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 …

In this letter, a sparse representation (SR) model named convolutional sparsity based
morphological component analysis (CS-MCA) is introduced for pixel-level medical image …

Multi-focus image fusion (MFF) is an effective way to eliminate the out-of-focus blur
generated in the imaging process. The difficulties in distinguishing different blur levels and …

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 …

Multi-focus image fusion methods can be mainly divided into two categories: transform
domain methods and spatial domain methods. Recent emerged deep learning (DL)-based …

This paper proposes an effective infrared and visible image fusion method based on a
texture conditional generative adversarial network (TC-GAN). The constructed TC-GAN …

Abstract Multi-Focus Image Fusion (MFIF) is a method that combines two or more source
images to obtain a single image which is focused, has improved quality and more …

Multi-focus image fusion (MFIF) attempts to achieve an “all-focused” image from multiple
source images with the same scene but different focused objects. Given the lack of multi …

In this paper, a novel self-supervised mask-optimization model, termed as SMFuse, is
proposed for multi-focus image fusion. In our model, given two source images, a fully end-to …

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 …