SpringerOpen Newsletter

Receive periodic news and updates relating to SpringerOpen.

Open Access Open Badges Research

Robust flash denoising/deblurring by iterative guided filtering

Hae-Jong Seo1* and Peyman Milanfar2

Author Affiliations

1 Sharp Labs of America, Camas, WA 98683, USA

2 University of California-Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA

For all author emails, please log on.

EURASIP Journal on Advances in Signal Processing 2012, 2012:3  doi:10.1186/1687-6180-2012-3

Published: 6 January 2012


A practical problem addressed recently in computational photography is that of producing a good picture of a poorly lit scene. The consensus approach for solving this problem involves capturing two images and merging them. In particular, using a flash produces one (typically high signal-to-noise ratio [SNR]) image and turning off the flash produces a second (typically low SNR) image. In this article, we present a novel approach for merging two such images. Our method is a generalization of the guided filter approach of He et al., significantly improving its performance. In particular, we analyze the spectral behavior of the guided filter kernel using a matrix formulation, and introduce a novel iterative application of the guided filter. These iterations consist of two parts: a nonlinear anisotropic diffusion of the noisier image, and a nonlinear reaction-diffusion (residual) iteration of the less noisy one. The results of these two processes are combined in an unsupervised manner. We demonstrate that the proposed approach outperforms state-of-the-art methods for both flash/no-flash denoising, and deblurring.