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saliency detection of infrared image based on region covariance and global feature

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Journal of Systems Engineering and Electronics 2018年第3期29卷 483-490页

作者： LIU Songtao JIANG Ning LIU Zhenxing JIANG Kanghui Department of Information Operation Dalian Naval Academy

In order to better represent infrared target features under different environments, a saliency detection method based on region covariance and global feature is proposed. Firstly, the region covariance features on different scale spaces and different image regions are extracted and transformed into sigma features,then combined with central position feature, the local salient map is generated. Next, a global salient map is generated by gray contrast and density estimation. Finally, the saliency detection result of infrared images is obtained by fusing the local and global salient maps. The experimental results show that the salient map of the proposed method has complete target features and obvious edges,and the proposed method is better than the state of art method both qualitatively and quantitatively.

关键词： saliency detection region covariance gray contrast density estimation

saliency detection based on superpixels clustering and stereo disparity

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Applied Mathematics(A Journal of Chinese Universities) 2016年第1期31卷 68-80页

作者： GAO Shan-shan CHI Jing LI Li ZOU Ji-biao ZHANG Cai-ming School of Computer Science and Technology Shandong University of Finance and Economics Jinan 250014 China School of Computer Science and Technology Shandong University Jinan 250100 China. Shandong Provincial Key Laboratory of Digital Media Technology Jinan 250014 China.

Reliable saliency detection can be used to quickly and effectively locate objects in images. In this paper, a novel algorithm for saliency detection based on superpixels clustering and stereo disparity （SDC） is proposed. Firstly, we use an improved superpixels clustering method to decompose the given image. Then, the disparity of each superpixel is computed by a modified stereo correspondence algorithm. Finally, a new measure which combines stereo disparity with color contrast and spatial coherence is defined to evaluate the saliency of each superpixel. From the experiments we can see that regions with high disparity can get higher saliency value, and the saliency maps have the same resolution with the source images, objects in the map have clear boundaries. Due to the use of superpixel and stereo disparity information, the proposed method is computationally efficient and outperforms some state-of-the-art color- based saliency detection methods.

关键词： saliency detection superpixels stereo disparity spatial coherence.

saliency detection via Manifold Ranking Based on Robust Foreground

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International Journal of Automation and computing 2021年第1期18卷 73-84页

作者： Wei-Ping Ma Wen-Xin Li Jin-Chuan Sun Peng-Xia Cao Lanzhou Institute of Physics China Academy of Space TechnologyLanzhou 730000China

The graph-based manifold ranking saliency detection only relies on the boundary background to extract foreground seeds,resulting in a poor saliency detection result,so a method that obtains robust foreground for manifold ranking is proposed in this ***,boundary connectivity is used to select the boundary background for manifold ranking to get a preliminary saliency map,and a foreground region is acquired by a binary segmentation of the ***,the feature points of the original image and the filtered image are obtained by using color boosting Harris corners to generate two different convex *** the intersection of these two convex hulls,a final convex hull is ***,the foreground region and the final convex hull are combined to extract robust foreground seeds for manifold ranking and getting final saliency *** results on two public image datasets show that the proposed method gains improved performance compared with some other classic methods in three evaluation indicators:precision-recall curve,F-measure and mean absolute error.

关键词： saliency detection manifold ranking boundary connectivity convex hull robust foreground

Hierarchical Visual Attention Model for saliency detection Inspired by Avian Visual Pathways

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IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 540-552页

作者： Xiaohua Wang Haibin Duan the State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University the State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University the Peng Cheng Laboratory

Visual attention is a mechanism that enables the visual system to detect potentially important objects in complex environment. Most computational visual attention models are designed with inspirations from mammalian visual ***, electrophysiological and behavioral evidences indicate that avian species are animals with high visual capability that can process complex information accurately in real time. Therefore,the visual system of the avian species, especially the nuclei related to the visual attention mechanism, are investigated in this paper. Afterwards, a hierarchical visual attention model is proposed for saliency detection. The optic tectum neuron responses are computed and the self-information is used to compute primary saliency maps in the first hierarchy. The "winner-takeall" network in the tecto-isthmal projection is simulated and final saliency maps are estimated with the regularized random walks ranking in the second hierarchy. Comparison results verify that the proposed model, which can define the focus of attention accurately, outperforms several state-of-the-art *** study provides insights into the relationship between the visual attention mechanism and the avian visual pathways. The computational visual attention model may reveal the underlying neural mechanism of the nuclei for biological visual attention.

关键词： Avian visual pathways bio-inspired saliency detection visual attention

Seismic Attribute Analysis with saliency detection in Fractional Fourier Transform Domain

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Journal of Earth Science 2018年第6期29卷 1372-1379页

作者： Yuqing Wang Zhenming Peng Yan Han Yanmin He School of Optoelectronic Information University of Electronic Science and Technology of China Center for Information Geoscience University of Electronic Science and Technology of China

Most image saliency detection models are dependent on prior knowledge and demand high computational cost. However, spectral residual（SR） and phase spectrum of the Fourier transform（PFT） models are simple and fast saliency detection approaches based on two-dimensional Fourier transform without the prior knowledge. For seismic data, the geological structure of the underground rock formation changes more obviously in the time direction. Therefore, one-dimensional Fourier transform is more suitable for seismic saliency detection. Fractional Fourier transform（FrFT） is an improved algorithm for Fourier transform, therefore we propose the seismic SR and PFT models in one-dimensional FrF T domain to obtain more detailed saliency maps. These two models use the amplitude and phase information in FrFT domain to construct the corresponding saliency maps in spatial domain. By means of these two models, several saliency maps at different fractional orders can be obtained for seismic attribute analysis. These saliency maps can characterize the detailed features and highlight the object areas, which is more conducive to determine the location of reservoirs. The performance of the proposed method is assessed on both simulated and real seismic data. The results indicate that our method is effective and convenient for seismic attribute extraction with good noise immunity.

关键词： saliency detection spectral residual phase spectrum fractional Fourier transform (FrFT) attribute extraction seismic data

A Visual saliency detection Algorithm Based on Channel Selecting in Transform Domains 26th

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A Visual Saliency Detection Algorithm Based on Channel Selec...

Drogue detection for autonomous aerial refueling via hybrid pigeon-inspired optimized color opponent and saliency aggregation

第26届中国控制与决策会议

作者： Shen Yifeng Niu Yifeng Shen Lincheng College of Mechatronics Engineering and Automation National University of Defense Technology

ISBN: (纸本)9781479937097

A transform domain algorithm using channel selecting is proposed for visual saliency in this paper. This algorithm is able to improve the accuracy of the traditional transform domain saliency detection while preserving their advantage of fast processing speed. Based on the image signature algorithm, we select the channels by calculating the correlation values between each channel. Then, the selected channels, instead of all of the channels, are combined for the final saliency map according to the corresponding combination rule which we designed. The experimental comparison between the proposed and original approaches demonstrates that our method is higher in accuracy while maintaining high processing speed.

关键词： saliency detection Transform Domain Image Signature Channel Selecting

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Chinese Journal of Aeronautics 2024年第5期37卷 27-38页

作者： Tongyan WU Haibin DUAN Yanming FAN State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China AVIC Shenyang Aircraft Design and Research Institute Shenyang 110035China

Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and *** detection based on image intrinsic cues can achieve fast detection,but with poor *** studies reveal that optimization-based methods provide accurate and quick solutions for saliency *** paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue *** can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and *** results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic *** algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.

关键词： Autonomous aerial refueling Drones Hybrid pigeon-inspired optimization Color opponent saliency detection saliency aggregation

Biological Eagle-eye Inspired Target detection for Unmanned Aerial Vehicles Equipped with a Manipulator

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Machine Intelligence Research 2023年第5期20卷 741-752页

作者： Yi-Min Deng Si-Yuan Wang School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Inspired by eagle eye mechanisms,the structure and information processing characteristics of the eagle′s visual system are used for the target capture task of an unmanned aerial vehicle(UAV)with a mechanical *** this paper,a novel eagle-eye inspired multi-camera sensor and a saliency detection method are proposed.A combined camera system is built by simulating the double fovea structure on the eagle retina.A saliency target detection method based on the eagle midbrain inhibition mechanism is proposed by measuring the static saliency information and dynamic ***,salient targets can be accurately detected through the collaborative work between different cameras of the proposed multi-camera *** results show that the eagle-eye inspired visual system is able to continuously detect targets in outdoor scenes and that the proposed algorithm has a strong inhibitory effect on moving background interference.

关键词： Unmanned aerial vehicle(UAV) eagle eye multi-camera sensor target detection saliency detection

A saliency Based Image Fusion Framework for Skin Lesion Segmentation and Classification

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Computers, Materials & Continua 2022年第2期70卷 3235-3250页

作者： Javaria Tahir Syed Rameez Naqvi Khursheed Aurangzeb Musaed Alhussein Department of Computer Science COMSATS University IslamabadIslamabad CampusPakistan Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusPakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

Melanoma,due to its higher mortality rate,is considered as one of the most pernicious types of skin cancers,mostly affecting the white *** has been reported a number of times and is now widely accepted,that early detection of melanoma increases the chances of the subject’s ***-aided diagnostic systems help the experts in diagnosing the skin lesion at earlier stages using machine learning *** thiswork,we propose a framework that accurately segments,and later classifies,the lesion using improved image segmentation and fusion *** proposed technique takes an image and passes it through two methods simultaneously;one is the weighted visual saliency-based method,and the second is improved HDCT based saliency *** resultant image maps are later fused using the proposed image fusion technique to generate a localized lesion *** resultant binary image is later mapped back to the RGB image and fed into the Inception-ResNet-V2 pre-trained model-trained by applying transfer *** simulation results show improved performance compared to several existing methods.

关键词： Skin lesion segmentation image fusion saliency detection skin lesion classification deep neural networks transfer learning