Extracting intrinsic images from multi-spectral

Ming Shao, Yunhong Wang
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引用次数: 2

Abstract

Intrinsic images as a useful midlevel description attract more and more attentions in computer vision. According to Barrow and Tenenbaum's theory, a face image can be decomposed into two images: a reflectance image and an illumination image. Finding such decomposition remains difficult since it is an ill-posed problem. In this paper, we focus on a slightly easier problem: given a pair of multi-spectral facial images, can we recover its reflectance image and corresponding illumination image? Experiments show that it is promising and feasible. According to recent research in skin color model and Quotient Image, we propose a simple but effect method to derive the intrinsic image from a near infrared and a visual image. After modulating the grey distribution of visual images and dividing visual images by near infrared ones, we can recover its reflectance and illumination image. Experimental results show that our method is promising in image synthesis and processing.
从多光谱中提取本征图像
内在图像作为一种有用的中级描述在计算机视觉中越来越受到重视。根据Barrow和Tenenbaum的理论,人脸图像可以分解为两种图像:反射图像和照明图像。找到这样的分解仍然很困难,因为它是一个不适定问题。在本文中,我们关注一个稍微简单一点的问题:给定一对多光谱人脸图像,我们能否恢复其反射率图像和相应的照明图像?实验表明,该方法是可行的。根据最近在肤色模型和商数图像方面的研究,提出了一种简单而有效的从近红外图像和视觉图像中提取固有图像的方法。通过对视觉图像的灰度分布进行调制,将视觉图像分割成近红外图像,即可恢复其反射率和照度图像。实验结果表明,该方法在图像合成和处理方面具有较好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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