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检索条件"任意字段=Conference on Image Quality and System Performance IX"

共 7092 条记录，以下是11-20 订阅

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Status of the Lowell Discovery Telescope (LDT) and assessment of the image quality at the focal plane 9

Status of the Lowell Discovery Telescope (LDT) and assessmen...

引用

conference on Ground-based and Airborne Telescopes ix

作者： Levine, S. E. Ellsworth-Bowers, T. Bida, T. A. Hamilton, R. Kuehn, K. Lowell Observ 1400 West Mars Hill Rd Flagstaff AZ 86001 USA MIT Dept Earth Atmospher & Planetary Sci 77 Massachusetts Ave Cambridge MA 02139 USA

ISBN: (纸本)9781510653467;9781510653450

The Lowell Discovery Telescope (LDT, formerly known as the DCT) is a 4.3-m telescope designed and constructed for optical and near infrared astronomical observation. We present the evolution over time of LDT's image quality and ways to improve it, upgrades to the instrument suite, and lessons learned from operating during the pandemic.

关键词： Lowell Discovery Telescope LDT Lowell Observatory Telescope and system performance image quality system Status

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Automating system-level stray light analysis with Ansys Optics 9

Automating system-level stray light analysis with Ansys Opti...

引用

conference on Optical Design and Engineering ix

作者： Lauinger, Tobias Thoene, Stefan Dannenberg, Tino Nazari, Mina Morales, Angel Blobel, Gernot Gely, Sandra Grove, Mike Lesage, Etienne Sklavenitis, Stavros Bastide, Fabien Ansys 2600 Ansys Dr Canonsburg PA 15317 USA

ISBN: (纸本)9781510673571;9781510673564

Stray light analysis is essential for the design of high-quality optical systems, to ensure that unwanted light reaching the sensor is minimized, and artifacts that degrade optical performance - such as lens flare - are mitigated. This article introduces a system-level approach for stray light analysis using Ansys Optics simulation tools, considering stray light from both optical and non-optical components. The article illustrates how these tools can be integrated with Ansys optiSLang for automated exploration and design optimization. The practical camera use-case highlights a seamless data exchange between Ansys Optics simulation tools. It employs a range of intuitive features, from Ansys Zemax OpticStudio's sequential ray tracing, extending to Ansys Speos ray path analysis, while leveraging HPC and Cloud Computing. The combined capabilities offer an efficient solution, streamlining collaboration and enabling optimized optical system designs.

关键词： Stray light analysis Automation High-quality optical systems Ansys Zemax OpticStudio Ansys Speos Ansys OptiSLang GPU HPC and Cloud Computing Lens flare

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Blind image quality Assessment Based on Human Visual Perception 24

Blind Image Quality Assessment Based on Human Visual Percept...

引用

6th International conference on Video Signal and image Processing

作者： Xia, Tianfeng Zhao, Yongcan Yang, Gangqiang Chen, Lei Shandong Univ Sch Informat Sci & Engn Qingdao Shandong Peoples R China

ISBN: (纸本)9798400709647

The human visual system (HVS) is important for guiding the blind image quality assessment method (BIQA). Inspired by the free-energy principle, an NR-IQA method that simulates human visual perception is proposed. The whole model consists of an image restoration network and a multi-stream quality prediction network. Firstly, the distorted image is fed into the image restoration network to generate the restored images and discrepancy map, in which the quality perception constraint and the structural similarity discrepancy map-based constraint are both considered during the optimization to improve the recovery performance. Then, the distorted images, the restored images, and the perceptual discrepancy maps are utilized as inputs for the multi-stream quality prediction network to obtain their fused features. Finally, the fused features are input into the patch-based attention module to obtain the final image patch scores. Extensive experiments demonstrate that our proposed model is effective and achieves competitive performance when compared with other related state-of-the-art methods.

关键词： image quality assessment Human visual system image restoration

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Ghost reflection Simulation, Analysis and Correction in a Multispectral Imaging system 9

Ghost reflection Simulation, Analysis and Correction in a Mu...

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conference on Optical Design and Engineering ix

作者： Rishav, Kumar Gupta, Barkha India Space Res Org Space Applicat Ctr Ahmadabad 380015 Gujarat India

ISBN: (纸本)9781510673571;9781510673564

Ghost images refer to unwanted secondary images or reflections that appear alongside the primary image, causing interference or reducing image quality. These ghost images are caused by multiple reflections of in-field imaging rays within the optical system. We have developed a methodology for comprehensive modeling and analysis of ghost images produced within a catadioptric multi-spectral imaging systems. Instead of characterising these ghosts as mere points of light, we conducted a detailed qualitative and quantitative examination of the ghost reflections. We identify cross-talk ghost as a significant issue, even with low surface reflection coefficients. By identifying major contributors, the study enables the formulation of robust mitigation strategies. Our methodology includes generating ghost layouts, identifying primary contributors, and precisely quantifying the flux stemming from these ghost reflections. Furthermore, we introduced multiple strategies for reducing ghost reflections, culminating in the design of a Ghost Blocker Plate engineered to effectively counteract ghost reflections. A series of meticulously planned experiments was conducted to validate our developed methodology. As a result, we successfully demonstrated a substantial reduction in ghost reflections within an optical system, reducing them from an initial level of 23% to less than 1%.

关键词： Ghost Analysis Integrating Sphere Illumination Stray light ASAP Illumination Design Multispectral Imaging Telescope

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Quadratic Polynomial Residual Network for No-Reference image quality Assessment 6th

Quadratic Polynomial Residual Network for No-Reference Image...

引用

6th Chinese conference on Pattern Recognition and Computer Vision (PRCV)

作者： Fan, Xiaodong Liaoning Tech Univ Fac Elect & Control Engn Huludao 125105 Liaoning Peoples R China

ISBN: (纸本)9789819985456;9789819985463

Residual connection has become an essential structure of deep neural networks. In residual connection, shallow features are directly superimposed to deep features without any processing. In this paper, a quadratic polynomial residual module is designed to increase the nonlinear fitting ability of the network. As the name suggests, this module superimposes quadratic polynomials of shallow features onto deep features. In this way, the series of two modules has the fitting ability of a quartic polynomial. The fitting ability of the network increases exponentially with the number of layers. According to Taylor's theorem, it can be concluded that this module effectively improves the fitting ability of the network. Meanwhile, the image patches containing more information have greater contribution to image quality assessment. The patches are screened according to the two-dimensional information entropy, which reflects the information amount of patches. Based on the above two points, a quadratic polynomial residual network with entropy weighting and multi-receptive field structure is proposed for no-reference image quality assessment. The experimental results show that the proposed algorithm achieves high accuracy and more effectively fits the human visual system.

关键词： image quality assessment Deep learning Residual network

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Construction of Interactive Construction Progress and quality Monitoring system Based on image Processing

Construction of Interactive Construction Progress and Qualit...

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2024 International conference on Telecommunications and Power Electronics, TELEPE 2024

作者： Wu, Wei Fushun Vocational and Technical College Liaoning Fushun113122 China

ISBN: (数字)9798350369212

ISBN: (纸本)9798350369212

The purpose of this study is to build an interactive construction progress and quality monitoring system based on image processing, so as to improve the monitoring efficiency and quality management level of the construction site. The system uses advanced deep learning algorithm to realize automatic recognition, progress prediction and quality inspection of construction site images. In terms of system design, this study proposes a modular system architecture, including data acquisition, image processing, progress monitoring, quality inspection, interactive interface and data storage management. Through the design, implementation and experimental verification of the system, this study proves that the system can effectively monitor the progress of the construction site, find quality problems, and provide users with real-time monitoring reports and improvement suggestions. The experimental results show that the system has good monitoring effect and performance in different scenarios, which provides a brand-new digital solution for construction management. © 2024 IEEE.

关键词： Project management

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Tackling the Satellite Downlink Bottleneck with Federated Onboard Learning of image Compression

Tackling the Satellite Downlink Bottleneck with Federated On...

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IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Gomez, Pablo Meoni, Gabriele ESA ESRIN Frascati Italy Delft Univ Technol Dept Space Engn Aerosp Engn Delft Netherlands AI Sweden Gothenburg Sweden ESA ESTEC Adv Concepts Team Noordwijk Netherlands

ISBN: (纸本)9798350365474

Satellite data transmission is a crucial bottleneck for Earth observation applications. To overcome this problem, we propose a novel solution that trains a neural network on board multiple satellites to compress raw data and only send down heavily compressed previews of the images while retaining the possibility of sending down selected losslessly compressed data. The neural network learns to encode and decode the data in an unsupervised fashion using distributed machine learning. By simulating and optimizing the learning process under realistic constraints such as thermal, power and communication limitations, we demonstrate the feasibility and effectiveness of our approach. For this, we model a constellation of three satellites in a Sun-synchronous orbit. We use real raw, multispectral data from Sentinel-2 and demonstrate the feasibility on space-proven hardware for the training. Our compression method outperforms JPEG compression on different image metrics, achieving better compression ratios and image quality. We report key performance indicators of our method, such as image quality, compression ratio and benchmark training time on a Unibap ix10-100 processor. Our method has the potential to significantly increase the amount of satellite data collected that would typically be discarded (e.g., over oceans) and can potentially be extended to other applications even outside Earth observation. All code and data of the method are available online to enable rapid application of this approach.

关键词： distributed edge learning federated learning Onboard compression Onboard ML satellite constellation Sentinel-2 raw data

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Patient-specific NEQ(f): Automatic local and global determination of spatial-frequency-dependent SNR and task performance in clinical CT

Patient-specific NEQ(f): Automatic local and global determin...

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conference on Medical Imaging - Physics of Medical Imaging

作者： Pillai, Parvathy S. Siewerdsen, Jeffrey H. Rypinski, Tatiana Deva, Anshuj Soni, Bhavin Jones, A. Kyle Ahmad, Moiz Univ Texas MD Anderson Canc Ctr Dept Imaging Phys 1515 Holcombe Blvd Houston TX 77030 USA

ISBN: (纸本)9781510671553;9781510671546

Phantom-based quality control, the current standard of QC in medical imaging, calibrates image quality at a population level, but does not account for the influence of patient variation on quality. In this work, we present a method to evaluate task-based image quality directly in individual clinical CT exams. Noise power spectrum (NPS) is measured in selected local image regions satisfying linearity and noise stationarity constraints, and globally over the volumetric image. Together with a semi-empirical model of image resolution, NPS is used to calculate noise-equivalent quanta (NEQ), a fundamental metric of image fidelity and information content. The NEQ may be extended to task-based detectability (d') via a specified task function and model observer. We show that this method can: 1) elucidate intra-patient variations in signal detectability, and 2) task performance variations across a patient population. The method may be implemented in a hospital-wide online system that monitors imaging performance in CT exams in real-time.

关键词： computed tomography image quality quality control patient-specific task-based performance model observer

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Research on the Application of Multi-Channel Display Technology in Virtual Scene image Generation 5

Research on the Application of Multi-Channel Display Technol...

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5th IEEE International conference on Power, Electronics and Computer Applications, ICPECA 2025

作者： Liu, Yuanlin Wang, Lingling Haikou University of Economics Haikou571127 China

ISBN: (纸本)9798331533694

This study proposes an innovative algorithm based on DCNN and multi-channel image fusion, aiming to improve the quality and efficiency of virtual scene image generation. The algorithm extracts depth information and texture features in virtual scenes through DCNN, and combines multi-channel image fusion technology to optimize and fuse the information of different image channels (such as color, depth, normal, etc.), thereby significantly improving the image rendering effect. Through adaptive weight adjustment and image fusion strategy, the image detail performance is optimized, especially in scenes with complex lighting and rich textures, the rendering quality is significantly improved. Experimental results show that the image generation system based on this algorithm improves image quality by 15%, rendering speed by 25%, and computing resource consumption by 20%. When processing highly complex virtual scenes, the system can achieve real-time rendering and meet the performance requirements of VR and AR applications. This study provides a new and efficient solution for image generation in virtual reality and augmented reality, and demonstrates the great potential of combining multi-channel display technology with deep learning in improving rendering effects. © 2025 IEEE.

关键词： Virtual environments

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ARCHITECTURAL GENERATIVE MODEL EVALUATION METHODS: image quality ASSESSMENT METRICS AND EXPERT-BASED APPROACH 29th

ARCHITECTURAL GENERATIVE MODEL EVALUATION METHODS: IMAGE QUA...

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29th International conference of the Association-for-Computer-Aided-Architectural-Design-Research-in-Asia (CAADRIA)

作者： Lin, Ying Ye, Fei Xian Univ Architecture & Technol Xian Peoples R China

ISBN: (纸本)9789887891819

The feasibility of using machine learning methods to generative architectural design solutions has been widely recognized as an effective in enhancing innovation, diversity, and efficiency of solutions. However, in generative design methods, the accuracy and quality of design results often rely on empirical evaluation of expert, which is challenging to evaluate and quantify by unified standards. This paper proposes a comprehensive method for evaluating model performance in architectural design tasks. The evaluation is based on computational criteria (i.e., FID, IS, SIMM indicators) and expert system criteria. The computational metrics will measure the distance, diversity, and similarity between the feature vectors of the real image and the generated image. In contrast, the expert criteria will measure the accuracy, intentionality, and rationality of the layout scheme. This study applies this framework to evaluate three widely used generative models in architectural design: GANs, Diffusion Models, and VAE. The framework also guides the optimization of generative models in architectural applications and assists architects in validating generative outcomes with more efficient workflows.

关键词： Deep Learning Generate Design Evaluation Metrics Campus Planning

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