The paper proposes a new method that combines the decorrelation and shrinkage techniques to neural network-based approaches\nfor noise removal purposes.Theimages are represented as sequences of equal sized blocks, each block being distorted by a stationary\nstatistical correlated noise. Some significant amount of the induced noise in the blocks is removed in a preprocessing step, using a\ndecorrelation method combined with a standard shrinkage-based technique.The preprocessing step provides for each initial image\na sequence of blocks that are further compressed at a certain rate, each component of the resulting sequence being supplied as inputs\nto a feed-forward neural architecture
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