基于边缘检测的Kinect深度图像去噪算法  

Kinect Depth Image Denoising Based on Edge Detection

作　　者：邹星星[1] 钟莎[1] 马增强[1,2] 

机构地区：[1]石家庄铁道大学电气与电子工程学院,河北石家庄050043 [2]河北省交通安全与控制重点实验室,河北石家庄050043

出　　处：《湖南工业大学学报》2013年第6期36-39,72,共5页Journal of Hunan University of Technology

基　　金：国家自然科学基金资助项目(11372199);国家级大学生创新创业训练计划基金资助项目(201210107005)

摘　　要：Kinect实时提取的深度图像映射得到的彩色图像以及目标背景分离图像边缘存在明显锯齿,且图像噪声大,质量较差。对此提出一种针对Kinect深度图像去噪算法。运用基于Prewitt算子的分块自适应阈值边缘检测算法可得到比较精细的图像边缘;进而根据获取边缘信息对深度图像进行分类,边缘区采用单向多级中值滤波算法进行降噪处理,而非边缘区采用双向多级中值滤波算法进行降噪处理。最终利用Kinect得到边缘清晰,噪声较小的高质量深度图像,实验证明了算法的有效性。The depth image and the target background image separation captured by Kinect real-time extraction exist obvious serrated and loud image noise. Proposes a denoising algorithm for Kinect depth image. Applies the auto-regulative thresholds edge detection algorithm based on Prewitt operator to obtain fine image edge, then classifies the depth image according to the edge information, and reduces noises of the edge region by the unidirectional multistage median filtering algorithm, while suppresses noises at non edge region by the bidirectional multistage median filtering algorithm. Finally, acquires high quality depth images of clear-edge and small noise by the proposed Kinect algorithm, and verifies the effectiveness of the algorithm.

关 键 词：边缘检测 多级中值滤波算法 PREWITT算子 KINECT 

分 类 号：TN911.73[电子电信—通信与信息系统]