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A Modified Structural Similarity Index with Low computational Complexity

A Modified Structural Similarity Index with Low Computationa...

引用

ieee International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Woei-Tan Loh David Boon Liang Bong Faculty of Engineering Universiti Malaysia Sarawak Kota Samrahan Malaysia

Structural Similarity Index (SSIM) has been a benchmark method for image quality assessment (IQA). This is due to its simplicity and good performance. In this paper, we propose a modified SSIM method that reduces the computational complexity with comparable performance. Instead of computing similarities on local windows, the proposed method computes global information similarities. The proposed method omits the luminance part similarities in SSIM due to its less crucial role in assessing image quality. From the presented results, the proposed method has a much lower computational time and comparable performance compared to SSIM.

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Flocculation Effect Detection of Chemical Wastewater Based on image processing 11

Flocculation Effect Detection of Chemical Wastewater Based o...

引用

11th International symposium on computational intelligence and Design (ISCID)

作者： Rong, Huang Chen Li, Tang Jia Nanjing Inst Technol Sch Comp Engn Nanjing Jiangsu Peoples R China Jiangsu Univ Technol Coll Comp Engn Changzhou Peoples R China

ISBN: (纸本)9781538685273

With the image correction technology, a deep study and analysis was performed on the mutual relationships among a series of key parameters, including the coagulant dosage and the equivalent diameter, fractal dimension and concentration characteristics of the flocculation image, in the correction process of the chemical wastewater. Considering the actual operation environment and the real-time requirements of automatic dosing control, the Retinex algorithm was adopted in this article to solve the problems of uneven light distribution occurring in the process of experiment. In addition, another algorithm, the simple algorithm, was also applied to the calculation in the link of image correction, so as to shrink the program scale. According to the simulation results, it was indicated that the simulation operation was of relatively good practicability in the practical automatic control.

关键词： chemical wastewater correction flocculation image correction uneven illumination real time

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signal and image processing and computational intelligence

Signal and Image Processing and Computational Intelligence

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ieee International Conference on Industrial Technology (ICIT)

Start of the above-titled section of the conference proceedings record.

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Fast Laplacian of Gaussian Edge Detection Algorithm for Quantum images

Fast Laplacian of Gaussian Edge Detection Algorithm for Quan...

引用

ieee International symposium on Parallel and Distributed processing with Applications and ieee International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Suzhen Yuan Salvador E. Venegas-Andraca Chaoping Zhu Yan Wang Xuefeng Mao Yuan Luo College of opto electronic engineering Chongqing University of Posts and Telecommunications Chongqing China Escuela de Ingenieria y Ciencias Tecnologico de Monterrey Mexico Mexico School of Artificial Intelligence Chongqing Technology and Business University Chongqing China

ISBN: (纸本)9781728152103

Quantum image processing, which is the application of quantum theory in image processing, has attracted increasing attention in recent years. In this paper, we propose a framework of Laplacian of Gaussian (LoG) edge detection algorithm for quantum images. The LoG is commonly employed as a second-order edge detector in image processing. Firstly, discrete LoG mask is obtained from the continuous Gaussian operator within certain detection error. Secondly, filter the quantum image with the LoG mask. Thirdly, to obtain the edge image, the searching for zero-crossing point of the filtered image is proposed. Finally, the time complexity is analyzed, which shows that this quantum LoG operator has polynomial-time complexity.

关键词： computational complexity edge detection Gaussian processes image filtering Laplace equations quantum computing complexity classes Laplace's equation image filtering Edge detection Gaussian processes quantum computing boundary detection algorithm Laplacian operator image processing edge image quanta logs logarithm (log) Error detection Gauss

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GPU Usage trends in Medical image processing

GPU Usage trends in Medical Image processing

引用

International symposium on Applied computational intelligence and Informatics ( SACI)

作者： Abdallah BENHAMIDA Miklos KOZLOVSZKY Sándor SZÉNÁSI BioTech Research Center EKIK Óbuda University Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Budapest Hungary

ISBN: (数字)9781728106861

ISBN: (纸本)9781728106878

Graphics processing units (GPUs), mainly named as general-purpose computing on graphics processing units (GPGPUs) became a widely used technology for many computer-aided procedures in different research or industry areas that require high algorithmic computation capabilities for parallel computing tasks. In the field of bioinformatics and especially in medical image processing, GPUs play an essential role to enable high performance and computation capabilities in order to facilitate the tasks related to image processing. This paper highlights the usage of the graphics processing units in medical image processing and three-dimensional medical image processing related applications (computer-aided image processing, volume rendering, and segmentation), such as image segmentation, noise reduction or denoising, and image registration. It gives a deep understanding of the influence of GPU cards on general purpose programming GPGPU in general and on medical image processing specifically. It presents a good starting point for further applications of GPU programming in the field of biomedical applications and mainly for medical image processing that requires high-performance capabilities for medical image treatment shortly after the medical imaging activity such as in the ICU or the emergency services.

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Object Tracking Based on Deep CNN Features Together with Color Features and Sparse Representation

Object Tracking Based on Deep CNN Features Together with Col...

引用

ieee symposium Series on computational intelligence (SSCI)

作者： Yuchi Liu Yujuan Qi Yanjiang Wang College of Control Science and Engineering China University of Petroleum(East china) Qingdao China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

To acquire the better object tracking performance in this paper, the object of interest is modeled by its RGB-color histogram feature together with deep convolutional neural network feature (deep CNN feature) and sparse representation. Because the information of the objects of interest cannot be obtained ahead in practical use, the deep CNN features should be abstracted through the pre-trained VGG network. Then the deep feature and RGB-color histogram are combined to model the object in adaptive mode. And then sparse representation is used to express the model. Above all, an adaptive particle filter algorithm based on deep CNN feature together with RGB-color feature and sparse representation is proposed to track the object of interest. Extensive experiment results demonstrate the effectiveness of our proposed method under the serious object occlusions and appearance changes.

关键词： Particle filters Feature extraction Object tracking Target tracking image color analysis signal processing algorithms Robustness

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Feature Extraction with computational intelligence for Head Pose Estimation 8

Feature Extraction with Computational Intelligence for Head ...

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8th ieee symposium Series on computational intelligence (ieee SSCI)

作者： Reid, Shane Coleman, Sonya Kerr, Dermot Vance, Philip O'Neill, Siobhan Ulster Univ Magee Coll Sch Comp Engn & Intelligent Syst Coleraine Londonderry North Ireland Ulster Univ Magee Coll Sch Psychol Coleraine Londonderry North Ireland

ISBN: (纸本)9781538692769

Measuring social signals has often proved challenging as they are often characterized by subtle movements which are difficult to detect. Head pose is one such social signal used to indicate where an individual's attention is focused. This paper will discuss the problem of head pose estimation by defining the problem in terms of two fields of view, pan and tilt. A novel approach for head pose estimation is described that uses histogram of oriented gradients with support vector machines. The approach is compared with a template matching approach, among others, using a well-known dataset. The results show that the histogram of oriented gradients approach is able to determine head pan to within one class approximately 72% of the time, and head tilt to within one class approximately 71% of the time.

关键词： Head Pose estimation Template matching Social signal processing Histogram of oriented gradients Support vector machine

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Interactive Evolutionary Parameter Optimization for Eulerian Video Magnification 8

Interactive Evolutionary Parameter Optimization for Eulerian...

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8th ieee symposium Series on computational intelligence (ieee SSCI)

作者： Rizvi, Syed Raazi Rahnamayan, Shahryar UOIT Dept Elect Comp & Software Engn Nat Inspired Computat Intelligence NICI Lab Oshawa ON Canada

ISBN: (纸本)9781538692769

This paper explores control parameter tuning for the Eulerian Video Magnification (EVM) process using a pair comparison-based interactive differential evolution (PCB-IDE) algorithm. Interactive evolutionary optimizers have a history of being applied to video/image post-processing tasks because assessing the quality of video data is objectively difficult without subjective assessment by users. The EVM technique magnifies motion and color variations within a video in a manner similar to a visual microscope. Applying EVM to video sequences allows the observation of known physical phenomenon by using only video data, which is critical to development of camera based monitoring applications. The proposed PCB IDE assists experts in determining the optimal parameters for EVM process to better identify visual changes and correlate them to physical phenomenons.

关键词： Eulerian Video Magnification Parameter Estimation Video Post-processing Interactive Differential Evolution

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Identification of functional states of the cardiovascular system according to flowmetry data using machine learning methods 11

Identification of functional states of the cardiovascular sy...

引用

11th International symposium on computational intelligence and Design (ISCID)

作者： Sergeevna, Konnova Natalia Alekseevich, Basarab Mikhail Bauman Moscow State Tech Univ Informat Secur Dept Moscow Russia Bauman Moscow State Tech Univ Theoret Informat & Comp Technol Moscow Russia

ISBN: (纸本)9781538685273

The aim of this work is to analyze the applicability of machine learning methods to the problems of diagnosing on the cardiovascular system data and develop a novel technique for automating this process to support decision making in cardiology. Here, the results obtained with the help of classifiers based on random decision forests are examined, and a proprietary numerical experiment is performed with the Doppler flowmetry data. Considerable attention is paid to data processing and reduction of the input vector dimension for analysis.

关键词： machine learning random forest diagnostics of the cardiovascular system state decision support system digital signal processing Doppler flowmetry

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Gaussian Noise Removal of Blind Source Separation Based on image Sequence 11

Gaussian Noise Removal of Blind Source Separation Based on I...

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11th International symposium on computational intelligence and Design (ISCID)

作者： Dong, Shijia Yu, Chunyu Sun, Bin Nanjing Univ Posts & Telecommun Coll Elect & Opt Engn Nanjing Peoples R China Nanjing Univ Posts & Telecommun Coll Microelect Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Automat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538685273

This paper proposes a noise reduction method of blind source separation based on image sequence. In the image, the signal and the noises can be considered as the independent components, so the multi-frame images can be considered as the multiple linear combinations of one signal and a lot of noises for the noise's randomness. Due to that, the noises can be removed from the sampled multi-images based on blind source separation (BSS). During the separation calculation, the common Gaussian noise is taken as the object to be eliminated, and the nonlinear principal component analysis (NLPCA) is used as the BSS method and the analysis of the noise reduction is based on changing either the noise degree or the image sampling numbers. This proposed algorithm is compared with the multi-frame average (MFA) that is a famous noise reduction algorithm based on image sequence. The analysis results show that the noise reduction properties by using the proposed method will be affected by the noise degree or the image sampling numbers when eliminating the Gaussian noise;and this method can recover the images which are heavily noise polluted, and the suppression effect on strong noises is obviously better than MFA algorithm.

关键词： image noise reduction image sequence blind source separation principal component analysis multi-frame averaging

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