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 …

Dynamic threshold neural P systems (DTNP systems) are a distributed parallel computing
model with an interesting mechanism involving the cooperative spiking of neurons in a local …

Image fusion is a long-established and well-known study area of digital image processing.
The reason is its substantial approach in several practical applications in which multi-focus …

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 …

In this paper, an end-to-end multi-focus fusion network is proposed to solve the mis-
registration problem of the captured images. This paper takes the shaking and camera …

Multi-focus image fusion techniques are designed to integrate the focused regions of
multiple source images to produce an all-in-focus image. Unfortunately, the fusion results …

This paper presents a novel approach to addressing the fusion of multi-focus images in
either registered or mis-registered cases. The conventional approaches often produce …

Multi-focus image fusion (MFIF) aims to utilize multiple images with different focal lengths to
fuse into a single full-focus image. This process enhances the realism and clarity of the …

This paper develops a simple and effective multi-focus image fusion method based on local
standard deviations of the corresponding Laplacian images of source images and further …

Image-based 3D reconstruction or 3D photogrammetry of small-scale objects including
insects and biological specimens is challenging due to the use of a high magnification lens …