the Point Spread Function
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Related Articles from SNS
Fundamental Limit for One versus Two Point Sources Detection using Direct Imaging
arXiv:2606.00968v1 Announce Type: new Abstract: We consider the task of distinguishing between a single weak incoherent optical point source and two weak incoherent optical point sources located symmetrically about the first source. $\theta$ is the separation between the two point sources scaled to the Point Spread Function (PSF) width in the image plane. Using an ideal focal plane array of intensity detectors (ideal direct imaging), we quantify the performance using the Bhattacharyya...
Instant Prior-Free Resolution Enhancement for Cross-Modality Microscopy
The resolving power of optical microscopy is fundamentally constrained by the diffraction of light, limiting our ability to visualize subcellular structures. Computational methods, particularly deconvolution, can restore blurred images but critically depend on an accurate point spread function (PSF), whose estimation is often impractical and error-prone, leading to artifacts. Here, we introduce Nonlinear Fourier Re-weighting (NFR), a rapid algorithm that operates without any prior knowledge...
Semi-supervised Source Detection in Astronomical Images: New Benchmark and Strong Baseline
arXiv:2606.09219v1 Announce Type: new Abstract: Source detection in modern observational astronomy is a cornerstone for localizing and identifying stellar sources accurately. It is crucial for studies such as stellar population synthesis and cosmological parameter estimation. However, the characteristics of astronomical images, including high density, the effect of point spread functions and low signal-to-noise ratios, significantly challenge the latest advanced object detectors.
The Need for Neural ISP in the Small-Pixel Era: How Shrinking Pixels Push Optics to the Limit and Neural Restoration Pushes Back
arXiv:2606.07675v1 Announce Type: Smartphone telephoto cameras are approaching a "telephoto physics wall": as pixel pitches shrink toward sub-0.5 micron, the optics remain limited by geometric aberrations, leading to diminishing returns on resolution. Traditional Image Signal Processors (ISPs) cannot eliminate these aberrations, because they operate through local, stage-wise processing with no explicit model of the underlying point spread function (PSF).
Towards Blind Lens Aberration Correction via Large LensLib Pre-training and Discrete Degradation Priors
arXiv:2511.17126v4 Announce Type: replace-cross Abstract: Emerging deep-learning-based lens library pre-training (LensLib-PT) pipeline offers a new avenue for blind lens aberration correction by training a universal neural network, demonstrating strong capability in handling diverse unknown optical degradations. This work proposes FoundCAC, a universal foundational framework that resolves two challenges hindering the generalization of existing pipelines: the difficulty of scaling training...
Dual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detection
Announce Type: replace Abstract: Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introduce substantial inference latency. Most existing acceleration strategies compress the reconstruction network while overlooking physical priors from the optical path, leaving a trade-off between accuracy and speed. We present Physics-aware Dual-Integrated Network (PDI-Net), a low-latency framework that...
Dual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detection
Announce Type: replace-cross Abstract: Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introduce substantial inference latency. Most existing acceleration strategies compress the reconstruction network while overlooking physical priors from the optical path, leaving a trade-off between accuracy and speed. We present Physics-aware Dual-Integrated Network (PDI-Net), a low-latency framework that...
Towards Blind Lens Aberration Correction via Large LensLib Pre-training and Discrete Degradation Priors
arXiv:2511.17126v4 Announce Type: replace-cross Abstract: Emerging deep-learning-based lens library pre-training (LensLib-PT) pipeline offers a new avenue for blind lens aberration correction by training a universal neural network, demonstrating strong capability in handling diverse unknown optical degradations. This work proposes FoundCAC, a universal foundational framework that resolves two challenges hindering the generalization of existing pipelines: the difficulty of scaling training...
SL-BiLEM: Structured Learnable Behavior-in-the-Loop Epidemic Modeling for Forecasting and Policy Evaluation
Announce Type: replace Abstract: Epidemic forecasting faces a fundamental challenge: human behavior dynamically responds to disease spread, creating feedback loops that induce distribution shifts at policy intervention points. This renders data-driven models unreliable under distribution shift. We propose \textbf{SL-BiLEM} (Structured Learnable Behavior-in-the-Loop Epidemic Model), leveraging physical constraints as regularization for robust extrapolation.
DWP trials PIP changes affecting thousands of claimants
DWP trials PIP changes affecting thousands of claimants A DWP whistleblower brought the plans to light - Bookmark - CommentsGo to comments The Department for Work and Pensions (DWP) has confirmed that it has begun trialling a new system for assessing claimants for the personal independence payment (PIP) after a whistleblower expressed concerns over the plans. Under current rules, healthcare professionals such as nurses, paramedics and physiotherapists are tasked with carrying out functional...