Anisotropic Diffusion for Details Enhancement in Multi-Exposure Image Fusion

TL;DR

This paper introduces a multiexposure image fusion method using anisotropic diffusion based on PDEs, which preserves details and textures without HDRI processing, suitable for standard displays and various image blending tasks.

Contribution

The proposed technique leverages texture features and anisotropic diffusion for detail-preserving image fusion, bypassing complex HDRI steps and applicable to flash/no-flash and multifocus images.

Findings

Effective detail preservation in fused images.

Avoids complex HDRI and tone mapping processes.

Versatile for different image fusion scenarios.

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.