Zhang Yue, Zou Huanxin, Luo Tiancheng, Qin Xianxiang, Zhou Shilin, Ji Kefeng
College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China.
School of Information and Navigation, Air Force Engineering University, Xi'an 710077, China.
Sensors (Basel). 2016 Oct 13;16(10):1687. doi: 10.3390/s16101687.
The superpixel segmentation algorithm, as a preprocessing technique, should show good performance in fast segmentation speed, accurate boundary adherence and homogeneous regularity. A fast superpixel segmentation algorithm by iterative edge refinement (IER) works well on optical images. However, it may generate poor superpixels for Polarimetric synthetic aperture radar (PolSAR) images due to the influence of strong speckle noise and many small-sized or slim regions. To solve these problems, we utilized a fast revised Wishart distance instead of Euclidean distance in the local relabeling of unstable pixels, and initialized unstable pixels as all the pixels substituted for the initial grid edge pixels in the initialization step. Then, postprocessing with the dissimilarity measure is employed to remove the generated small isolated regions as well as to preserve strong point targets. Finally, the superiority of the proposed algorithm is validated with extensive experiments on four simulated and two real-world PolSAR images from Experimental Synthetic Aperture Radar (ESAR) and Airborne Synthetic Aperture Radar (AirSAR) data sets, which demonstrate that the proposed method shows better performance with respect to several commonly used evaluation measures, even with about nine times higher computational efficiency, as well as fine boundary adherence and strong point targets preservation, compared with three state-of-the-art methods.
作为一种预处理技术，超像素分割算法应在快速分割速度、精确的边界贴合度和均匀的规则性方面表现出良好的性能。一种通过迭代边缘细化（IER）的快速超像素分割算法在光学图像上效果良好。然而，由于强斑点噪声以及许多小尺寸或细长区域的影响，它可能会为极化合成孔径雷达（PolSAR）图像生成质量较差的超像素。为了解决这些问题，我们在不稳定像素的局部重新标记中使用了快速修正的Wishart距离而非欧几里得距离，并将不稳定像素初始化为在初始化步骤中替代初始网格边缘像素的所有像素。然后，采用基于差异度量的后处理来去除生成的小孤立区域并保留强点目标。最后，通过对来自实验合成孔径雷达（ESAR）和机载合成孔径雷达（AirSAR）数据集的四幅模拟和两幅真实世界的PolSAR图像进行广泛实验，验证了所提算法的优越性，实验表明，与三种最先进的方法相比，所提方法在几种常用评估指标方面表现出更好的性能，甚至计算效率高出约九倍，同时具有良好的边界贴合度和强点目标保留能力。
