We present an algorithm for separating the local gradient information by using Multiple images in the presence of highlights and shadows.
提出一种在多光源下多幅图像来恢复有高光和阴影物体三维表面的方法。
Based on results of change detection using statistical hypothesis test,the intensity,hue and saturation in the YCbCr color space are employed to recognize and eliminate shadows and .
在一种快速动态背景图像初始化的基础上,建立了Gaussian统计背景模型;基于使用统计假设检验方法检测变化区域的结果,利用YCbCr颜色空间的亮度、颜色信息,识别和消除视频序列图像中的阴影和反光等。