一种应用轮廓锐度的单视点图像深度信息提取算法  

A Depth Information Extraction Algorithms for Single View Image Using Profile Sharpness

作　　者：马利[1,2] 李晶皎[2] 马技[1,2] 彭紫一 

机构地区：[1]辽宁大学信息学院,沈阳110036 [2]东北大学信息科学与工程学院,沈阳110819

出　　处：《小型微型计算机系统》2016年第2期316-320,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(61101115)资助;辽宁省教育厅一般科技项目(L2012003)资助

摘　　要：针对单视点图像恢复场景深度信息算法中采用图像高层次线索算法复杂度高,计算量大的情况,提出一种应用图像低层次线索——边缘轮廓锐度的单视点图像深度信息提取算法.将模糊信息作为深度信息提取的约束条件,应用边缘轮廓锐度信息作为模糊信息估计特征,建立改进的轮廓跟踪模型,实现图像的轮廓提取.利用先验假设轮廓深度图,提取场景中深度信息.为了避免因图像噪声及轮廓跟踪局部求解误差造成的干扰,采用交叉双边滤波方法对深度图进行了优化.经对大量图像进行对比实验,实验结果表明算法简单、实用,可以有效地实现了单视点图像深度信息的提取.To overcome the high complexity and the large computation of the recovery scenarios depth information algorithm using im- age high-level cues, a depth imformation extration algorithm for the single view image using profile sharpness of image low-level cues was proposed. In this paper, the blur information is considered as depth extration constraints. It establish an improved model of contour tracking with the edge contour sharpness information and consequently the coutour is extrated. A prior hypothesis of depth gradient is used to assign depth to extrate the scenarios depth information. Avoiding the interferences by image noise and the errors with the local optimum of the contour tracking, the depth map is optimized by the cross bilateral filter. Experimental results on a variety of images show that a liable extration of the depth for the single view image can be acquireared availably with this simple but effective algo-rithm.

关 键 词：轮廓锐度 深度信息提取 单视点图像 轮廓跟踪 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]