Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly a...Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly accurate, reliable and low computation cost in image registration a suitable and similarity metric and reduction in search data and search space is required. In this paper, the author shows that if the right bin size is chosen, mutual information can be more robust than correlation in the registration of multi-temporal images. The author also compares the sensitivity of mutual information and correlation to Gaussian and multiplicative speckle noise. The author investigates automatic subimage selection as a reduction in search data strategy. The author proposes a measure, called alienability, which shows the ability ofa subimage to provide reliable registration. Alternate subimage selection methods such as using gradient, entropy and variance are also investigated. The author furthermore looks into a search space strategy using a gradient approach to maximize mutual information and show our first results.展开更多
文摘Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly accurate, reliable and low computation cost in image registration a suitable and similarity metric and reduction in search data and search space is required. In this paper, the author shows that if the right bin size is chosen, mutual information can be more robust than correlation in the registration of multi-temporal images. The author also compares the sensitivity of mutual information and correlation to Gaussian and multiplicative speckle noise. The author investigates automatic subimage selection as a reduction in search data strategy. The author proposes a measure, called alienability, which shows the ability ofa subimage to provide reliable registration. Alternate subimage selection methods such as using gradient, entropy and variance are also investigated. The author furthermore looks into a search space strategy using a gradient approach to maximize mutual information and show our first results.
