基于正交分解的室外阴影图像恢复

Outdoor Shadow Image Restoration Based on Orthogonal Decomposition

图像中的阴影会降低计算机或机器人视觉的鲁棒性.为了消除这一干扰,本文提出了一种单幅彩色图像阴影自动消除算法.首先应用图像光照正交分解模型,将一彩色图像正交分解为光照本征图像和光照强度图像,然后根据同一物体在阴影和非阴影中的成像具有相同光照不变分量和不同光照强度的特性,对图像中的阴影区域进行自动恢复,从而生成无阴影图像.与目前已有的图像阴影恢复算法相比,本文算法无需对阴影区域进行识别检测且具有较强的实时性和鲁棒性,同时可有效消除图像中的浅阴影和细碎阴影.另外,对同一场景不同光照下拍摄的系列图像,所提算法处理的结果具有较好的光照恒常性.通过与目前主流阴影去除算法实验相比,验证了所提算法的实时性、鲁棒性和先进性.

Shadow reduces the robustness of computer vision.To eliminate this interference,we propose a method to remove shadow from an image automatically.We first use an orthogonal decomposition model to decompose a color image into an illumination invariant image and an illumination image.Then,considering the characteristic that image of the same object shares the same illumination invariant value and have different illumination values in and out of shadow,we generate a shadow-free image by automatically restoring the shadow area.In comparison with existing shadow removal algorithms,our method can generate a shadow-free image without shadow detection.It also has good real-time performance and robustness.It can effectively remove light or fine shadows.For a series of images taken under different illuminations in a scene,our results have better illumination constancy.We verify the real-time property,robustness,and advancement of our method by comparing with advanced shadow removal algorithms.