Evaluation and Comparison of Edge-Preserving Filters

TL;DR

This paper introduces a systematic methodology for evaluating and comparing edge-preserving filters, providing a common baseline and guidelines to improve understanding and unbiased assessment of these operators in computational photography.

Contribution

It presents a novel evaluation framework, a baseline for comparison, and parameter mapping methods for diverse edge-preserving filters, addressing current methodological gaps.

Findings

Established a comprehensive evaluation methodology

Created a baseline for fair comparison of filters

Provided guidelines for objective assessment

Abstract

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.