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Dynamic Spatial Predicted Background
IEEE Transactions on Image Processing, 2020We present a novel method for online background modeling for static video cameras - Dynamic Spatial Predicted Background (DSPB). Our unique method employs a small subset of image pixels to predict the whole scene by exploiting pixel correlations (distant and close).
Yaniv Tocker +2 more
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On spatial smoothing and linear prediction
International Conference on Acoustics, Speech, and Signal Processing, 2002The relationship between Cadzow's signal subspace algorithm and the spatially smoothed minimum-norm algorithm of Tufts-Kumaresan is investigated. It is shown that Cadzow's algorithm can be realized by subarray averaging lower rank approximations to the array covariance matrix.
Hamid Krim +2 more
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PREDICTING SPATIAL DATA WITH RBF NETWORKS
International Journal of Neural Systems, 2004Spatial prediction needs to account for spatial information, which makes conventional radial basis function (RBF) networks inappropriate, for they assume independent and identical distribution. In this paper, we fuse spatial information at different layers of RBF.
Hu, T., Sung, S.Y.
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Environmental and Ecological Statistics, 1999
This paper presents a complete Bayesian methodology for analyzing spatial data, one which employs proper priors and features diagnostic methods in the Bayesian spatial setting. The spatial covariance structure is modeled using a rich class of covariance functions for Gaussian random fields.
Marie Gaudard +3 more
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This paper presents a complete Bayesian methodology for analyzing spatial data, one which employs proper priors and features diagnostic methods in the Bayesian spatial setting. The spatial covariance structure is modeled using a rich class of covariance functions for Gaussian random fields.
Marie Gaudard +3 more
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Spatial Prediction Models for Mining Spatial Data
2007 IEEE International Conference on Integration Technology, 2007The multivariate linear regression (MLS) model is a very good technique for non-spatial prediction. But spatial prediction needs to account for spatial information, which makes the MLS model inappropriate, for it assume that the learning samples are independently and identically distributed(i.i.d).
Caiping Hu, Xiaolin Qin, Jun Zhang
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Spatial prediction in the presence of left-censoring
Computational Statistics & Data Analysis, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lina Schelin, Sara Sjöstedt de Luna
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2020
This chapter begins with linear extensions of kriging that provide higher flexibility and allow relaxing the underlying assumptions on the method. Such generalizations include the application of ordinary kriging to intrinsic random fields that can handle non-stationary data, as well as the methods of regression kriging and universal kriging that ...
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This chapter begins with linear extensions of kriging that provide higher flexibility and allow relaxing the underlying assumptions on the method. Such generalizations include the application of ordinary kriging to intrinsic random fields that can handle non-stationary data, as well as the methods of regression kriging and universal kriging that ...
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Spatial-temporal prediction of algal bloom
2013 Ninth International Conference on Natural Computation (ICNC), 2013We present an application of spatial-temporal prediction to track algal blooms. Algal bloom is an important water quality events in marine, coastal and estuarine environments. For a day, we first identify an area with anomalous algal growth represented by spatial points in the gridded data where values of Chlorophyll-a (indicator for algal bloom) are ...
Md. Sumon Shahriar, Ashfaqur Rahman
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Image compression using spatial prediction
1995 International Conference on Acoustics, Speech, and Signal Processing, 2002This paper describes a new image compression technique, referred to as spatial prediction. Spatial prediction works in a manner similar to fractal-based image compression techniques, and is in fact a result of several experiments that we conducted to gain a better understanding of why fractal compression works. Spatial prediction compresses an image by
Ephraim Feig +2 more
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Adaptive spatial prediction in intra coding
Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010In this paper, a novel spatial prediction method is proposed to improve prediction accuracy and capture the dynamics of different video contents. The method adaptively generates optimized spatial prediction modes according to the local feature of coded image.
Yu Chen, Lu Yu
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