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Superresolution is a process of extracting higher details. The main objective of this paper is the study of patch based method for super-resolving low resolution of a leaf diseased image. The domain specific prior is incorporated into superresolution by the means of learning patch based estimation of missing high frequency details from infected leaf image. Images are decomposed into fixed size patches in order to deal with time and space complexity. The problem is modeled by Markov Random Fielddoi:10.7753/ijcatr0305.1009 fatcat:ecvotuf5avf45g6b7cknkarwky