Aiming to solve the misclassification problems of unsupervised polarimetric Wishart clas- sification algorithm based on Freeman decomposition, an unsupervised Polarimetric Synthetic Aper- ture Radar （SAR） Interferot...Aiming to solve the misclassification problems of unsupervised polarimetric Wishart clas- sification algorithm based on Freeman decomposition, an unsupervised Polarimetric Synthetic Aper- ture Radar （SAR） Interferotnery （PolInSAR） classification algorithm based on optimal coherence set parameters is studied and proposed. This algorithm uses the result of Freeman decomposition to divide the image into three basic categories including surface scattering, volume scattering, and double-bounce Then, the PolInSAR optimal coherence set parameters are used to finely divide each of the three basic categories into 9 categories, and the whole image is divided into 27 categories. Because both the Freeman decomposition result and optimal coherence set parameters indicate specific scattering characteristics, the whole image is merged into 16 categories based on physical meaning. At last, the Wishart cluster is employed to obtain the final classification result. To preserve the purity of scattering characteristics, pixels with similar scattering characteristics are restricted to be classified with other pixels. The final classification results effectively resolve the misclassification problem, not only the buildings can be effectively distinguished from vegetation in urban areas, but also the road is well distinguished from grass. In this paper, the E-SAR PolInSAR data of German Aerospace Center （DLR） are used to verify the effectiveness of the algorithm.展开更多
In this paper, we conduct survey and research on the innovativeness and characteristic of digital media under the environment of Internet and big data. Under the background of the era of rapid change, the current educ...In this paper, we conduct survey and research on the innovativeness and characteristic of digital media under the environment of Internet and big data. Under the background of the era of rapid change, the current education system is more severe impact and challenge. Creative industry is the product of cultural industry development to a new stage, is the most creative cultural industry and the origin of the core part of the new economic era of creativity industry is the condition of globalization. The research indicates that the combination of the big data with digital media is necessary and needed. In the future, we will test more related combination and creativeness.展开更多
文摘Aiming to solve the misclassification problems of unsupervised polarimetric Wishart clas- sification algorithm based on Freeman decomposition, an unsupervised Polarimetric Synthetic Aper- ture Radar （SAR） Interferotnery （PolInSAR） classification algorithm based on optimal coherence set parameters is studied and proposed. This algorithm uses the result of Freeman decomposition to divide the image into three basic categories including surface scattering, volume scattering, and double-bounce Then, the PolInSAR optimal coherence set parameters are used to finely divide each of the three basic categories into 9 categories, and the whole image is divided into 27 categories. Because both the Freeman decomposition result and optimal coherence set parameters indicate specific scattering characteristics, the whole image is merged into 16 categories based on physical meaning. At last, the Wishart cluster is employed to obtain the final classification result. To preserve the purity of scattering characteristics, pixels with similar scattering characteristics are restricted to be classified with other pixels. The final classification results effectively resolve the misclassification problem, not only the buildings can be effectively distinguished from vegetation in urban areas, but also the road is well distinguished from grass. In this paper, the E-SAR PolInSAR data of German Aerospace Center （DLR） are used to verify the effectiveness of the algorithm.
文摘In this paper, we conduct survey and research on the innovativeness and characteristic of digital media under the environment of Internet and big data. Under the background of the era of rapid change, the current education system is more severe impact and challenge. Creative industry is the product of cultural industry development to a new stage, is the most creative cultural industry and the origin of the core part of the new economic era of creativity industry is the condition of globalization. The research indicates that the combination of the big data with digital media is necessary and needed. In the future, we will test more related combination and creativeness.
