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Partition-Based Weighted Sum Filters For Image Restoration, Kenneth Barner, Ahmad Sarhan, Russell Hardie

Russell C. Hardie

We develop the concept of partitioning the observation space to build a general class of filters referred to as partition-based weighted sum (PWS) filters. In the general framework, each observation vector is mapped to one of M partitions comprising the observation space, and each partition has an associatedfiltering function. We focus on partitioning the observation space utilizing vector quantization and restrict the filtering function within each partition to be linear. In this formulation, a weighted sum of the observation samples forms the estimate, where the weights are allowed to be unique within eachpartition. The partitions are selected and weights tuned …