Super-resolution photoelectric fusion imaging combines multiple imaging modalities to produce high-resolution, all-in-focus images, often using deep learning and advanced fusion algorithms.OverviewSup...
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Imaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence
Here, authors develop a multimodal AI method to generate super-resolution of a sensor using other available sensors in the system, revealing hidden dynamics in fusion plasmas and
However, this fusion process relies on the availability of precise alignment between image pairs, which is often challenging in real-world scenarios. To mitigate this limitation, we propose a single-image super
This fusion provides a novel approach for image super-resolution, combining the strengths of traditional spatial domain methods and frequency domain techniques, thereby demonstrating
Apart from technical requirements in optical systems and algorithms, super-resolution imaging relies on fluorescent dyes with special photophysical or photochemical properties. The
To address the limitations of hyperspectral imaging systems, super-resolution (SR) techniques that fuse low-resolution hyperspectral image (HSI) with high-resolution multispectral
Drawing inspiration from multi-image super-resolution (MISR), which is a cornerstone technique in remote sensing and satellite imaging that
To overcome these problems, a multi-modal medical image super-resolution (SR) fusion (MMISRF) method is proposed based on detail enhancement and weighted local energy deviation
Compared to conventional ptychography, our method not only achieves resolution enhancement but also delivers a 3× improvement in contrast
In the field of remote sensing, super-resolution (SR) is a severely ill-posed problem, and image quality is influenced by numerous factors such as atmospheric disturbance, ultra-long-range...
Due to increasingly complex factors of image degradation, inferring high-frequency details of remote sensing imagery is more difficult compared to ordinary digital photos. This paper
In this work, we have demonstrated that the multiframe super-resolution framework can be used in medical image fusion applications. The proposed method aggregates information from input
Quantum super-resolution imaging provides a nonlabeling method to surpass the diffraction limit of imaging systems. This technique relies on measurement of the second-order
Key Points 1 Teledyne FLIR OEM launched Prism Ground ISR, fusing visible and thermal imaging with AI to classify and track up to 15 ground-target classes. 2 Computational imaging
Image Super-Resolution (SR) has seen remarkable progress with the emergence of transformer-based architectures. However, due to the high computational cost, many existing
The invention discloses a photoelectric fusion microscopic imaging system combining a high-resolution fluorescence microscope and a scanning electron microscope, including a
This Review provides a comprehensive discussion of how methods in machine learning and computer vision have been used to improve super-resolution microscopy to gain insights into
Super-resolution (SR) aims to reconstruct high-resolution images from low-resolution inputs, with deep learning advancements driving substantial improvements in SR performance.
The super-resolution images are obtained by aligning and subtracting two images, that are acquired simultaneously using parallelized scanning solid- and donut-shaped excitation beams with a
We introduce a novel multi-resolution data fusion (MDF) method for super-resolution computational EM. Our method combines innovative data acquisition with novel algorithmic techniques to dramatically
Dual photoacoustic and fast super-resolution ultrasound imaging technique bridges the physiological and structural details in vivo. The authors demonstrated that this interleaved technology
Applications in materials and biological imaging are limited by the ability to collect high-resolution data over large areas in practical amounts of time. One solution to this problem is to
Purpose. To provide PET/CT image fusion with an improved PET resolution and better contrast ratios than standard reconstructions. Method. Using a super-resolution algorithm, several PET acquisitions
Far-field super-resolution fluorescence microscopy has allowed observation of biomolecular and synthetic nanoscale systems with features on the nanometre scale, with chemical
This study proposed a SR reconstruction method, DL-MFIF, for THz-TDS point-scan imaging, aiming to address key challenges in existing THz imaging systems, including insufficient
This paper proposes ESR-LEFuse, an end-to-end framework that couples a dual-branch fusion module with an ESR-U-Net upsampling head to realize fourfold super-resolution while preserving thermal
A loss controlled residual network (LCRN) workflow is developed for super-resolution fusion of plant mass spectrometry imaging data. LCRN uses a novel edge perceptual loss metric to
Although existing super-resolution (SR) reconstruction methods can partially improve imaging efficiency, a certain gap still remains between the reconstruction performance and practical
Infrared thermal imaging is widely used in military and civil fields like security and protecting monitoring, military reconnaissance, road traffic monitoring. However, most current infrared sensors have limited
In this study, we proposed a self-supervised pan-sharpening method with the aid of spectral super-resolution named sSRPNet. Coarsening-scale self-learning exploits the internal