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 …

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 …

In this paper, we propose a general image fusion framework based on the convolutional
neural network, named as IFCNN. Inspired by the transform-domain image fusion …

Multi-focus image fusion aims to extract the focused regions from multiple partially focused
images of the same scene and then combine them together to produce a completely focused …

The ideal fusion of the infrared image and visual image should integrate the important bright
features of the infrared image, and preserve much original visual information of the visual …

The purpose of multi-focus image fusion is integrating the partially focused images into one
single image which is focused everywhere. To achieve this purpose, we propose a new …

Multi-focus image fusion technology is to extract different focused regions of the same scene
among partially focused images and merge them together to generate a composite image …

Multi-focus image fusion combines the focused parts of multiple images of the same scene
to generate a fully focused image. Dual Channel Pulse coupled neural network (DCPCNN) …

Medical image fusion techniques have been extensively used in clinical diagnosis. Scaling
based techniques are well known techniques in multimodal image fusion, the generalized …

Image fusion enhances a single image by integrating information from multiple sources with
complementary data. Present end-to-end fusion methods often face overfitting or intricate …