Evaluation and Comparison of Edge-Preserving Filters
This work provides a standardized evaluation methodology for researchers and practitioners working with edge-preserving filters, helping to mitigate misunderstanding and misuse of these methods.
This paper addresses the lack of a systematic methodology for evaluating and comparing edge-preserving filters, which are crucial in computational photography tasks. It introduces a new evaluation framework and demonstrates it on various published filters, establishing a common baseline for comparison and determining equivalent parameter mappings between methods.
Edge-preserving filters play an essential role in some of the most basic tasks of computational photography, such as abstraction, tonemapping, detail enhancement and texture removal, to name a few. The abundance and diversity of smoothing operators, accompanied by a lack of methodology to evaluate output quality and/or perform an unbiased comparison between them, could lead to misunderstanding and potential misuse of such methods. This paper introduces a systematic methodology for evaluating and comparing such operators and demonstrates it on a diverse set of published edge-preserving filters. Additionally, we present a common baseline along which a comparison of different operators can be achieved and use it to determine equivalent parameter mappings between methods. Finally, we suggest some guidelines for objective comparison and evaluation of edge-preserving filters.