The integration of optical and SAR datasets through ensemble machine learning models
shows promising results in urban remote sensing applications. The integration of multi …

In this paper, a multi-focus image fusion algorithm via the distance-weighted regional energy
and structure tensor in non-subsampled contourlet transform domain is introduced. The …

Infrared and visible image fusion represents a significant segment within the image fusion
domain. The recent surge in image processing hardware advancements, including GPUs …

Infrared and visible images of the same scene are fused to produce a fused image with
richer information. However, most current image-fusion algorithms suffer from insufficient …

Multi-modal image fusion can provide more image information, which improves the image
quality for subsequent image processing tasks. Because the images acquired using photon …

Burning agricultural straw after reaping is a typical farming approach for quicker crop
rotation but compromises the sustainability of cultivation practices. Unmanned aerial vehicle …

Multi-focus image fusion (MFIF) aims to break the limitations of physical devices and
integrate different focused regions from multiple source images into a single fully focused …

This paper proposes an efficient algorithm for edge-preserving filtering with multiple
guidance images, so-called multilateral filtering. Multimodal signal processing for sensor …

The realm of medical imaging is a critical frontier in precision diagnostics, where the clarity
of the image is paramount. Despite advancements in imaging technology, noise remains a …

The rapid development of deep neural networks has attracted significant attention in the
infrared and visible image fusion field. However, most existing fusion models have many …