A PolSAR Classification Method Based on Scattering Model and Polarization Correlation Coefficient
Recently,many PolSAR image classification methods have been proposed.One commonly used method is based on the scattering model.However,traditional classification based on scattering model usually overestimates the volume scattering contributions,especially in urban areas,resulting in buildings not orthogonal to radar Line-Of-Sight(LOS)misjudged as forests.To solve this problem,an improved PolSAR classification method based on scattering model and polarization correlation coefficient is presented in this paper.By introducing two types of polarization correlation coefficients,circular-pol correlation coefficient(CCC)and normalized circular-pol correlation coefficient(NCCC),the oriented buildings can be effectively extracted from the volume scattering.Since the amplitude values of CCC of forests are very small,while that of buildings orthogonal to radar LOS or with small orientation angles are close to 1.There-fore,the CCC parameter is firstly used to extract some slightly tilted oriented buildings form the initial volume scattering category.Then,the NCCC parameter is introduced to distinguish the buildings with large orientation angles from the remainder volume scattering components.Since these buildings hold strong non-reflection symmetry and larger orientation angles,the values of NCCC of this kind are much larger than that of forests.Finally,the extracted buildings are reclassified into a new oriented buildings category.In order to maintain the dominant scattering mechanism characteristics,the classification method preserving scattering characteristics is utilized to classify the corrected scattering categories.The proposed classification algorithm remedies the defect of traditional scattering-model-based classification method and the experiment result of an E-SAR L-band PolSAR image of Oberpfaffenhofen,Germany demonstrates the effectiveness of the proposed method.
Jianbo Wang Chao Wang Hong Zhang Fan Wu Bo Zhang
Key Laboratory of Digital Earth Sciences Institute of Remote Sensing and Digital Earth,CAS,Beijing 1 Key Laboratory of Digital Earth Sciences Institute of Remote Sensing and Digital Earth,CAS,Beijing 1
国际会议
Progress in Electromagnetics Research Symposium 2014(2014年电磁学研究新进展学术研讨会)
广州
英文
1420-1424
2014-08-01（万方平台首次上网日期，不代表论文的发表时间）