Multi-focus image fusion (MFIF) is an important area in image processing. Since 2017, deep
learning has been introduced to the field of MFIF and various methods have been proposed …

In this study, we present new deep learning (DL) method for fusing multi-focus images.
Current multi-focus image fusion (MFIF) approaches based on DL methods mainly treat …

Multi-focus image fusion (MFF) is a fundamental task in the field of computational
photography. Current methods have achieved significant performance improvement. It is …

Multifocus image fusion is an important technique that aims to generate a single clean
image by fusing multiple input images. In this paper, we propose a novel multilevel features …

In this paper, we propose a novel unsupervised model for multi-focus image fusion based on
gradients and connected regions, termed as GCF. To overcome the stumbling block of …

Traditional and deep learning-based fusion methods generated the intermediate decision
map to obtain the fusion image through a series of postprocessing procedures. However, the …

This paper proposes a pixel-wise convolutional neural network (p-CNN) that can recognize
the focused and defocused pixels in source images from its neighbourhood information for …

Abstract The Convolutional Neural Networks (CNNs) based multi-focus image fusion
methods have recently attracted enormous attention. They greatly enhanced the constructed …

In this paper, a novel deep network is proposed for multi-focus image fusion, named Deep
Regression Pair Learning (DRPL). In contrast to existing deep fusion methods which divide …

To realize the multi-focus image fusion task, an end-to-end deep convolutional neural
network (DCNN) model that produces the final fused image directly from the source images …