The same sensor or a number of image sensors are used to take a series of photographs in
order to gather as much data as possible about the scene. Several imaging techniques are …

Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

Image fusion is capable of processing multiple heterogeneous images acquired by single or
multi-sensor imaging systems for an improved interpretation of the targeted object or scene …

Image fusion is a process that integrates similar types of images collected from
heterogeneous sources into one image in which the information is more definite and certain …

Image fusion is a well-recognized and a conventional field of image processing. Image
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …

Pixel-level image fusion has been applied in a variety of applications, including multi-modal
medical imaging, remote sensing, industrial inspection, video surveillance, and night vision …

Image fusion performance evaluation methods form an essential part in the development of
image fusion techniques. This chapter discusses various performance evaluation measures …

Image fusion has been a hot topic for many years, and it has been widely applied to fields
varying from robotics, medical engineering, and surveillance to military and many others …

Pixel-level image fusion is designed to combine multiple input images into a fused image,
which is expected to be more informative for human or machine perception as compared to …

Signal-level image fusion has been the focus of considerable research attention in recent
years with a plethora of algorithms proposed, using a host of image processing and …