Application of spatial statistics for IR background suppression

Background suppression is an effective method for extracting the signal of target in infrared remote sensing image. Background clutter contains spatial information and is correlative in spatial domain. In spatial statistics the semivariogram is an important function that relates semivariance to sampling lag. This function can characterize the spatial dependence of each point on its neighbor and provide a concise and unbiased description of the scale and pattern of spatial variability. One of the main reasons for deriving semivariogram is to use it in the process of estimation. Kriging is an interpolation and estimation technique that considers both the distance and the degree of variation between known data points when estimating values in unknown areas. A kriged estimate is a weighted linear combination of the known sample values around the point to be estimated. In this paper a new algorithm based on spatial statistics is developed for IR background suppression. The main objective of the algorithms is to suppress background clutter through Kriging estimation. Theory analysis and experiments show that the method is reasonable and efficient.