惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

T
Threat Research - Cisco Blogs
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
The Register - Security
The Register - Security
A
About on SuperTechFans
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
L
LangChain Blog
N
Netflix TechBlog - Medium
量
量子位
博
博客园 - 三生石上(FineUI控件)
宝玉的分享
宝玉的分享
H
Help Net Security
D
Docker
D
DataBreaches.Net
T
Tailwind CSS Blog
阮一峰的网络日志
阮一峰的网络日志
B
Blog
博
博客园 - 聂微东
Apple Machine Learning Research
Apple Machine Learning Research
Google DeepMind News
Google DeepMind News
The Cloudflare Blog
F
Full Disclosure
GbyAI
GbyAI
F
Fortinet All Blogs
Last Week in AI
Last Week in AI
Y
Y Combinator Blog
人人都是产品经理
人人都是产品经理
Recent Announcements
Recent Announcements
博
博客园 - Franky
MongoDB | Blog
MongoDB | Blog
有赞技术团队
有赞技术团队
博
博客园 - 叶小钗
小众软件
小众软件
V
Visual Studio Blog
月光博客
月光博客
Stack Overflow Blog
Stack Overflow Blog
The GitHub Blog
The GitHub Blog
Recorded Future
Recorded Future
J
Java Code Geeks
雷峰网
雷峰网
P
Privacy & Cybersecurity Law Blog
C
Cisco Blogs
C
Cyber Attacks, Cyber Crime and Cyber Security
AWS News Blog
AWS News Blog
Webroot Blog
Webroot Blog
美
美团技术团队
N
News | PayPal Newsroom
G
Google Developers Blog
Security Archives - TechRepublic
Security Archives - TechRepublic
博
博客园_首页
V
Vulnerabilities – Threatpost

cs.CV updates on arXiv.org

ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents On the Robustness of Watermarking for Autoregressive Image Generation Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference Anthropogenic Regional Adaptation in Multimodal Vision-Language Model From Redaction to Restoration: Deep Learning for Medical Image Anonymization and Reconstruction The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning Semantic-Geometric Dual Compression: Training-Free Visual Token Reduction for Ultra-High-Resolution Remote Sensing Understanding Lightweight Low-Light Image Enhancement via Distribution-Normalizing Preprocessing and Depthwise U-Net Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Evaluating the Impact of Medical Image Reconstruction on Downstream AI Fairness and Performance Retinal Cyst Detection from Optical Coherence Tomography Images LoViF 2026 The First Challenge on Weather Removal in Videos STORM: End-to-End Referring Multi-Object Tracking in Videos Data-Efficient Surgical Phase Segmentation in Small-Incision Cataract Surgery: A Controlled Study of Vision Foundation Models Rethinking the Diffusion Model from a Langevin Perspective Zero-shot World Models Are Developmentally Efficient Learners Edu-MMBias: A Three-Tier Multimodal Benchmark for Auditing Social Bias in Vision-Language Models under Educational Contexts VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation Degradation-Consistent Paired Training for Robust AI-Generated Image Detection FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer Demographic and Linguistic Bias Evaluation in Omnimodal Language Models FlowPalm: Optical Flow Driven Non-Rigid Deformation for Geometrically Diverse Palmprint Generation Cross-Cultural Value Awareness in Large Vision-Language Models I Walk the Line: Examining the Role of Gestalt Continuity in Object Binding for Vision Transformers GLEaN: A Text-to-image Bias Detection Approach for Public Comprehension From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping Not Your Stereo-Typical Estimator: Combining Vision and Language for Volume Perception Genie 4D: Semantic-Prior-Guided 4D Dynamic Scene Reconstruction Efficient Personalization of Generative User Interfaces Is There Knowledge Left to Extract? Evidence of Fragility in Medically Fine-Tuned Vision-Language Models ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories PhysInOne: Visual Physics Learning and Reasoning in One Suite Through Their Eyes: Fixation-aligned Tuning for Personalized User Emulation Neural Distribution Prior for LiDAR Out-of-Distribution Detection Adding Another Dimension to Image-based Animal Detection Long-SCOPE: Fully Sparse Long-Range Cooperative 3D Perception CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation FIRE-CIR: Fine-grained Reasoning for Composed Fashion Image Retrieval Detecting Diffusion-generated Images via Dynamic Assembly Forests Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation Tora3: Trajectory-Guided Audio-Video Generation with Physical Coherence Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion Dynamic Class-Aware Active Learning for Unbiased Satellite Image Segmentation Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift Degradation-Robust Fusion: An Efficient Degradation-Aware Diffusion Framework for Multimodal Image Fusion in Arbitrary Degradation Scenarios Adaptive Dual Residual U-Net with Attention Gate and Multiscale Spatial Attention Mechanisms (ADRUwAMS) MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification BIAS: A Biologically Inspired Algorithm for Video Saliency Detection DeFakeQ: Enabling Real-Time Deepfake Detection on Edge Devices via Adaptive Bidirectional Quantization Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs CatalogStitch: Dimension-Aware and Occlusion-Preserving Object Compositing for Catalog Image Generation Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning SenBen: Sensitive Scene Graphs for Explainable Content Moderation Towards Responsible Multimodal Medical Reasoning via Context-Aligned Vision-Language Models R2G: A Multi-View Circuit Graph Benchmark Suite from RTL to GDSII State Space Models are Effective Sign Language Learners: Exploiting Phonological Compositionality for Vocabulary-Scale Recognition Accelerating Transformer-Based Monocular SLAM via Geometric Utility Scoring Deep Learning-Based Tracking and Lineage Reconstruction of Ligament Breakup Unified Multimodal Uncertain Inference Unsupervised Local Plasticity in a Multi-Frequency VisNet Hierarchy EfficientSign: An Attention-Enhanced Lightweight Architecture for Indian Sign Language Recognition InsEdit: Towards Instruction-based Visual Editing via Data-Efficient Video Diffusion Models Adaptation 3D-VCD: Hallucination Mitigation in 3D-LLM Embodied Agents through Visual Contrastive Decoding On Semiotic-Grounded Interpretive Evaluation of Generative Art Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting From Selection to Scheduling: Federated Geometry-Aware Correction Makes Exemplar Replay Work Better under Continual Dynamic Heterogeneity ViSAGE @ NTIRE 2026 Challenge on Video Saliency Prediction Needle in a Haystack: One-Class Representation Learning for Detecting Rare Malignant Cells in Computational Cytology A Semi-Automated Framework for 3D Reconstruction of Medieval Manuscript Miniatures Detection of Hate and Threat in Digital Forensics: A Case-Driven Multimodal Approach Orthogonal Quadratic Complements for Vision Transformer Feed-Forward Networks HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models Pretrain-then-Adapt: Uncertainty-Aware Test-Time Adaptation for Text-based Person Search Assessing Privacy Preservation and Utility in Online Vision-Language Models R3PM-Net: Real-time, Robust, Real-world Point Matching Network Tipiano: Cascaded Piano Hand Motion Synthesis via Fingertip Priors Belief-Aware VLM Model for Human-like Reasoning GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents B-MoE: A Body-Part-Aware Mixture-of-Experts "All Parts Matter" Approach to Micro-Action Recognition FDIF: Formula-Driven supervised Learning with Implicit Functions for 3D Medical Image Segmentation CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention BiCLIP: Domain Canonicalization via Structured Geometric Transformation Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers When & How to Write for Personalized Demand-aware Query Rewriting in Video Search Relational Visual Similarity Enhancing Geo-localization for Crowdsourced Flood Imagery via LLM-Guided Attention GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models OmniPrism: Learning Disentangled Visual Concept for Image Generation MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions
Shift Variant Image Degradation and Restoration Using Singular Value Decomposition
[Submitted on 24 Jun 2026] · 2026-06-25 · via cs.CV updates on arXiv.org

Computer Science > Computer Vision and Pattern Recognition

arXiv:2606.25818 (cs)

[Submitted on 24 Jun 2026]

View PDF

Abstract:Shift-variant image degradation is frequently encountered in practical imaging systems where the point spread function (PSF) varies across the image field due to motion, optical aberrations, atmospheric turbulence, or sensor-related effects. Unlike shift-invariant, shift-variant degradation presents significant challenges for image restoration because the degradation process cannot be represented by a single convolution kernel. This paper proposes a singular value decomposition (SVD)-based framework for restoring images degraded by shift-variant motion blur. The proposed approach determines the contribution of small singular values using a singular-value energy retention criterion. Specifically, the number of small singular values is selected based on a specified percentage of cumulative singular-value energy, providing a systematic approach for controlling noise amplification while preserving useful image information. The degradation model is formulated using a position-dependent PSF represented by a shift-variant imaging operator. Three representative one dimensional shift-variant motion PSFs are considered: bidirectional linear motion, Gaussian motion, and simple harmonic motion. The image degradation process is modeled as a linear system, and SVD is employed to analyze and invert the corresponding degradation operator. The singular-value representation provides insight into the ill-conditioned nature of the restoration problem and enables the development of stable inversion techniques. The proposed SVD-based restoration algorithm is applied to three degraded images. Experimental results demonstrate the effectiveness of the proposed approach in recovering image details and reducing blur artifacts under different motion models.

Submission history

From: Arun Kulkarni [view email]
[v1] Wed, 24 Jun 2026 13:34:20 UTC (672 KB)

Current browse context:

cs.CV

Bookmark

BibSonomy Reddit

Bibliographic Tools

Bibliographic and Citation Tools

Bibliographic Explorer Toggle

Code, Data, Media

Code, Data and Media Associated with this Article

Demos

Demos

Related Papers

Recommenders and Search Tools

About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。