们可以找到无阴影的图像，并将该方法成功地应用于去除无源图像中的阴影。
A method was recently devised for the recovery of an invariant image from a 3-band colour image. The invariant image, originally 1D greyscale but here derived as a 2D chromaticity, is independent of lighting, and also has shading removed: it forms anintrinsic imagethat may be used as a guide in recovering colour images that are independent of illumination conditions. Invariance to illuminant colour and intensity means that such images are free of shadows, as well, to a good degree. The method devised finds an intrinsic reflectivity image based on assumptions of Lambertian reflectance, approximately Planckian lighting, and fairly narrowband camera sensors. Nevertheless, the method works well when these assumptions do not hold. A crucial piece of information is the angle for an “invariant direction” in a log-chromaticity space. To date, we have gleaned this information via a preliminary calibration routine, using the camera involved to capture images of a colour target under different lights. In this paper, we show that we can in fact dispense with the calibration step, by recognizing a simple but important fact: the correct projection isthat which minimizes entropyin the resulting invariant image. To show that this must be the case we first consider synthetic images, and then apply the method to real images. We show that not only does a correct shadow-free image emerge, but also that the angle found agrees with that recovered from a calibration. As a result, we can find shadow-free images for images with unknown camera, and the method is applied successfully to remove shadows from unsourced imagery.