基于Shannon-cosine小波的农田遥感图像纹理延拓

Texture Extension Method for Farmland Remote Sensing Image Based on Shannon-cosine Wavelet

农田遥感图像一般都是大图像,对这种大图像进行后续的分析,分块处理是较常见的方法,而在进行分块处理的时候易产生边界效应。消除边界效应最常用的方法是进行图像延拓,常见的延拓方法有对称延拓、零延拓和周期延拓,但在边界处会引入大量高频信息。农田遥感图像中的纹理承载了重要的信息,因此,结合农田遥感图像纹理呈现出的直线特性,本文提出了一种基于纹理方向的图像延拓法。利用多尺度插值小波解偏微分方程的方法根据图像的灰度变化自适应选取配置点,即在图像平坦区域稀疏取点,在纹理细节处密集取点。然后根据配点利用包围盒识别农田遥感图像的纹理方向,进一步沿纹理方向进行延拓。试验结果表明,本文提出的图像延拓方法有效地克服了常规延拓方法的缺点,提高了计算效率,消除了边界效应。

Remote sensing images are generally large images.For the subsequent analysis of this kind of image,there is a common method of dividing image into blocks,while the boundary effect is easy to occur in block processing.Therefore,the elimination of boundary effects is a problem that needs to be studied in block processing.The most common way to eliminate the boundary effects is to extend the image.Symmetry extension,zero extension and periodic extension are the common extension methods.The conventional extension method is not applicable because texture in farm remote sensing images carries important information.Thus,according to the line characteristics shown on remote sensing images,a new extension method based on texture orientation was proposed in this paper.Here,we used the method of multi-scale interpolation wavelet to solve the partial differential equation,according to the change of gray level of the image.In this method,external collocation points were chosen adaptively.Thus the computational efficiency could be greatly improved.Then,the texture direction of farm remote sensing images was identified by using bounding boxes,and the texture is further extended along the texture direction.Experimental results show that the image extension method proposed effectively overcomes the shortcomings of the conventional extension method,greatly improve the efficiency of calculation and the boundary effect is effectively eliminated.