2015 National Aerospace and Electronics Conference (NAECON)最新文献_第3页

Multiframe super resolution with JPEG2000 compressed images 多帧超分辨率与JPEG2000压缩图像

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443032

B. Narayanan, R. Hardie

引用次数: 0

Bandelet denoising in image processing 图像处理中的带状波去噪

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443035

Michel McLaughlin, Samuel Grieggs, Soundararajan Ezekiel, M. Ferris, Erik Blasch, M. Alford, Maria Cornacchia, A. Bubalo

{"title":"Bandelet denoising in image processing","authors":"Michel McLaughlin, Samuel Grieggs, Soundararajan Ezekiel, M. Ferris, Erik Blasch, M. Alford, Maria Cornacchia, A. Bubalo","doi":"10.1109/NAECON.2015.7443035","DOIUrl":"https://doi.org/10.1109/NAECON.2015.7443035","url":null,"abstract":"As digital media and internet use grow, imagery and video are prevalent in many areas of life. Many sensing methods such as Full Motion Video (FMV), Hyperspectral Imagery (HSI), and medical imaging have been developed to accumulate data for diagnostics. Analyzing imagery data to detect and identify specific objects is an essential phase of comprehending visual imagery. Content-based image retrieval (CBIR) is a contemporary development in the field of computer vision. Currently, edge detection filters create undesirable noise for CBIR that leads to difficulties in object detection algorithms. Bandelets have been shown to decrease the noise in signals and images by their use of geometric regularity to compute polynomial approximations in localized regions. In this paper, we use both the bandelet and the discrete wavelet transform to decrease noise within an image. By using Wavelet Exploitation of Bandelet Coefficients (WEBC) to decrease noise we can enhance object detection for CBIR. WEBC raised the peak signal to noise ratio from noised to the denoised images by 19 percent on average, while the structural similarity index measure actually increased by 80 percent on average.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125246039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Extraction and classification of moving targets in multi-sensory MAMI-1 data collection 多感官MAMI-1数据采集中运动目标的提取与分类

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443102

R. Ilin, Scott Clouse

引用次数: 4

Implementation of IR spectral target sensing algorithm in synthesizable logic 红外光谱目标感知算法的可合成逻辑实现

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443086

Woo-Yong Jang, M. Vakil, J. Vella, M. Noyola

引用次数: 0

Cloud technology applications for area surveillance 云技术在区域监控中的应用

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443044

Ryan Wu, Anna Deng, Yu Chen, Erik Blasch, Bingwei Liu

引用次数: 3

Detecting anomalous behavior in microcontrollers using unintentional radio frequency emissions 使用无意的射频发射检测微控制器中的异常行为

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443058

J. Wylie, Samuel J. Stone

引用次数: 1

Using ROC curves and AUC to evaluate performance of no-reference image fusion metrics 采用ROC曲线和AUC评价无参考图像融合指标的性能

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443034

M. Ferris, Michel McLaughlin, Samuel Grieggs, Soundararajan Ezekiel, Erik Blasch, M. Alford, Maria Cornacchia, A. Bubalo

{"title":"Using ROC curves and AUC to evaluate performance of no-reference image fusion metrics","authors":"M. Ferris, Michel McLaughlin, Samuel Grieggs, Soundararajan Ezekiel, Erik Blasch, M. Alford, Maria Cornacchia, A. Bubalo","doi":"10.1109/NAECON.2015.7443034","DOIUrl":"https://doi.org/10.1109/NAECON.2015.7443034","url":null,"abstract":"Image fusion has many applications in which a reference image is not always available including image registration, medical imaging, and fusion between visible and infrared imagery. For these no-reference applications, it is important that there are objective and efficient methods for validating fusion performance, as subjective image fusion evaluation is time consuming and non-scalable. There have been multiple no-reference objective metrics created in the past. These include mutual information, spatial frequency, and structural similarity index measure (SSIM). However, it is important to consider justification of a given evaluation metric as appropriate for a given type of image fusion method. We seek to ensure that if a given metric scores one image higher than another, then the image with the higher metric score is subjectively preferred. This pilot study investigates the applications of Receiver Operating Characteristic (ROC) curves and the Area Under the Curve (AUC) as a method of validation for fusion metrics used for evaluating image fusion methods. The results from the pilot study indicate that ROC curves and AUC provide a discriminating form of validation for image fusion metrics to support image fusion applications evaluation.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134416495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Near-and mid-infrared fluorescence enhancement in terbium-yttrium polytantalate 多钽酸铽钇近红外和中红外荧光增强

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443048

J. Vella, J. Goldsmith, N. Limberopoulos, V. Vasilyev

引用次数: 0

A modified collaborative adaptive wiener filter for multi-frame super-resolutionaper 一种改进的多帧超分辨率协同自适应维纳滤波器

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443031

K. M. Mohamed, R. Hardie

{"title":"A modified collaborative adaptive wiener filter for multi-frame super-resolutionaper","authors":"K. M. Mohamed, R. Hardie","doi":"10.1109/NAECON.2015.7443031","DOIUrl":"https://doi.org/10.1109/NAECON.2015.7443031","url":null,"abstract":"During acquisition, digital images are invariably degraded by a number of phenomena that limit image resolution and utility. Aliasing from undersampling, blur from optics, and sensor noise are some factors which can affect the image resolution. Multi-frame super-resolution (SR) is a technique that takes several low-resolution (LR) frames of a particular scene and processes them together to produce one or more high-resolution (HR) images. The HR images have higher spatial frequency content, and less noise and blur, than any of the LR frames. A collaborative adaptive Wiener filter (CAWF) for multi-frame SR, proposed by the current authors, is one of the very recent effective multi-frame SR algorithms. In this paper, we modify the original CAWF SR method by employing a spatially varying signal variance estimate. Instead of using a global signal variance estimate as an external input to the original CAWF SR algorithm, we estimate the desired signal variance in each processing window and incorporate it to estimate the HR pixels. The modified CAWF SR is presented and demonstrated. In addition, performance comparisons between the original and the modified CAWF SR are conducted. The modified CAWF SR outperforms the original CAWF SR, particularly in low signal-to-noise ratio images.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121944058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Memristor crossbar based unsupervised training 基于忆阻交叉棒的无监督训练

2015 National Aerospace and Electronics Conference (NAECON) Pub Date : 2015-06-15 DOI: 10.1109/NAECON.2015.7443091

Raqibul Hasan, T. Taha

引用次数: 5