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A New Shadow Removal Method for Color Images

机译:彩色图像的新影子拆除方法

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Shadow and variable illumination considerably influence the results of image understanding such as image segmentation, object tracking, and object recognition. The intrinsic image decomposition is to separate the reflectance and the illumination image from an observed image. The intrinsic image decomposition is very useful to remove shadows and then improve the performance of image understanding. In this paper, we present a new shadow removal method based on intrinsic image decomposition on a single color image using the Fisher Linear Discriminant (FLD). Under the assumptions-Lambertian surfaces, approximately Planckian lighting, and narrowband camera sensors, there exist an invariant image, which is 1-dimensional greyscale and independent of illuminant color and intensity. The Fisher Linear Discriminant is applied to create the invariant image. And further the shadows can be removed through the difference between invariant image and original color image. The experimental results on real data show good performance of this algorithm.
机译:阴影和可变照明显着影响图像理解的结果,例如图像分割,对象跟踪和对象识别。内在图像分解是将反射率和照明图像与观察到的图像分开。内在图像分解对于移除阴影并提高图像理解的性能非常有用。在本文中,我们使用Fisher线性判别(FLD)基于单彩色图像上的内在图像分解的新的阴影去除方法。在假设 - 兰伯蒂曲面下,大约普朗斯照明和窄带照相机传感器,存在不变的图像,这是1维灰度和无光度的颜色和强度。渔业线性判别应用于创建不变图像。并且可以通过不变图像和原始彩色图像之间的差异来删除阴影。实验结果对真实数据显示出该算法的良好性能。

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