检索结果-内蒙古大学图书馆

conference on image and signal processing for Remote Sensing xxVI

作者： Zhang, Cong Zhang, Haopeng Jiang, Zhiguo Beihang Univ Sch Astronaut Dept Aerosp Informat Engn Beijing 102206 Peoples R China Beijing Key Lab Digital Media Beijing 102206 Peoples R China Minist Educ Key Lab Spacecraft Design Optimizat & Dynam Simul Beijing 102206 Peoples R China

ISBN: (纸本)9781510638808

The infrared observation sensors aboard remote sensing satellites play an important role in the applications of crop yield estimation, environmental protection, land resources survey, disaster monitoring, etc. But infrared remote sensing data is always in low resolution due to hardware limitations. It is a high cost-effective choice to improve the spatial resolution of infrared remote sensing data through super-resolution (SR) algorithm. Deep learning methods have made great breakthroughs in super-resolution of natural images. In this paper, we comparably study five recently popular supervised-deep-learning-based single image SR models for the purpose of super-resolving infrared images, including SRGAN, ESRGAN, LapSRN, RCAN, and SRFBN. We first test the performance of models trained by natural images on infrared remote sensing images to obtain a benchmark, and then specially fine-tune the SR models using infrared images of Landsat8 in a transfer-learning manner. We evaluate the performance of all these fine-tuned models on infrared images with three indicators including PSNR, SSIM, and NIQE. The experimental results show that the SRFBN model achieves the best generalization ability and SR performance. Therefore, we suggest using SRFBN for super-resolution reconstruction of single infrared remote sensing image in applications.

关键词： image super-resolution deep learning infrared remote sensing supervised learning

来源：评论

学校读者我要写书评

暂无评论

Large Format Atomic Layer Deposited Microchannel Plates for Photon Counting image Sensors 22

Large Format Atomic Layer Deposited Microchannel Plates for ...

引用

conference on UV, x-Ray, and Gamma-Ray Space Instrumentation for Astronomy xxII

作者： Curtis, T. Darling, N. Siegmund, O. H. W. McPhate, J. Cremer, T. Univ Calif Berkeley Space Sci Lab 7 Gauss Way Berkeley CA 94720 USA Incom Inc 242 Sturbridge Rd Charlton MA 01507 USA

ISBN: (数字)9781510644816

ISBN: (纸本)9781510644816;9781510644809

For future astronomical applications we have been developing cross-strip anodes with electronic readouts integrated with large format (>= 50 mm) sealed tubes and photocathodes covering the UV and optical regimes. These large format devices will be important for the next generation of moderate and large NASA astrophysics instruments under study (e.g. LUVOIR, HabEx, CETUS), as well as ground based focal plane instruments. Microchannel plates (MCPs) are used as electron multipliers in these devices. They amplify the detected photon signal to a charge cloud on order of a million electrons, which is then sensed through the imaging readout. A recent enhancement comes by way of incorporating resistive and secondary emissive layers to borosilicate capillary arrays utilizing atomic layer deposition (ALD) processing techniques. The borosilicate substrates are more robust than traditional MCPs, allowing for large formats (20 x 20 cm), while also supporting 10-micron pores (capillaries). We have successfully integrated this type of MCP into 50 mm aperture sealed tube devices for the first time. These devices show stable, uniform gain, and can provide very good event timing accuracy. Spatial resolution of better than 20 microns can be achieved with these MCPs, providing more than 2k x 2k resolution elements for a 50mm device. Compared with the current generation of MCPs, the ALD-borosilicate MCPs have shown an order of magnitude increase in lifetime stability gain retention within the vacuum sealed device and long-term preservation of the photocathode efficiency.

关键词： Microchannel plates atomic layer deposition cross-strip anodes

来源：评论

学校读者我要写书评

暂无评论

A Novel 3-D Radar Imaging Method Based on Sparse Optimization 2

A Novel 3-D Radar Imaging Method Based on Sparse Optimizatio...

引用

conference on Big Data II - Learning, Analytics, and applications

作者： Fu, Jixiang xing, Mengdao Amin, Moeness G. Xidian Univ Natl Lab Radar Signal Proc Xian Shaanxi Peoples R China Villanova Univ Ctr Adv Commun Villanova PA 19085 USA

ISBN: (纸本)9781510635685

Three-dimensional (3-D) radar imaging is an important task underpinning many applications that seek target detection, localization, and classification. However, traditional 3-D radar imaging is computationally cumbersome and needs a large memory space to store the cubic data matrix. These challenges have hindered 3-D radar imaging development and limited its applications. Owing to the sparsity of the radar image of typical targets, the data size could be significantly reduced by exploiting compressive sensing and sparse reconstruction techniques. These techniques prove important to mitigate the sidelobe levels that arise from successive Fourier-based processing. Towards this end, we first perform polar reformatting to the 2-D data matrix in azimuth and range. Then, a series of images over different values of the vertical variable z are generated by using different focusing filters. Sparse optimization is afterwards applied to the 3-D data cube to produce high-resolution, significantly reduced sidelobe 3-D image. Compared with the conventional 3-D radar imaging methods, the proposed method, in addition to high fidelity images, requires fewer data measurements and offers computationally efficient processing. Numerical simulations are provided to evaluate the effectiveness of the proposed method.

关键词： Three-dimensional Radar Imaging Polar Reformatting Sparse Optimization High-resolution

来源：评论

学校读者我要写书评

暂无评论

Adaptive image denoising using a deep neural network with a noise correction map 43

Adaptive image denoising using a deep neural network with a ...

引用

conference on applications of Digital image processing xLIII

作者： Nair, Tejas Lee, Jaesung Yoon, Youngjin Lee, Tammy Samsung Seoul R&D Samsung Res 56 Seongchon Gil Seoul 06765 South Korea

ISBN: (数字)9781510638273

ISBN: (纸本)9781510638273

Smartphone camera is becoming the primary choice for photography among general users due to its convenience and rapidly improving image quality. However, it is more prone to noise compared to a professional DSLR camera due to a smaller sensor. image noise, especially in low-light situations, is a critical problem that must be addressed to obtain high quality photos. image denoising has thus remained an important low level vision topic over years with both traditional and learning based techniques used for mitigating this problem. We propose an adaptive Deep Neural Network based Noise Reduction (DNN-NR) algorithm to address the denoising problem in smartphone images. image noise was modeled from photos captured under different light settings using a Poisson-Gaussian noise model which better approximates the signal-dependence (photon sensing) and stationary disturbances in the sensor data. Using this noise model, synthetic noisy datasets were prepared to mimic photos captured under varying light conditions and train the network. A noise correction map based on camera and image information like ISO, vignetting map and image gray level was provided as an input to the network. This correction map provides an indication of the local noise level to help the network adaptively denoise photos. Experimental results show that our adaptive neural network based denoising approach produced a significantly better denoised image with higher PSNR and MOS quality scores in comparison to a standard denoising method like CBM3D across varying light conditions. In addition, using a locally varying noise map helped in preserving more detail in denoised images.

关键词： image denoising noise map synthetic noise generation deep learning neural network

来源：评论

学校读者我要写书评

暂无评论

Urinary Stones Segmentation in Abdominal x-Ray images Based on U-Net Deep Learning Model and Data Augmentation Techniques 5

Urinary Stones Segmentation in Abdominal X-Ray Images Based ...

引用

5th IEEE International conference on signal and image processing, ICSIP 2020

作者： Preedanan, Wongsakorn Kumazawa, Itsuo Kondo, Toshiaki Junichiro, Ishioka Tokyo Institute of Technology Department of Information and Communications Engineering Japan Thammasat University Toshiaki Kondo School of Information and Communication Technology Sirindhorn International Institute of Technology Thailand Tokyo Medical and Dental University Japan

ISBN: (纸本)9781728168968

Urinary stone is the most common abnormality occurring in human urinary system. Early detection in medical imaging is important for promptly treatment or surgery planning. Recently, deep learning methods have been proposed and played a major role in medical image applications. The performance of deep learning model largely depends on the size of training samples. However, the number of samples of patient having urinary stones is limited, and the process of labeling preparation is time-consuming and need experts. In this research, we used a combination of real stone-contained images and synthesized stone-embedded images to train U-Net model to segment urinary stones in abdominal x-ray images. Furthermore, the simple augmentation methods which appear realistic in x-ray images were also implemented in these combined datasets. From the comparative experiments, the proposed method can achieve higher F2 score than U-Net trained with only real images. This method not only helps to reduce the requirement of training data and labels of positive samples, but also increase the number and variability of training data to improve deep learning performance. © 2020 IEEE.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Digital Holography and 3D Imaging 2020: introduction to the feature issue

引用

APPLIED OPTICS 2021年第4期60卷 DH1-DH2页

作者： Liu, Juan Cao, Liangcai Stoykova, Elena Ferraro, Pietro Memmolo, Pasquale Blanche, Pierre-Alexandre Beijing Inst Technol Beijing Peoples R China Tsinghua Univ Beijing Peoples R China Bulgarian Acad Sci Sofia Bulgaria CNR Inst Intelligent Syst Bari Italy CNR ISASI Biella Italy Univ Arizona Tucson AZ 85721 USA

This feature issue of JOSA A and Applied Optics is dedicated to the fourteenth OSA Topical Meeting "Digital Holography and 3D Imaging" held 22-26 June 2020 in a virtual meeting. The conference, taking place every year, is a focal point for global technical interchange in the field of digital holography and 3D imaging, providing premier opportunities for people working in the field to present their new advances in research and development. Papers presented at the meeting highlight current research in digital holography and three-dimensional imaging, including interferometry, phase microscopy, phase retrieval, novel holographic processes, 3D and novel holographic displays, integral imaging, computer-generated holograms, compressive holography, 3D holographic display, AR display, full-field tomography, specific image and signal processing, and holography with various light sources, including coherent to incoherent and x-ray to terahertz waves. Techniques of digital holography and of 3D imaging have numerous applications, such as the state-of-the-art technological developments that are currently underway and have also stimulated further novel applications of digital holography and 3D imaging in biomedicine, deep learning, and scientific and industrial metrologies. (C) 2021 Optical Society of America

关键词： Compressive holography Digital holographic imaging image processing Light sources Phase retrieval Three dimensional imaging

来源：评论

学校读者我要写书评

暂无评论

Design of a Hyperspectral imager Using COTS Optics for Small Satellite applications

Design of a Hyperspectral Imager Using COTS Optics for Small...

引用

2020 International conference on Space Optics, ICSO 2020

作者： Prentice, Elizabeth Frances Grøtte, Mariusz Eivind Sigernes, Fred Johansen, Tor Arne Department of Engineering Cybernetics Norwegian University of Science and Technology Trondheim7491 Norway University Centre in Svalbard Svalbard Science Centre LongyearbyenN-9171 Norway

This paper describes the design of a pushbroom hyperspectral imager built for small satellite applications. Its design allows for low weight, low cost, and flexible configuration making it accessible to both smaller projects and supplemental to larger ones. The imager is constructed from commercial off-the-shelf (COTS) optical and sensor components, along with a machined mechanical structure to enable rapid development times. The presented configuration was selected based on a 6U CubeSat ocean color mission developed at the Norwegian University of Science and Technology. The optical design includes three 50 mm lens objectives, a precision-cut 50 μm slit, a blazed transmission grating, and a detecting CMOS sensor. It has the ability to record wavelengths in the spectral range of 300−1000 nm, e.g. in the visible and near infrared spectrum. The calculated bandpass of typically about 5 nm can be configured or binned for the specific application needs. Since targets, such as the ocean surface, are dark and non-Lambertian, it is challenging to reach the necessary sensitivity that ensures a high signal-to-noise ratio (SNR) in the image. The imaging system presented in this paper is built for obtaining that sufficient SNR for a given resolution, both in the spatial and spectral domains. The satellite will be launched into a 500 km altitude sun-synchronous orbit. While in orbit, the imager utilizes the pushbroom concept of sequentially gathering lines of pixels, of all wavelengths in range, as it passes over its target. The pushbroom concept, combined with the optical design, yields a swath width of up to 70 km per scan line with a sampling distance of 49 × 60 m on ground. A final consideration must be made due to the large size of raw hyperspectral data cubes and the constraints this sets on satellite power consumption for downlink. This can be significantly improved through onboard image processing (e.g. correction, classification, anomaly detection, feature extraction, an

关键词： Orbits

来源：评论

学校读者我要写书评

暂无评论

Starry image Matching Method based on the Description of Multi-scale Geometric Invariant Features

Starry Image Matching Method based on the Description of Mul...

引用

International conference on Optical Instruments and Technology - Optoelectronic Imaging/Spectroscopy and signal processing Technology

作者： Liu, xiaoZheng Mao, Yuxuan Yang, ZhiJia Gao, Kun Zhang, TingHua Beijing Inst Technol Key Lab Photoelect Imaging Technol & Syst Minist Educ China Beijing 100081 Peoples R China

ISBN: (纸本)9781510636552

In the spatial target surveillance and astronomical observation applications, image matching processing is the key procedure for the multi-temporal starry images or the multi-channel starry images acquired by different imaging sensors. However, the starry images obtained often have low signal-to-Noise Ratios (SNR), the light intensities of the target stars or spacecrafts in them are vulnerable to background interferences, such as the atmospheric turbulence and the night clouds, etc., and become dim and instable. With the weak texture information of the target stars, all the influences make the feature point extraction quite difficult. In this paper, a new type of image matching method based on the description of Multi-scale Geometric Invariant Features (MGIF) is proposed, which uses the Rolling Guidance Filter (RGF) to perform preprocessing for the input images. By virtue of the excellent edge-preserving performance of the Joint Bilateral Filter in RGF, the integrities of contour profile of the star points are guaranteed effectively while the interference and other noise in the background are suppressed. Then the segmented and morphology methods are applied to extract star points and get the centroid of star points to form the feature point constellation. Considering the cross ratio of two lines in projection transformation model of image matching is a geometric invariant, a multi-scale geometric invariants based function, which uses the scaling of RGF as a reference to describe the relative spatial positions of matching points more accurately, is constructed to evaluate the level of similarity between star points according to the relative position of each points in the constellation. Subsequently, Random Sample Consensus(RANSAC)method is adopted to remove the mismatching star points and calculate the rigid transform matrix and other registration parameters. Digital simulation and practical processing results demonstrate that the proposed method can achieve higher m

关键词： Starry image Matching Multi-Scale Space Geometric Invariant Features RANSAC Method

来源：评论

学校读者我要写书评

暂无评论

High Dynamic Range image Sharing with Privacy Protection 43

High Dynamic Range Image Sharing with Privacy Protection

引用

conference on applications of Digital image processing xLIII

作者： Upenik, Evgeniy Fernandez-Marti, Pol Ebrahimi, Touradj Ecole Polytech Fed Lausanne EPFL Multimedia Signal Proc Grp MMSPG CH-1015 Lausanne Switzerland

ISBN: (数字)9781510638273

ISBN: (纸本)9781510638273

Sharing pictures has become a very popular practice among consumers. Most recent cameras, displays, and smartphones can capture and display images in high dynamic range and wide colour gamut, contributing to an increase of this type of content. It is a well-known fact that pictures contain information that could cause various security and privacy issues. This is in particular true because high dynamic range pictures exhibit more information when compared to conventional images resulting in an increased invasion of privacy. Lack of proper solutions to overcome privacy can hinder a wide spread adoption of high dynamic range pictures shared in social networks. For example, dark areas of a content that are otherwise difficult to view in a conventional picture become more visible. It is therefore natural that mechanisms are offered to protect privacy while sharing pictures also in high dynamic range. In this paper, we propose an architecture to share high dynamic range images captured by high-end smartphones while offering a mechanism to protect privacy. In our approach, the high dynamic range picture is tone-mapped into a lower dynamic range version which reduces its degree of invasiveness as far as privacy is concerned. Eventually, any remaining privacy sensitive areas in the picture can be further protected (blurring of faces, masking cars licence plates, etc.). The core of the proposed architecture conforms to both JPEG xT, a recently standardised format that offers backward compatibility with legacy JPEG and to JPEG Systems under development. The proposed solution allows to publicly share a protected version of the high dynamic range image tone-mapped to a standard dynamic range picture. The latter can go through transmorphing operation to further protect it. Authorised users can access the original high dynamic range picture. The architecture as described above has been implemented as an app for smartphones running Android OS. We demonstrate feasibility and usefuln

关键词： image processing privacy HDR JPEG xT JPEG Systems security social networks

来源：评论

学校读者我要写书评

暂无评论

Performance evaluation of low power reconfigurable multiplier architectures using different adders for signal processing applications

引用

AIP conference Proceedings 2024年第1期3180卷

作者： R. Ramya S. Moorthi Department of Electronics and Communication Engineering Srinivasa Ramanujan Centre SASTRA Deemed to be University Kumbakonam Tamil Nadu India VLSI Systems Research Laboratory Department of Electrical and Electronics Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India

The multimedia audio and video applications in battery operated portable hand-held devices need to perform numerous signal processing arithmetic operations which are highly multiplication intensive. The development of low power multiplier designs for signal processing applications will significantly contribute to the performance of portable mobile devices. This work provides emphasis on reconfigurability and approximation logic for increasing the power-saving and speed. A low power reconfigurable multi-precision approximate multiplier architecture is presented and its performance is compared against standard exact multiplier designs. Depending on the actual size of the input operands, the multiplier configures itself preventing un-necessary power loss. The impact of the wordlength and the adder used for adding partial products on the low power performance of the multiplier is studied by implementing variants of the proposed multiplier architecture. High boost filtering is performed on certain class of images and image quality is assessed. The approximate technique used does not deteriorate the image quality to notable extent.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：