Close-Form Solution and Parameter Selection for Convex Minimization-Based Edge-Preserving Smoothing

Authors:
Stan Z. Li
Affiliations:
-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1998

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Abstract

This work presents a new approach for the analysis of convex minimization-based edge-preserving image smoothing and the parameter selection therein. The global solution, that is, the response of a convex smoothing model to the ideal step edge, is derived in close-form. By analyzing the close-form solution, insights are drawn into how the optimal solution responds to edges in the data and how the parameter values affect resultant edges in the solution. Based on this, a scheme is proposed for selecting parameters to achieve desirable responses at edges. The theoretic results are substantiated by experiments.