Multimodal medical image fusion consists in combining two or more images of the same or
different modalities aiming to improve the image content, and preserve information. The …

Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …

At the crossing of the statistical and functional analysis, there exists a relentless quest for an
efficient image denoising algorithm. In terms of greyscale imaging, a plethora of denoising …

As an effective way to integrate the information contained in multiple medical images with
different modalities, medical image fusion has emerged as a powerful technique in various …

In image-based medical decision-making, different modalities of medical images of a given
organ of a patient are captured. Each of these images will represent a modality that will …

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 …

The fast-developing Image fusion technique has become a necessary one in every field.
Analyzing the efficiency of various fusion technologies analytically and objectively are …

CT imaging is widely used in medical science over the last decades. The process of CT
image reconstruction depends on many physical measurements such as radiation dose …

A large number of imaging problems reduce to the optimization of a cost function, with
typical structural properties. The aim of this paper is to describe the state of the art in …

In the last decade, advances and popularity of low-cost RGB-D sensors have enabled us to
acquire depth information of objects. Consequently, researchers began to solve face …