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Following the presentation and proof of the hypothesis that image featuresare particularly perceived at points where the Fourier components are maximallyin phase, the concept of phase congruency (PC) is introduced. Subsequently, atwo-dimensional multi-scale phase congruency (2D-MSPC) is developed, which hasbeen an important tool for detecting and evaluation of image features. However,the 2D-MSPC requires many parameters to be appropriately tuned for optimalimage features detection. In this paper, we defined a criterion for parameteroptimization of the 2D-MSPC, which is a function of its maximum and minimummoments. We formulated the problem in various optimal and suboptimalframeworks, and discussed the conditions and features of the suboptimalsolutions. The effectiveness of the proposed method was verified throughseveral examples, ranging from natural objects to medical images from patientswith a neurological disease, multiple sclerosis.

Phase Congruency Parameter Optimization for Enhanced Detection of Image Features for both Natural and Medical Applications