摘要
自然环境下获得的植物叶片图像往往由于阴影的存在而严重影响植物叶面特征的提取,为了解决这个问题,提出了一种基于YCbCr颜色空间的阴影的检测与去除方法.首先在YCbCr颜色空间中计算Y通道强度,采用阈值法检测阴影区域.然后在YCbCr颜色空间下根据光照模型对阴影区每个像素进行光照恢复.最后转化到RGB颜色空间下.相对于直接在RGB空间进行的阴影去除,该方法减弱阴影区的边缘效应,使得去除阴影后的区域与非阴影区的颜色更加一致,恢复图像看上去更加自然.
With the influence of shadow on plant leaf images in natural environment, extraction of foliar features will be seriously affected. Hence, this paper proposes a method of shadow detection and removal based on YCbCr color space. First, the intensity of channel Y in YCbCr color space is calculated and the shadow regions are detected by a threshold on the intensity. Then according to the shadow model, light restorations for each pixel in shadow regions are made and the results are finally transformed to the RGB color space. Compared with direct shadow removal in the RGB space, this method weakens the edge effect, thus making the color between the post removal shadow region and non shadow region more uniform and the restored images more natural.
出处
《计算机系统应用》
2015年第11期262-265,共4页
Computer Systems & Applications
