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New Class 3 image processing algorithms are presented. They are direct extensions of previously published one-dimensional algorithms. Class 3 algorithms require almost no a priori information knowledge about the signal and noise that are being processed. Their performance depends upon the kind of smoothing used and on the images being processed by the filter. The previously published Class 3 filter algorithms require that the filter input be stationary, and that the noise spectrum have zero mean and be uncorrelated to the signal. For the new Class 3 image processing algorithms, the only additional assumption for the noise is that its spectrum be white. Simulations using Lena demonstrate much better performance using the new Class 3 algorithms over the standard Class 3 algorithms.