中文摘要：

为解决传统信息散度算法存在物体图像大小不一致以及非连续区域深度恢复精度低等问题,提出了一种新的基于空间变化窗口的信息散度算法.该算法计算两幅原散焦图像之间的单应矩阵,并利用单应矩阵重新矫正原图像以获得相同大小的散焦图像对,通过空间变化的窗口结构来估计不连续区域附近的深度.模拟实验和实际图像实验结果表明,文中改进算法可以避免平滑非连续域的深度值并提高估计的精度.

英文摘要：

In order to solve such problems existing in the traditional information divergence algorithm as the inconsistence of object image sizes and the low accuracy of the depth recovery in non-contiguous areas,a new information divergence algorithm is proposed based on space-variant window.In this algorithm,first,the homography matrix between two original defocused images is calculated.Then,by using this homography matrix,the original images are rectified to obtain new defocus images of the same size.Moreover,the depth of non-contiguous area is estimated through the space-variant window structure.The simulated and real-image experimental results show that the proposed algorithm can avoid the smoothing depth in discontinuities and improve the precision.