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 …

Pulse-coupled neural networks (PCNN) have an inherent ability to process the signals
associated with the digital visual images because it is inspired from the neuronal activity in …

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 …

Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and
parallel computing model, combining the spiking and coupled mechanisms of neurons. This …

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 plays an important role in the application of computer vision. In the
process of image fusion, there may be blurring and information loss, so it is our goal to …

Coupled neural P (CNP) systems are recently developed distributed and parallel computing
models that are abstracted by the mechanisms of coupled and spiking neurons. CNP …

The issue of visible light and infrared images fusion has been an active topic in both military
and civilian areas, and a great many relevant algorithms and techniques have been …

Dynamic threshold neural P systems (DTNP systems) are recently proposed distributed and
parallel computing models, inspired from the intersecting cortical model. DTNP systems …

In this paper, by considering the main objective of multi-focus image fusion and the physical
meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique …