Synthetic aperture radar （SAR） is an effective tool to analyze the features of the ocean. In this paper, the microcanon- ical multifractal formalism is used to analyze SAR images to obtain meso-micro scale surface f...Synthetic aperture radar （SAR） is an effective tool to analyze the features of the ocean. In this paper, the microcanon- ical multifractal formalism is used to analyze SAR images to obtain meso-micro scale surface features. We use the Sobel operator to calculate the gradient of each point in the image, then operate continuous variable scale wavelet transform on this gradient matrix. The relationship between the wavelet coefficient and scale is built by linear regression. This relation- ship decides the singular exponents of every point in the image which contain local and global features. The manifolds in the ocean can be revealed by analyzing these exponents. The most singular manifold, which is related to the streamlines in the SAR images, can be obtained with a suitable threshold of the singular exponents. Experiments verify that application of the microcanonical multifractal formalism to SAR image analysis is effective for detecting the meso-micro scale surface information.展开更多
基金Project supported by the National Key R&D Program of China(Grant No.2016YFC1401007)the Global Change Research Program of China(Grant No.2015CB953901)+3 种基金the National Natural Science Foundation of China(Grant No.41776181)the Canadian Program on Energy Research and Development(OERD)Canadian Space Agency’s SWOT Programthe Canadian Marine Environmental Observation Prediction and Response Network(MEOPAR)
文摘Synthetic aperture radar （SAR） is an effective tool to analyze the features of the ocean. In this paper, the microcanon- ical multifractal formalism is used to analyze SAR images to obtain meso-micro scale surface features. We use the Sobel operator to calculate the gradient of each point in the image, then operate continuous variable scale wavelet transform on this gradient matrix. The relationship between the wavelet coefficient and scale is built by linear regression. This relation- ship decides the singular exponents of every point in the image which contain local and global features. The manifolds in the ocean can be revealed by analyzing these exponents. The most singular manifold, which is related to the streamlines in the SAR images, can be obtained with a suitable threshold of the singular exponents. Experiments verify that application of the microcanonical multifractal formalism to SAR image analysis is effective for detecting the meso-micro scale surface information.
