Anisotropic Diffusion for Details Enhancement in Multi-Exposure Image Fusion
This is an incremental improvement for image processing applications, addressing detail preservation in multi-exposure fusion without requiring HDR generation.
The authors tackled the problem of enhancing details in multi-exposure image fusion by developing a method based on texture features and anisotropic diffusion, which skips complex HDR generation steps to produce well-exposed fused images for standard displays, with effectiveness demonstrated for flash/no-flash and multifocus images.
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.