CAJ | 학술논문

针对传统的极化SAR滤波方法图像中城镇区域和植被区域地物在滤波中易被混淆, 导致滤波后图像中地物边缘保持效果下降的问题, 提出了一种增强的保持极化散射特性的滤波算法。利用一种增强的四分量极化分解方法获取更加精确的地物散射机制, 并将散射机制信息引入滤波方法中, 使滤波算法中像素的散射机制更精确。增强的四分量极化分解方法引入了极化SAR数据的定向角补偿技术、一种新的体散射模型以及两种散射功率限制条件, 来改进Freeman-Durden分解的结果。理论分析和实验结果表明, 改进后的方法获取了比传统的极化SAR图像滤波算法更加理想的计算结果。
침대전통적겁화SAR려파방법도상중성진구역화식피구역지물재려파중역피혼효, 도치려파후도상중지물변연보지효과하강적문제, 제출료일충증강적보지겁화산사특성적려파산법。이용일충증강적사분량겁화분해방법획취경가정학적지물산사궤제, 병장산사궤제신식인입려파방법중, 사려파산법중상소적산사궤제경정학。증강적사분량겁화분해방법인입료겁화SAR수거적정향각보상기술、일충신적체산사모형이급량충산사공솔한제조건, 래개진Freeman-Durden분해적결과。이론분석화실험결과표명, 개진후적방법획취료비전통적겁화SAR도상려파산법경가이상적계산결과。
The conventional filtering algorithm tends to mix the urban areas with the vegetation areas for polarimetric SAR images. </sup>Therefore, the edges of the ground objects in the filtered images are usually not well reserved. To overcome this problem, this paper proposed an enhanced filtering algorithm that could reserve the polarimetric scattering mechanisms, and applied an improved</sup> four-component polarimetric decomposition. The proposed filter included the orientation angle compensation of the scattering matrix, a new volume scattering model, and two power constraints to deal with the previous problems. Experimental results indicate that the proposed algorithm have acquired a better filtering effect than the conventional one for polarimetric SAR images.