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Adaptive Small Target Detection Based on Least Squares and Human visual System

Adaptive Small Target Detection Based on Least Squares and H...

引用

2017 17th IEEE International conference on Communication Technology (ICCT 2017)

作者： Linna Yang Bei Jia Qiang Liu Xi'an Communications Institute

The detection of small target in sequential images is an importance part of infrared technology. Sequential images with heavy cutter is vulnerable to influences such as mismatch and stray light of the sun, which can lower the detection ***, adaptive small target detection based on least squares and human visual system is proposed in this ***, weighted coefficient for each frame and the minimum residual image are calculated by least squares algorithm. Then a contrast value is weighted to residual image according to the principle of extensive human visual system. Experimental evaluation results show that, the proposed method has better adaptability, when sequential images with heavy clutter is influenced by mismatch or stray light of the sun. And compared with median filtering, the proposed method has higher detection rate and lower false alarm rate.

关键词： small target detection least squares human visual system adaptive image processing

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O(1) Contrast Preserving Decolorization Using Linear Local Mapping 8

<i>O</i>(1) Contrast Preserving Decolorization Using Linear ...

引用

8th International conference on Wireless communications and Signal processing (WCSP)

作者： Song, Yibing Gong, Lijun City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China SenseNets Corp Ctr Res & Dev Shenzhen Peoples R China

ISBN: (纸本)9781509028603

We propose an effective and efficient local decolorization method in this paper. It is an extension of the global decolorization method [6] which robustly reproduces visual appearance of a color image in the grayscale output. The improvement of the local extension is the effective preservation of the local color contrast which may diminish in the global method. Meanwhile the proposed local extension is efficient in that the computational complexity is O(1) for each pixel, which will be independent of the local kernel size. Quantitative evaluation among existing decolorization methods shows that our local extension performs favorable in both image quality and time cost. Meanwhile, our method can be extended into temporal domain for robust video decolorization.

关键词： image decolorization

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Diffraction as a Resolution Enhancer visual Hyperacuity Simulation Method 22

Diffraction as a Resolution Enhancer Visual Hyperacuity Simu...

引用

22nd International conference on Applied Electromagnetics and communications (ICECOM)

作者： Lagunas, Adur Dominguez, Oier del Rio, Carlos Univ Publ Navarra Elect & Elect Engn Dept Antenna Grp Pamplona Spain

ISBN: (纸本)9789536037728

visual hyperacuity is the capability of the human eye to see beyond the acuity defined by the number and size of its photo receptors. Optical imaging systems suffer from diffraction since light passes through an aperture and a lens system. Common diffraction-limited devices are designed to limit this effect and capture a sharp image. Nevertheless, the human eye produces a noteworthy diffraction effect which exceeds these limits, projecting a blurred image over the retina, where photo receptors are located. On this basis, it seems difficult to understand it operating as a diffraction-limited system. Assuming that diffraction could be helpful to achieve visual hyperacuity, we present a method that intend to simulate and explain it: introducing a controlled diffraction, we are able to enhance the image resolution using post-processing techniques as interpolation and inverse filtering. Our approach uses diffraction to improve image resolution when captured with a reduced number of sensors, far from being a limiting factor.

关键词： diffraction image processing image resolution inverse problems

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Video action classification by deep learning

Video action classification by deep learning

引用

IEEE Signal processing and communications Applications (SIU)

作者： Esra Ergün Filiz Gürkan Onur Kaplan Bilge Günsel Çoğulortam ışaret İşleme ve Örüntü Tanıma Grubu İstanbul Teknik Üniversitesi İstanbul Türkiye

ISBN: (纸本)9781509064953

The purpose of this study is learning and classification of video activities using video color and motion information. The video activity labeling is important for many applications such as video content modeling, indexing, and quick access to content. In this study video activity recognition is performed by deep learning. In order to learn visual features of video, Convolutional Neural Network (CNN) layers and a special type of recursive networks, Long-Short Term Memory (LSTM), layers are stacked. Video sequence learning is performed by end-to-end training. Recent works on deep learning employ color end motion information together to improve learning and classification accuracy. In this study, unlike the existing models, video motion content is learned using SIFT flow vectors and motion and color features are fused for activity recognition. Performance tests performed on a commonly used benchmarking data set, UCF 101 which includes activity labeled videos from 101 action categories such as "Biking", "Playing Guitar," demonstrate that SIFT flow vectors allow us to model motion information more accurately than optical flow vectors and increase video motion classification performance.

关键词： Machine learning Art Neural networks image color analysis Activity recognition image motion analysis Computer vision

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Coupled shape priors for dynamic segmentation of dendritic spines

Coupled shape priors for dynamic segmentation of dendritic s...

引用

IEEE Signal processing and communications Applications (SIU)

作者： Naeimeh Atabakilachini Ertunc Erdil A. Ozgur Argunsah Lavdie Rada Devrim Unay Mujdat Cetin Faculty of Engineering and Natural Sciences Sabanci University Istanbul Turkey Zurich University Institute of Brain Research Zurich Switzerland Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Department of Biomedical Engineering Izmir Economy University Izmir Turkey

ISBN: (纸本)9781509064953

Segmentation of biomedical images is a challenging task, especially when there is low quality or missing data. The use of prior information can provide significant assistance for obtaining more accurate results. In this paper we propose a new approach for dendritic spine segmentation from microscopic images over time, which is motivated by incorporating shape information from previous time points to segment a spine in the current time point. In particular, using a training set consisting of spines in two consecutive time points to construct coupled shape priors, and given the segmentation in the previous time point, we can improve the segmentation process of the spine in the current time point. Our approach has been evaluated on 2-photon microscopy images of dendritic spines and its effectiveness has been demonstrated by both visual and quantitative results.

关键词： Shape image segmentation Microscopy visualization Training Manuals Neck

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Generating Structure-Aware Compositional Sketches for Simultaneous Object Retrieval and Localization 8

Generating Structure-Aware Compositional Sketches for Simult...

引用

8th International conference on Wireless communications and Signal processing (WCSP)

作者： Zhang, Dongyu Xiao, Tianfang Li, Xiying Sun Yat Sen Univ Guangzhou Guangdong Peoples R China Zhejiang Univ Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781509028603

This paper introduces a simple yet effective retrieval framework for object retrieval and localization. Our method is based on min-Hash method using compositional structure preserved object representation. Compared to the traditional hash-based Content-based image retrieval (CBIR) system which always suffers from low recall due to insufficient discriminability of image representations, our method contributes in the following three terms: firstly, a new image feature, namely Pair of Geometric Coupled Words (PGCW), is presented to impose spatial context into visual words and generate very discriminative hash functions. Secondly, we select a batch of hashing functions by learning from a number of supervised retrievals. The sketches are then generated by selecting the hashing functions from the constructed object model. Finally, in the step of hash sketches matching, we introduce an auxiliary offset space, in which the object localization can be estimated by clustering. Our approach valids on popular public image databases and outperforms stateof-the-art methods.

关键词： Large-Scale image Retrieval Object localization Ranking

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image Quality Assessment Based on the visual Perception of image Contents

Image Quality Assessment Based on the Visual Perception of I...

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30th IEEE conference on visual communications and image processing (VCIP)

作者： Yao, Juncai Liu, Guizhong Ying, Chen Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China Shaanxi Sci Tech Univ Sch Phys & Telecommun Engn Hanzhong 723000 Peoples R China

ISBN: (纸本)9781509053162

This paper describes an image quality assessment (IQA) metric based on the visual perception of image contents (VPIC). In the metric, VPIC is firstly modelled by simulating the nonlinearity of luminance perception, masking properties and contrast sensitivity characteristics of human visual system (HVS). Then the source and distorted images are processed by this model respectively, and their intensity differences are calculated. Finally, based on the intensity differences, an IQA model is built. And 47 reference images and 1549 distorted images in the LIVE, TID2008 and CSIQ databases are tested with the IQA metric. The results show that it is helpful to improve the consistency between the objective IQA scores and the subjective mean opinion scores (MOSs) combining the visual perception and complexity of image contents.

关键词： image quality assessment visual perception contrast image contents correlation coefficient

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A Review on Feature Extraction Techniques in Content Based image Retrieval

A Review on Feature Extraction Techniques in Content Based I...

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IEEE International conference on Wireless communications, Signal processing and Networking (WiSPNET)

作者： Patel, Jigisha M. Gamit, Nikunj C. Uka Tarsadia Univ CGPIT Dept Comp Engn Bardoli India

ISBN: (纸本)9781467393379

The Content Based image retrieval (CBIR) is a very important for retrieving the most visual relevant images from the large image database. The various low level features are extracted based on their visual content which are color, shape, texture etc. The paper gives the overview of color and texture feature extraction techniques like color histogram, color correlogram, color co-occurrence matrix and tamura texture feature, steerable pyramid, wavelet transform, Gabor wavelet transform respectively and also the comparative analysis of this techniques is shown in the paper.

关键词： CBIR feature extraction color histogram color correlogram DCD CCM tamura feature wavelet transform GWT

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Investigation of Mobile Surroundings for visual Attention Based on image Perception Model

Investigation of Mobile Surroundings for Visual Attention Ba...

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30th IEEE conference on visual communications and image processing (VCIP)

作者： Chen, Jiazhong Li, Yizhang Fan, Yebin Wu, Weimin Wang, Xian Cao, Hua Chen, Yang Huazhong Univ Sci & Technol Sch Comp Wuhan Peoples R China China Mobile Hubei Branch Wuhan Peoples R China Fujian Chuanzheng Commun Coll Dept Informat Technol Fuzhou Peoples R China

ISBN: (纸本)9781509053162

This paper presents a novel perspective of performance evaluation for visual attention estimation: how the saliency models perform in mobile conditions. In particular, a broad-spectrum contrast sensitivity function is firstly proposed in this work. Based on this function, a new visual perception model is established, which will be further used to simulate the image perception in various mobile circumstances. Then the influence caused by mobile surroundings for visual attention is investigated. Meanwhile three types of mobile ground truth are generated by collecting viewers' fixations in three typical mobile conditions. Finally, by the perception model and mobile ground truth, an evaluation for ten classical visual attention models in various mobile surroundings is presented.

关键词： Mobile environment contrast sensitivity function visual attention saliency detection

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Improving mesh-based motion compensation by using edge adaptive graph-based compensated wavelet lifting for medical data sets

Improving mesh-based motion compensation by using edge adapt...

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IEEE International conference on Acoustics, Speech and Signal processing

作者： Daniela Lanz Andre Kaup Multimedia Communications and Signal Processing Friedrich-Alexander-Universitat Erlangen-Nurnberg (FAU) Cauerstr. 7 91058 Germany

ISBN: (纸本)9781509041183

Medical applications like Computed Tomography (CT) or Magnetic Resonance Tomography (MRT) often require an efficient scalable representation of their huge output volumes in the further processing chain of medical routine. A downscaled version of such a signal can be obtained by using image and video coders based on wavelet transforms. The visual quality of the resulting lowpass band, which shall be used as a representative, can be improved by applying motion compensation methods during the transform. This paper presents a new approach of using the distorted edge lengths of a mesh-based compensated grid instead of the approximated intensity values of the underlying frame to perform a motion compensation. We will show that an edge adaptive graph-based compensation and its usage for compensated wavelet lifting improves the visual quality of the lowpass band by approximately 2.5 dB compared to the traditional mesh-based compensation, while the additional filesize required for coding the motion information doesn't change.

关键词： Discrete Wavelet Transforms Motion Compensation Scalability Signal processing on Graphs Computed Tomography Motion compensation discrete wavelet transform Scalability X-Ray Computed Tomography compensated wavelets video coder lift lifts Edge of a figure or solid

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