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A nonlinear image restoration framework using vector quantization

Vector quantization (VQ) is a powerful method used primarily in signal and image compression. In recent years, it has also been applied to other various image processing tasks, including image classification, histogram modification, and restoration. In this paper, we focus our attention on image restoration using VQ. We present a general framework that incorporates two other methods in the literature, and discuss our method that follows more naturally from this framework. With appropriate training data for the VQ codebook, this method can restore images beyond its diffraction limit.