Signal and image processing : an international journal最新文献_第4页

Free- Reference Image Quality Assessment Framework Using Metrics Fusion and Dimensionality Reduction 基于度量融合和降维的自由参考图像质量评估框架

Signal and image processing : an international journal Pub Date : 2019-10-31 DOI: 10.5121/sipij.2019.10501

B. Sadou, A. Lahoulou, T. Bouden, Anderson R. Avila, T. Falk, Z. Akhtar

{"title":"Free- Reference Image Quality Assessment Framework Using Metrics Fusion and Dimensionality Reduction","authors":"B. Sadou, A. Lahoulou, T. Bouden, Anderson R. Avila, T. Falk, Z. Akhtar","doi":"10.5121/sipij.2019.10501","DOIUrl":"https://doi.org/10.5121/sipij.2019.10501","url":null,"abstract":"This paper focuses on no-reference image quality assessment(NR-IQA)metrics. In the literature, a wide range of algorithms are proposed to automatically estimate the perceived quality of visual data. However, most of them are not able to effectively quantify the various degradations and artifacts that the image may undergo. Thus, merging of diverse metrics operating in different information domains is hoped to yield better performances, which is the main theme of the proposed work. In particular, the metric proposed in this paper is based on three well-known NR-IQA objective metrics that depend on natural scene statistical attributes from three different domains to extract a vector of image features. Then, Singular Value Decomposition (SVD) based dominant eigenvectors method is used to select the most relevant image quality attributes. These latter are used as input to Relevance Vector Machine (RVM) to derive the overall quality index. Validation experiments are divided into two groups; in the first group, learning process (training and test phases) is applied on one single image quality database whereas in the second group of simulations, training and test phases are separated on two distinct datasets. Obtained results demonstrate that the proposed metric performs very well in terms of correlation, monotonicity and accuracy in both the two scenarios.","PeriodicalId":90726,"journal":{"name":"Signal and image processing : an international journal","volume":"20 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85678654","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

Improvements of the Analysis of Human Activity Using Acceleration Record of Electrocardiographs 利用心电图加速记录分析人体活动的改进

Signal and image processing : an international journal Pub Date : 2019-10-31 DOI: 10.5121/sipij.2019.10504

Itaru Kaneko, Y. Yoshida, E. Yuda

{"title":"Improvements of the Analysis of Human Activity Using Acceleration Record of Electrocardiographs","authors":"Itaru Kaneko, Y. Yoshida, E. Yuda","doi":"10.5121/sipij.2019.10504","DOIUrl":"https://doi.org/10.5121/sipij.2019.10504","url":null,"abstract":"The use of Holter Electrocardiograph (Holter ECG) is rapidly spreading. It is a wearable electrocardiograph that records 24-hour electrocardiograms in a built-in flash memory, making it possible to detect atrial fibrillation (Atrial Fibrillation, AF) through all-day activities. It is also useful for screening for diseases other than atrial fibrillation and for improving health. It is said that more useful information can be obtained by combining electrocardiograph with the analysis of physical activity. For that purpose, the Holter electrocardiograph is equipped with heart rate sensor and acceleration sensors. If acceleration data is analysed, we can estimate activities in daily life, such as getting up, eating, walking, using transportation, and sitting. In combination with such activity status, electrocardiographic data can be expected to be more useful. In this study, we investigate the estimation of physical activity. For the better analysis, we evaluated activity estimation using machine learning as well as several different feature extractions. In this report, we will show several different feature extraction methods and result of human body analysis using machine learning.","PeriodicalId":90726,"journal":{"name":"Signal and image processing : an international journal","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89920634","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: 1

Test-cost-sensitive Convolutional Neural Networks with Expert Branches 具有专家分支的测试代价敏感卷积神经网络

Signal and image processing : an international journal Pub Date : 2019-10-31 DOI: 10.5121/sipij.2019.10502

Mahdi Naghibi, R. Anvari, A. Forghani, B. Minaei

引用次数: 0

Robust Image Watermarking Method using Wavelet Transform 基于小波变换的鲁棒图像水印方法

Signal and image processing : an international journal Pub Date : 2019-10-31 DOI: 10.5121/sipij.2019.10503

Omar Y. Adwan

引用次数: 0

The Study on Electromagnetic Scattering Characteristics of Jonswap Spectrum Sea Surface Jonswap谱海面电磁散射特性研究

Signal and image processing : an international journal Pub Date : 2019-08-31 DOI: 10.5121/sipij.2019.10401

X. Mi, Xiaobing Wang, Xinyi He, F. Dai

{"title":"The Study on Electromagnetic Scattering Characteristics of Jonswap Spectrum Sea Surface","authors":"X. Mi, Xiaobing Wang, Xinyi He, F. Dai","doi":"10.5121/sipij.2019.10401","DOIUrl":"https://doi.org/10.5121/sipij.2019.10401","url":null,"abstract":"The JONSWAP spectrum sea surface is mainly determined by parameters such as the wind speed, the fetch length and the peak enhancement factor. In view of the study of electromagnetic scattering from JONSWAP spectrum sea surface, we need to determine the above parameters. In this paper, we use the double summation model to generate the multi-directional irregular rough JONSWAP sea surface and analyze the distribution concentration parameter and the peak enhancement factor’s influence on the rough sea surface model, then using physical optics method to analysis the JONSWAP spectrum sea surface’s average backward scattering coefficient change with the different distribution concentration parameters and the peak enhancement factors, the simulation results show that the peak enhancement factor influence on the ocean surface of the average backward scattering coefficient is less than 1 dB, but the distribution concentration parameter influence on the JONSWAP surface of the average backward scattering coefficient is more than 5 dB. Therefore, when we study the electromagnetic scattering of the JONSWAP spectral sea surface, the peak enhancement factor can be taken as the mean value but the distribution concentration parameter have to be determined by the wave growth state.","PeriodicalId":90726,"journal":{"name":"Signal and image processing : an international journal","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87143935","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

Ransac Based Motion Compensated Restoration for Colonoscopy Images 基于Ransac的结肠镜图像运动补偿恢复

Signal and image processing : an international journal Pub Date : 2019-08-31 DOI: 10.5121/sipij.2019.10402

Nidhal Azawi, J. Gauch

{"title":"Ransac Based Motion Compensated Restoration for Colonoscopy Images","authors":"Nidhal Azawi, J. Gauch","doi":"10.5121/sipij.2019.10402","DOIUrl":"https://doi.org/10.5121/sipij.2019.10402","url":null,"abstract":"Colonoscopy is a procedure that has been used widely to detect the abnormality in a colon. Colonoscopy images suffer from a lot of problems that make it hard for the doctor to investigate/ understand a colon patient. Unfortunately, with the current technology, three is no way for doctors to know if the whole colon surface has been investigated or not. We have developed a method that utilizes RANSAC-based image registration to align sequences of any length in the colonoscopy video and restores each frame of the video using information from these aligned images. We proposed two methods. First method used the deep neural net for the classification of informative and non-informative image. The classification result was used as a preprocessing for alignment method. Also, we proposed a visualization structure for the classification results. The second method used the alignment to decide/classify the bad and good alignment by using two factors. The first factor is the accumulated error and the second factor contain three checking steps that check the pair error alignment beside the geometry transform status. The second method was able to align long sequences.","PeriodicalId":90726,"journal":{"name":"Signal and image processing : an international journal","volume":"154 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74498956","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

Machine-Learning Estimation of Body Posture and Physical Activity by Wearable Acceleration and Heartbeat Sensors 基于可穿戴加速和心跳传感器的身体姿势和身体活动的机器学习估计

Signal and image processing : an international journal Pub Date : 2019-06-30 DOI: 10.5121/SIPIJ.2019.10301

Y. Yoshida, E. Yuda, Kento Yamamoto, Yutaka Miura, J. Hayano

引用次数: 3

Application of A Computer Vision Method for Soiling Recognition in Photovoltaic Modules for Autonomous Cleaning Robots 计算机视觉方法在自主清洁机器人光伏组件污垢识别中的应用

Signal and image processing : an international journal Pub Date : 2019-06-29 DOI: 10.5121/SIPIJ.2019.10305

Tatiani Pivem, Felipe de Oliveira de Araujo, Laura de Oliveira de Araujo, Gustavo Spontoni de Oliveira

引用次数: 7

Method for the Detection of Mixed QPSK Signals Based on the Calculation of Fourth-Order Cumulants 基于四阶累积量计算的混合QPSK信号检测方法

Signal and image processing : an international journal Pub Date : 2019-06-29 DOI: 10.5121/SIPIJ.2019.10302

V. Semenov, P. Omelchenko, O. Kruhlyk

引用次数: 0

A Novel Data Dictionary Learning for Leaf Recognition 一种新的树叶识别数据字典学习方法

Signal and image processing : an international journal Pub Date : 2019-06-29 DOI: 10.5121/SIPIJ.2019.10304

S. Ibrahem, Y. M. A. El-Latif, Naglaa M. Reda

引用次数: 1