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

作者： Sae-Tang, Wannida Fujiyoshi, Masaaki Kiya, Hitoshi Tokyo Metropolitan Univ Dept Informat & Commun Syst Tokyo 1910065 Japan

ISBN: (纸本)9781479961207

In this paper, an effective data hiding method for encrypted JPEG 2000 codestreams is proposed. By using the property of the discrete wavelet transformation (DWT), an image is visually encrypted: multiplying random signs to the discrete wavelet transformed (DWTed) coefficients of the image, where the image is also compressed in the DWTed domain by JPEG 2000. In addition, data hiding is performed in the DWTed domain as well. It provides a number of possible applications;the hidden data may be extracted and then the original image is recovered, or the codestreams is directly decoded and decrypted to get the image containing the hidden data. Experimental results show that the proposed method is efficient in terms of visual protection, quality of decrypted images containing the hidden data, and hidden data extraction.

关键词： Perceptual encryption reversible data hiding privacy protection image compression

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computational Snapshot Multispectral Cameras Toward dynamic capture of the spectral world

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ieee signal processing MAGAZINE 2016年第5期33卷 95-108页

作者： Cao, Xun Yue, Tao Lin, Xing Lin, Stephen Yuan, Xin Dai, Qionghai Carin, Lawrence Brady, David J. Nanjing Univ Sch Elect Sci & Engn Nanjing Jiangsu Peoples R China Stanford Univ Dept Biol Howard Hughes Med Inst Stanford CA 94305 USA Microsoft Res Internet Graph Grp Beijing Peoples R China Int Conf Comp Vis 2011 Beijing Peoples R China Pacific Rim Symposium Image & Video Technol 2009 Beijing Peoples R China Bell Labs Murray Hill NJ USA Duke Univ Dept Elect & Comp Engn Durham NC 27706 USA Tsinghua Univ Dept Automat Beijing Peoples R China Polytech Univ Dept Elect Engn Brooklyn NY 11201 USA Dept Elect Commun Engn Brooklyn NY USA Duke Univ Durham NC 27706 USA IEEE Washington DC USA Duke Univ Elect & Comp Engn Durham NC 27706 USA Duke Kunshan Univ Suzhou Peoples R China Univ Illinois Chicago IL 60680 USA SPIE Bellingham WA USA

Multispectral cameras collect image data with a greater number of spectral channels than traditional trichromatic sensors, thus providing spectral information at a higher level of detail. Such data are useful in various fields, such as remote sensing, materials science, biophotonics, and environmental monitoring. The massive scale of multispectral data-at high resolutions in the spectral, spatial, and temporal dimensions-has long presented a major challenge in spectrometer design. With recent developments in sampling theory, this problem has become more manageable through use of undersampling and constrained reconstruction techniques. This article presents an overview of these state-of-the-art multispectral acquisition systems, with a particular focus on snapshot multispectral capture, from a signal processing perspective. We propose that undersampling-based multispectral cameras can be understood and compared by examining the efficiency of their sampling schemes, which we formulate as the spectral sensing coherence information between their sensing matrices and spectrum-specific bases learned from a large-scale multispectral image database. We analyze existing snapshot multispectral cameras in this manner, and additionally discuss their optical performance in terms of light throughput and system complexity.

关键词： Cameras Snapshots

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Label the many with a few: Semi-automatic medical image modality discovery in a large image collection 2

Label the many with a few: Semi-automatic medical image moda...

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ieee symposium on computational intelligence in Healthcare and e-health

作者： Vajda, Szilard You, Daekeun Antani, Sameer K. Thoma, George R. NIH Lister Hill Natl Ctr Biomed Commun Natl Lib Med Bethesda MD 20892 USA Univ Michigan Hlth Syst Ann Arbor MI USA

ISBN: (纸本)9781479953752

In this paper we present a fast and effective method for labeling images in a large image collection. image modality detection has been of research interest for querying multimodal medical documents. To accurately predict the different image modalities using complex visual and textual features, we need advanced classification schemes with supervised learning mechanisms and accurate training labels. Our proposed method, on the other hand, uses a multiview-approach and requires minimal expert knowledge to semi-automatically label the images. The images are first projected in different feature spaces, and are then clustered in an unsupervised manner. Only the cluster representative images are labeled by an expert. Other images from the cluster "inherit" the labels from these cluster representatives. The final label assigned to each image is based on a voting mechanism, where each vote is derived from different feature space clustering. Through experiments we show that using only 0.3% of the labels was sufficient to annotate 300,000 medical images with 49.95% accuracy. Although, automatic labeling is not as precise as manual, it saves approximately 700 hours of manual expert labeling, and may be sufficient for next-stage classifier training. We find that for this collection accuracy improvements are feasible with better disparate feature selection or different filtering mechanisms.

关键词： document image processing feature extraction feature selection image classification image retrieval learning (artificial intelligence) medical image processing pattern clustering accuracy improvement classification schemes cluster representative image labelling complex textual features complex visual features feature space clustering feature spaces filtering mechanisms image clustering image modality detection image projection large-image collection multimodal medical document query multiview-approach next-stage classifier training semiautomatic image labeling semiautomatic medical image modality discovery supervised learning mechanisms training labels unsupervised mechanism voting mechanism Biomedical imaging Computed tomography Feature extraction Labeling Manuals Visualization X-ray imaging Feature extraction Eigenvector document image processing Biomedical imaging image samples Medical image processing images X-ray imaging image classification image retrieval Cluster Analysis Visualization classification scheme X-Ray Computed Tomography

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Multi-Grid Back-Projection Networks

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ieee JOURNAL OF SELECTED TOPICS IN signal processing 2021年第2期15卷 279-294页

作者： Michelini, Pablo Navarrete Chen, Wenbin Liu, Hanwen Zhu, Dan Jiang, Xingqun BOE Technol Grp Co Ltd Dept Artificial Intelligence Beijing Peoples R China

Multi-grid back-projection (MGBP) is a fully-convolutional network architecture that can learn to restore images and videos with upscaling artifacts. Using the same strategy of multi-grid partial differential equation (PDE) solvers this multiscale architecture scales computational complexity efficiently with increasing output resolutions. The basic processing block is inspired in the iterative back-projection (IBP) algorithm and constitutes a type of cross-scale residual block with feedback from low resolution references. The architecture performs in par with state-of-the-arts alternatives for regression targets that aim to recover an exact copy of a high resolution image or video from which only a downscale image is known. A perceptual quality target aims to create more realistic outputs by introducing artificial changes that can be different from a high resolution original content as long as they are consistent with the low resolution input. For this target we propose a strategy using noise inputs in different resolution scales to control the amount of artificial details generated in the output. The noise input controls the amount of innovation that the network uses to create artificial realistic details. The effectiveness of this strategy is shown in benchmarks and it is explained as a particular strategy to traverse the perception-distortion plane.

关键词： image resolution Videos Standards Distortion Training Technological innovation image reconstruction Multigrid iterative backprojection super resolution convolutional networks

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State-space recursive least-squares with adaptive memory 3

State-space recursive least-squares with adaptive memory

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3rd International symposium on image and signal processing and Analysis (ISPA)

作者： Malik, MB Natl Univ Sci & Technol Coll Elect & Mech Engn Lalkurti Pakistan

ISBN: (纸本)953184061X

State-space recursive least-squares (SSRLS) is optimal linear estimator for deterministic signals. The performance of SSRLS however, depends on model uncertainty, time-varying nature of the observed signal or nonstationary behavior of observation noise. We incorporate stochastic gradient tuning of the forgetting factor to develop SSRLS with adaptive memory. This new algorithm addresses the limitations faced by standard SSKLS. An approximation of the actual filter, which alleviates the computational burden, is also derived. An example of tracking a noisy chirp signifies and demonstrates the overall capability and power of the new algorithm. It is expected that this new filter will be able to track and estimate time-varying signals that are difficult to deal with the available tools.

关键词： Chirp Cost function Educational institutions Filters Recursive estimation Riccati equations signal processing signal processing algorithms State estimation Steady-state

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EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces

EEG Subspace Analysis and Classification Using Principal Ang...

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ieee symposium on computational intelligence in Brain Computer Interfaces (CIBCI)

作者： Ashari, Rehab Anderson, Charles Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)9781479945436

Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of voluntary muscle control. Most BCIs are based on the classification of multichannel electroencephalography (EEG) signals recorded from users as they respond to external stimuli or perform various mental activities. The classification process is fraught with difficulties caused by electrical noise, signal artifacts, and nonstationarity. One approach to reducing the effects of similar difficulties in other domains is the use of principal angles between subspaces, which has been applied mostly to video sequences. In this paper, it is shown that principal angles are also a useful approach to the classification of EEG signals that are recorded during a BCI typing application. Single letters are flashed on a computer display every second as the subject counts the number of times the desired letter appears. The appearance of the subject's desired letter is detected by identifying a P300-wave within a one-second window of EEG following the flash of a letter. Classification of pairs of one-second windows of EEG resulted in an average accuracy of detecting the P300 of 88% for a motor-impaired subject recorded in their home and 76% for an unimpaired subject recorded in the lab.

关键词： brain-computer interfaces diseases electroencephalography medical signal processing signal classification BCI typing application EEG signal classification EEG subspace analysis classification process computer display electrical noise external stimuli mental activities multichannel electroencephalography signal classification nonstationarity paralyzed people principal angles signal artifacts voluntary muscle control loss Accuracy Barium Electroencephalography Smoothing methods Testing Training Brain-Computer Interfaces Electroencephalography signal classification Computer displays Electrical noise External stimuli smoothing methods medical signal processing barium Mental activity letter

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Applying brain emotional learning based fuzzy inference system for EEG signal classication between schizophrenics and control participant

Applying brain emotional learning based fuzzy inference syst...

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ieee Conference on computational intelligence in Bioinformatics and computational Biology (CIBCB)

作者： Khasraghi, Bahar Javadi Setayeshi, Saeed Price, Greg Islamic Azad Univ Dept Comp Engn Sci & Res Branch Tehran Iran Amirkabir Univ Dept Energy Engn & Phys Tehran Iran Univ Western Australia Graylands Hosp Perth WA Australia

ISBN: (纸本)9781467389884

This paper concerns the diagnosis of schizophrenia using encephalographic signals and introduces a new framework based on image processing technique. Time-frequency approach or spectrogram image processing technique was used to analyze EEG signals. The spectrogram images were formed from EEG signals, then the Gray Level Co-occurrence Matrix (GLCM) texture feature was extracted from the images. This texture feature produced huge matrix data, thus we used locally linear embedding algorithm (LLA) to reduce the big matrix. In this model, the neuro-based computational model on the limbic system was used to discriminate subjects with schizophrenia patients and control participant that models the emotional process. This architecture is a merging algorithm based on brain emotional learning and fuzzy inference system. The results showed that the proposed model is able to classify the electroencephalographic spectrogram image with 81.5% accuracy.

关键词： Electroencephalography Spectrogram Fuzzy Schizophrenics Amygdala Orbitofrontal Emotional learning

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Sidelobe suppression using the locations of subarrays of the antenna array 3

Sidelobe suppression using the locations of subarrays of the...

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3rd International symposium on image and signal processing and Analysis (ISPA)

作者： Hejres, JA Hejres, JA Univ Bahrain Dept Elect & Elect Engn Isa Town Bahrain

ISBN: (纸本)953184061X

In phased array antennas, sidelobe reduction of the radiation pattern in the direction of the interference signals can be done by controlling either the complex excitations or the spatial phases of the array elements without affecting the main beam. However, the computation times become very large when an antenna with a large number of elements is analyzed. This paper presents a method of sidelobe reduction, which involves perturbing the locations of the subarrays.

关键词： Antenna arrays Antenna radiation patterns Chemical elements computational efficiency Directive antennas Electromagnetic interference Electromagnetic radiative interference Equations Interference suppression Phased arrays

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image Invariant Description based on Local Fourier-Mellin Transform 5

Image Invariant Description based on Local Fourier-Mellin Tr...

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ieee International Conference on signal and image processing Applications (ICSIPA)

作者： Lehiani, Yassine Maidi, Madjid Preda, Marius Ghorbel, Faouzi Ecole Natl Sci Informat ENSI Campus Univ Manouba Manouba 2010 Tunisia ESME Sudria Lab Intelligence Numer & Data 38 Rue Moliere F-94200 Ivry France Telecom SudParis Inst Mines Telecom Dept Artemis 9 Rue Charles Fourier F-91011 Evry France

ISBN: (纸本)9781509055593

In this paper, we present a novel approach for real-time object identification on a mobile platform. First, our system detects keypoints within a scaled pyramid-based FAST detector and then descriptors of the object of interest are computed using an Analytical Fourier-Mellin transform. The Fourier-Mellin is used in similarity studies due to its invariance property and discrimination power. In this approach, we exploited information from the phase of Fourier Transform instead of magnitude applied on patches. The phase carries more information and handle, particularly, rotation and light changes. Finally, experiments are conducted to evaluate the system performances in terms of accuracy, robustness and computational efficiency as well.

关键词： Detectors Robustness Feature extraction Training Fourier transforms image recognition

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A computational digital-pixel-sensor VLSI featuring block-readout architecture for pixel-parallel rank-order filtering

A computational digital-pixel-sensor VLSI featuring block-re...

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ieee International symposium on Circuits and Systems (ISCAS)

作者： Tongprasit, B Ito, K Shibata, T Univ Tokyo Dept Frontier Informat Tokyo Japan

ISBN: (纸本)0780388348

A computational digital-pixel-sensor (DPS) VLSI with on-chip image processing circuits has been developed. A 6402 DPS array and the versatile rank-order filtering circuits are implemented. Newly proposed block-readout architecture is employed in DPS memory in order to resolve the interconnection bottleneck between sensors and processing units. The data from sensor array are read out in block and processed on the chip. As a result, this architecture enhances the performance of bit-serial digital signal processing. This paper also presents a versatile rank-order filtering circuit. The rank-order filtering algorithm and the reversed rank-order filtering algorithm proposed in this work are merged and implemented in a simplified circuit. The pixel-parallel seamless scan of filtering operations has been successfully realized.

关键词： Digital signal processing

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