This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

The necessity of image fusion is growing in recently in image processing applications due to
the tremendous amount of acquisition systems. Fusion of images is defined as an alignment …

Deep learning technology has been extensively explored in pattern recognition and image
processing areas. A multi-mode medical image fusion with deep learning will be proposed …

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 …

The images captured by the cameras contain distortions, misclassified pixels, uncertainties
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input …

Multi-modality is widely used in medical imaging, because it can provide multiinformation
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …

In this paper, we propose a fast unified image fusion network based on proportional
maintenance of gradient and intensity (PMGI), which can end-to-end realize a variety of …

Image fusion integrates a series of images acquired from different sensors, eg, infrared and
visible, outputting an image with richer information than either one. Traditional and recent …

Multimodal medical image fusion consists in combining two or more images of the same or
different modalities aiming to improve the image content, and preserve information. The …

Pan-sharpening in remote sensing image fusion refers to obtaining multi-spectral images of
high-resolution by fusing panchromatic images and multi-spectral images of low-resolution …