By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …

Pixel-level image fusion is designed to combine multiple input images into a fused image,
which is expected to be more informative for human or machine perception as compared to …

The recent years have been marked by continuous improvements of remote sensors with
applications like monitoring and management of the environment, precision agriculture …

This article addresses the problem of remote sensing image pan-sharpening from the
perspective of generative adversarial learning. We propose a novel deep neural network …

Remote sensing image fusion (also known as pan-sharpening) aims at generating a high
resolution multi-spectral (MS) image from inputs of a high spatial resolution single band …

Modality is a source or form of information. Through various modal information, humans can
perceive the world from multiple perspectives. Simultaneously, the observation of remote …

The field of multimodal medical image fusion has made huge progress in the past decade.
However, previous methods always suffer from color distortion, blurring, and noise. To …

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion.
To better preserve the significant information of the infrared and visible images in the final …

Image fusion is a well-recognized and a conventional field of image processing. Image
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …

This paper presents a deep learning-based pansharpening method for fusion of
panchromatic and multispectral images in remote sensing applications. This method can be …