不同极化方式SAR与TM融合影像滨海湿地分类精度比较

Comparison of coastal wetland classification accuracy using fused images of different-polarization SAR and TM images

以覆盖黄河口湿地区域的Radarsat-2SAR全极化影像和Landsat-5TM影像为例,将4种极化方式的SAR影像与TM影像分别进行融合,采用支持向量机对融合结果进行滨海湿地典型地物土地覆盖分类,并对分类结果进行比较评价,分析不同极化方式的SAR影像与TM影像融合结果在滨海湿地地区的分类能力。实验结果表明:采用与SAR影像融合的方法能够提高TM影像的分类精度,其中HV极化方式的SAR影像与TM影像的融合结果分类精度最高,最适用于滨海湿地土地覆盖分类研究。

The supported vector machine was adopted on the coastal wetland land cover classification using fused images of 4-polarization SAR and TM images, the results of classification were compared and evaluated to analyze the capability of different-polarization SAR and TM fused images in coastal wetland area. An area of Yellow River Delta was selected as the experimental area, and a Radarsat-2 full-polarization image and a Landsat-5 TM image were taken as an example. The results of the experiment were analyzed quantitatively, which show that the classification accuracy of the original TM image can be improved by using the SAR- image-fusion method, the classification accuracy of the image fused by the HV-polarization SAR and TM image is the highest, so that the HV polarization is the most suitable polarization of SAR image for fusion and classification research work in coastal wetland area.