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Multiple Information Principle (MIP) is reviewed as a method of assigning a prior probability mass of density function to a random variable in the presence of some prior information. It is compared to the Maximum Information (MI) method and shown to be more general and inclusive of prior data available to the investigator. The image restoration problem is outlined as an inverse source problem with insufficient data for yielding a unique solution.

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