Indexed by:Journal Article

Date of Publication:2013-01-01

Journal:IEEE TRANSACTIONS ON IMAGE PROCESSING

Included Journals:Scopus、PubMed、EI、SCIE

Volume:22

Issue:1

Page Number:80-90

ISSN:1057-7149

Key Words:Edge-preserving image filtering; high dynamic range (HDR) compression; local linear model; Stein's unbiased risk estimate (SURE)

Abstract:In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.