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Mallet and Zhong [1992] have derived some elegant results on 1-D and 2-D wavelet transforms. The objective here is to extend the 2-D results of Mallet and Zhong to 3-D. Illustrated here is how these results can be applied to the feature analysis of 2-D images with time t as the third dimension. An algorithm for extending 2-D to 3-D wavelets is presented  相似文献   
2.
Clutter plays a very important role in the area of machine and human-in-the-loop target acquisition. A great deal of interest has recently been shown in assessing several different definitions of clutter. In spite of so many definitions available, no single clutter definition has been agreed on by the target acquisition modeling community as being the best. Here we develop a new clutter metric, called relative clutter, based on factor analysis which is extensively used for statistical analysis. This relative clutter combines many definitions of clutter. Different methods for calculating the relative clutter based on the magnitude of the eigenvalues obtained from the correlation matrix are suggested. The relative clutter of many images is analyzed. The relative clutter is used to calculate probability of detection on Night Vision Lab (NVL) Terrain Board Infrared images  相似文献   
3.
Clutter plays a very important role in the area of machine and human-in-the-loop target acquisition. A great deal of interest has recently been shown in assessing several different definitions of clutter. In spite of so many definitions available, no single clutter definition has been agreed on by the infrared community as being the best. We develop a new clutter metric, called relative clutter, which is based on factor analysis which is extensively used for statistical analysis. This relative clutter combines many definitions of clutter. Different methods for calculating the relative clutter based on the magnitude of the eigenvalues obtained from the correlation matrix are suggested. The relative clutter of many images is analyzed  相似文献   
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