基于灰度段的立体匹配算法

立体匹配一直是计算机视觉领域的一个中心研究问题.为了得到适用于IBR(image-basedrendering)技术中视图合成的比较精确的高密度视差图,提出了一种基于灰度段的立体匹配算法.该算法以灰度段作为匹配基元,并将应用于语音识别的DTW(dynamictimewarping)方法引入灰度段的匹配算法中.相对于点基元,灰度段基元覆盖的图像空间要大得多,且不易受噪声、光度变化等因素的影响,因此可以减少误匹配发生的几率,更容易进行匹配,比特征线段、二次曲线等匹配基元计算要简便得多.实验结果表明,该算法效果良好,具有实用价值.

A Stereo Matching Algorithm Based on Gray-Level Segments

Stereo matching has long been one of the central research problems in computer vision. A stereo matching algorithm is proposed based on gray level segments in order to recover dense depth map for the application of view synthesis in IBR (image-based rendering). This algorithm uses gray level segments as elements to be matched, and introduces the principle of DTW (dynamic time warping), which applied for speech recognition, into the matching processes on the segments. Covering more image space than point elements, gray-level segments are less sensitive to noise and photometric variations and easier to be matched, and can reduce the false matching. Moreover, gray-level segments segments require less computational resources than feature-based line segments and conices. Experimental results show that this algorithm is effective and of great value to use.