相关论文: J-comb: An image fusion algorithm to combine obser…
This paper proposes a novel spatiotemporal (ST) fusion framework for satellite images, named Robust Optimization-based Spatiotemporal Fusion (ROSTF). ST fusion is a promising approach to resolve a trade-off between the temporal and spatial…
In this work, we investigate a multistatic MIMO-OFDM joint sensing and communication (JSC) system that leverages cooperation among spatially distributed base stations (BSs) to detect and localize multiple targets through soft fusion of…
Multimodal Image Fusion (MMIF) integrates complementary information from various modalities to produce clearer and more informative fused images. MMIF under adverse weather is particularly crucial in autonomous driving and UAV monitoring…
Contrary to the ongoing trend in automotive applications towards usage of more diverse and more sensors, this work tries to solve the complex scene flow problem under a monocular camera setup, i.e. using a single sensor. Towards this end,…
In this paper, an efficient beam and channel acquisition scheme together with joint angle-delay power profile (JADPP) construction are proposed for single-carrier mm-wave wideband sparse massive multiple-input multiple-output (MIMO)…
Strategic subsampling has become a focal point due to its effectiveness in compressing data, particularly in the Full Matrix Capture (FMC) approach in ultrasonic imaging. This paper introduces the Joint Deep Probabilistic Subsampling…
This paper proposes a novel algorithm for multi-focus thermal image fusion. The algorithm is based on local activity analysis and advanced pre-selection of images into fusion process. The algorithm improves the object temperature…
Image fusion combines images from multiple domains into one image, containing complementary information from source domains. Existing methods take pixel intensity, texture and high-level vision task information as the standards to determine…
Integration of aerial and ground images has been proved as an efficient approach to enhance the surface reconstruction in urban environments. However, as the first step, the feature point matching between aerial and ground images is…
With a scheduled launch in October 2018, the James Webb Space Telescope (JWST) is expected to revolutionise the field of atmospheric characterization of exoplanets. The broad wavelength coverage and high sensitivity of its instruments will…
We present an algorithm to derive difference images for data taken with the JWST with matched point-spread functions (PSFs). It is based on the saccadic fast Fourier transform (SFFT) method but with revisions to accommodate the rotations…
Object detection in unmanned aerial vehicle (UAV) remote sensing images poses significant challenges due to unstable image quality, small object sizes, complex backgrounds, and environmental occlusions. Small objects, in particular, occupy…
Generic object detection algorithms have proven their excellent performance in recent years. However, object detection on underwater datasets is still less explored. In contrast to generic datasets, underwater images usually have color…
The combination of range sensors with color cameras can be very useful for robot navigation, semantic perception, manipulation, and telepresence. Several methods of combining range- and color-data have been investigated and successfully…
Multiheterodyne techniques using frequency combs -- light sources whose lines are perfectly evenly-spaced -- have revolutionized optical science. By beating an unknown signal with the many lines of a comb, its spectrum is recovered.…
Mid-infrared (mid-IR) spectroscopy offers unparalleled sensitivity for the detection of trace gases, solids and liquids, which is based on the existence of strong telltale vibrational bands in this part of the spectrum. It was shown more…
Remote sensing images and techniques are powerful tools to investigate earth surface. Data quality is the key to enhance remote sensing applications and obtaining a clear and noise-free set of data is very difficult in most situations due…
We propose an unsupervised image fusion architecture for multiple application scenarios based on the combination of multi-scale discrete wavelet transform through regional energy and deep learning. To our best knowledge, this is the first…
Visible images offer rich texture details, while infrared images emphasize salient targets. Fusing these complementary modalities enhances scene understanding, particularly for advanced vision tasks under challenging conditions. Recently,…
Longtime monitoring of gravitational lens systems is often done using telescopes and recording equipment with modest resolution. Still, it would be interesting to get as much information as possible from the measured lightcurves. From high…