Table of Contents
ISRN Signal Processing
Volume 2013, Article ID 928971, 18 pages
http://dx.doi.org/10.1155/2013/928971
Research Article

Anisotropic Diffusion for Details Enhancement in Multiexposure Image Fusion

1Baddi University of Emerging Sciences and Technology, Baddi, Solan 173205, India
2Grupo de Procesado Multimedia, Departamento de Teoría de la Señal y Comunicaciones, Universidad Carlos III de Madrid, Leganés, 28911 Madrid, Spain
3Jaypee University of Information Technology, Waknaghat, Solan 173215, India

Received 21 February 2013; Accepted 25 March 2013

Academic Editors: Y.-S. Chen, A. Ito, C. S. Lin, and J.-G. Wang

Copyright © 2013 Harbinder Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We develop a multiexposure image fusion method based on texture features, which exploits the edge preserving and intraregion smoothing property of nonlinear diffusion filters based on partial differential equations (PDE). With the captured multiexposure image series, we first decompose images into base layers and detail layers to extract sharp details and fine details, respectively. The magnitude of the gradient of the image intensity is utilized to encourage smoothness at homogeneous regions in preference to inhomogeneous regions. Then, we have considered texture features of the base layer to generate a mask (i.e., decision mask) that guides the fusion of base layers in multiresolution fashion. Finally, well-exposed fused image is obtained that combines fused base layer and the detail layers at each scale across all the input exposures. Proposed algorithm skipping complex High Dynamic Range Image (HDRI) generation and tone mapping steps to produce detail preserving image for display on standard dynamic range display devices. Moreover, our technique is effective for blending flash/no-flash image pair and multifocus images, that is, images focused on different targets.