测绘学报 ›› 2014, Vol. 43 ›› Issue (3): 263-267.

• 学术论文 • 上一篇    下一篇

雷达干涉测量图像的梯度自适应光滑子函数滤波法

付政庆1,刘国林2,陶秋香1,刘伟科3   

  1. 1. 山东科技大学
    2. 山东科技大学测绘科学与工程学院
    3. 山东科技大学 测绘学院
  • 收稿日期:2012-11-26 修回日期:2013-06-07 出版日期:2014-03-20 发布日期:2014-04-01
  • 通讯作者: 付政庆 E-mail:fzhqing@163.com
  • 基金资助:

    国家自然基金;山东省自然基金

APPLICATION OF ADAPTIVE SMOOTHING FUNCTION FILTERING BASEED ON GRADIENT IN InSAR IMAGE

  • Received:2012-11-26 Revised:2013-06-07 Online:2014-03-20 Published:2014-04-01

摘要:

提出了基于梯度的自适应光滑子函数滤波的新方法。对于干涉图中的点,通过梯度分为噪声点和非噪声点。在噪声点处,将包含噪声点的InSAR图像窗口拟合为二次曲面,然后用光滑子函数对拟合曲面进行平滑去噪处理,非噪声点处不进行平滑处理。通过这种方法有效抑制了斑点噪声,又同时做到使干涉图相位偏差较少和较好地保留了边缘信息。利用北京地区的真实ALOS数据进行滤波试验,并与几种常用的滤波方法进行比较和分析。通过均方根误差、峰值信噪比、边缘保持指数和标准相位偏差等量化指标,验证了基于梯度的自适应光滑子函数滤波方法的可行性与有效性。

关键词: InSAR, 自适应, 光滑子函数, 滤波, 斑点噪声

Abstract:

A new filtering algorithm smoothing function based on gradient was proposed. Based on gradient, noise points are identified. This algorithm is based on the spatial curved surface fitting, and then the surface is processed through smoothing function. The good pixels are unsmooth. The results of experiment, using the data which come from ALOS data of Beijing, show that the smoothing function filer has effectiveness and feasibility. The RMS (Root mean square error), PSNR (Peak signal-to-noise ratio), EPI(Edge preserve index) and PSD (Phase standard deviation) suggest that the algorithm can reduce the speckle noise and keep the edge information.

Key words: InSAR, adaptive, smoothing function, filter, speckle