VQ based Bayesian image filtering
Manuel Graña, Imanol Echave, Jesús Ruı́z-Cabello · 2000
In this paper we propose the application of vector quantizers computed over an image for its own filtering. Each pixel processing is conditioned to its neighborhood and the neighborhood's closest code vector. The code vectors play the role of conditional context in a Bayesian image processing framework. The approach is applied to high resolution MRI. The visual results show that this approach produces image smoothing with good edge preservation, although no edge model is introduced.