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Hidden Markov model approaches to hyperspectral image classification

Hidden Markov model approaches to hyperspectral image classi...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Qian Du Chein-I Chang Department of Electrical Engineering and Computer Science Texas A and M University Kingsville TX USA Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

In this paper, we present a hidden Markov model (HMM) approach to hyperspectral image classification. HMMs have been widely used in speech recognition to model a doubly stochastic process with a hidden state process that can be only observed through a sequence of observations. Since the temporal variability of a speech signal is similar to the spectral variability of a remotely sensed image pixel vector, the same idea can be applied to hyperspectral image classification. It makes use of a hidden Markov process to characterize the spectral correlation and band-to-band variability where the model parameters are determined by the spectra of the pixel vectors that form the observation sequences. Experiments demonstrate that the HMM can better describe the unobserved spectral properties so as to improve classification performance.

关键词： Hidden Markov models Image classification

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Real-time processing of an unsupervised constrained linear spectral unmixing algorithm

Real-time processing of an unsupervised constrained linear s...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： D.C. Heinz Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Most spectral unmixing techniques require complete a priori knowledge of spectral endmembers in an image scene to be implemented. This knowledge is usually obtained from a complete hyperspectral image scene in either a supervised or unsupervised fashion, which prohibits real-time implementation. In this paper, we present a unique constrained spectral unmixing technique, which develops this knowledge in real-time on a pixel-by-pixel basis. Experiments using HYDICE data were conducted to demonstrate this proposed real-time approach for target detection and classification in hyperspectral imagery. Small modifications to the real-time algorithm were made in the experimental section to alleviate practical problems associated with a true pixel-by-pixel implementation.

关键词： Hyperspectral sensors Layout Hyperspectral imaging Object detection computer displays Remote monitoring Image sensors Remote sensing signal processing Image processing

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Discrimination measures for target classification

Discrimination measures for target classification

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Shao-Shan Chiang Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Target detection does not necessarily yield target classification since the detected targets may belong to different classes and cannot be differentiated one from another by target detection. This often occurs when no prior target knowledge is available. In order to resolve this dilemma, four measures are proposed for target discrimination in this paper, two of which are designed based on the Bhattacharyya distance and the other two are derived from the concept of the matched filter. They will be used to cluster the detected anomalies into different types of targets in an unsupervised manner. These four target discrimination measures take advantage of the second-order statistics of the image data to account for sample spectral correlation. Consequently, they all outperform the commonly used single-pixel based similarity measures, such as spectral angle mapper (SAM), Euclidean distance. An experiment-based quantitative study is conducted for their performance evaluation. Interestingly, all these four measures perform very similarly.

关键词： Covariance matrix Matched filters signal processing Object detection Remote sensing Image processing Laboratories computer science Statistics Euclidean distance

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Blind separation of second-order nonstationary and temporally colored sources

Blind separation of second-order nonstationary and temporall...

引用

IEEE/SP Workshop on Statistical signal Processing (SSP)

作者： Seungjin Choi A. Cichocki A. Belouchrani Department of Computer Science & Engineering POSTECH South Korea Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN Japan Department of Electrical Engineering Ecole Nationale Polytechnique (ENP) Algeria

This paper presents a method of blind source separation that jointly exploits the nonstationarity and temporal structure of sources. The method needs only multiple time-delayed correlation matrices of the observation data, each of which is evaluated at a different time-windowed data frame, to estimate the demixing matrix. We show that the method is quite robust with respect to the spatially correlated but temporally white noise. We also discuss the extension of some existing second-order blind source separation methods. Extensive numerical experiments confirm the validity of the proposed method.

关键词： Source separation Noise robustness Blind source separation Additive noise White noise computer science Biomedical signal processing Telecommunications Speech processing signal analysis

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An ROC analysis for subpixel detection

An ROC analysis for subpixel detection

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chein-I Chang Shao-Shan Chiang Qian Du Hsuan Ren A. Ifarragaerri Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA Department of Computer Science and Electrical Engineering Texas A and M University Kingsville TX USA Biological and Chemical Command US Army MD USA

ROC (Receiver Operating Characteristic) analysis has been widely used to evaluate detection performance. It is based on the Neyman-Pearson detection theory, which solves binary hypothesis testing problems. In mixed pixel classification many algorithms that are developed to estimate abundance fractions (of image endmembers) generally produce gray scale images. As a result, they are not directly applied to hypothesis testing problems. Instead of using the standard ROC curve generated by the detection power versus the false alarm probability, a 3-dimensional (3D) ROC curve is developed in this paper for subpixel detection. It is a 3D plot derived from the mean-detection probability versus the mean-false alarm rate with the third dimension specified by abundance fractions produced by subpixel detection algorithms. In order to illustrate the utility of the proposed 3D ROC analysis in subpixel detection, several linear unmixing-based algorithms are used for performance evaluation.

关键词： Testing Pixel Performance analysis computer science Chemical analysis Image segmentation signal processing Image processing Laboratories Chemical processes

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A digital envelope detection filter for blood pressure measurement

A digital envelope detection filter for blood pressure measu...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： J.Y. Lee J.K. Kim G. Yoon Medical Application Team Samsung Advanced Institute of Technology Yongin si South Korea Digital Signal Processing Laboratory Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea

We developed a finger type blood pressure measurement system using a volume oscillometric algorithm. The digital envelope detection filter (EDF) method was applied to volume oscillometric signals which were acquired from an air-filled occlusive finger cuff. In the case of using the EDF, we could reduce the difference error and standard deviation by 30-40%.

关键词： Envelope detectors Digital filters Blood pressure Pressure measurement Fingers Arteries Finite impulse response filter Frequency Biomedical monitoring Volume measurement

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Color error diffusion with generalized optimum noise shaping

Color error diffusion with generalized optimum noise shaping

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IEEE International Conference on Image Processing

作者： N. Damera-Venkata B.L. Evans Halftoning and Image Processing Group Hewlett Packard Laboratories Palo Alto CA USA Embedded Signal Processing Laboratory Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

We optimize the noise shaping behavior of color error diffusion by designing an optimized error filter based on a proposed noise shaping model for color error diffusion and a generalized linear spatially-invariant model of the human visual system. Our approach allows the error filter to have matrix-valued coefficients and diffuse quantization error across channels in an opponent color representation. Thus, the noise is shaped into frequency regions of reduced human color sensitivity. To obtain the optimal filter, we derive a matrix version of the Yule-Walker equations which we solve by using a gradient descent algorithm.

关键词： Colored noise Noise shaping Design optimization Humans Nonlinear filters Visual system Quantization Noise reduction Frequency Equations

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FM halftoning via block error diffusion

FM halftoning via block error diffusion

引用

IEEE International Conference on Image Processing

Error diffusion halftoning is a popular method of producing frequency modulated (FM) halftones. In FM halftoning the dot size and shape is fixed (equal to one pixel) and the dot frequency is varied in accordance to the graylevel values of the underlying grayscale image. We generalize error diffusion to produce FM halftones with user controlled dot size and shape using block quantization and a block filter in the feedback loop. We call this modified quantization and feedback process block error diffusion. The block filters are designed from well known scalar error filter prototypes and retain their properties. Further, we show that choosing a structured block filter results in an efficient parallel implementation of block error diffusion.

关键词： Frequency modulation Filters Shape control Quantization Pixel Gray-scale Error correction Size control Feedback loop Prototypes

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Asymptotic closed-loop design of predictive multi-stage vector quantizers

Asymptotic closed-loop design of predictive multi-stage vect...

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IEEE International Conference on Image Processing

作者： H. Khalil K. Rose Signal Compression Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

This work considers the design of a multi-stage vector quantizer (MSVQ) for application to the motion compensated prediction error of video signals. It is well known that the design of predictive vector quantizers suffers from fundamental difficulties due to the prediction loop, which have an impact on the convergence and the stability of the design procedure. We propose an approach to predictive MSVQ design that enjoys the stability of open-loop design while ensuring ultimate optimization of the closed-loop system. The proposed design method is tested on video compression at low bit rates, where it significantly outperforms widely-used closed-loop design techniques, and achieves improvement over the H.263 standard.

关键词： Video compression Discrete cosine transforms Bit rate Image coding Laboratories Stability Mobile communication Statistics Video coding signal design

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A 16-kbit/s bandwidth scalable audio coder based on the G.729 standard

A 16-kbit/s bandwidth scalable audio coder based on the G.72...

引用

International Conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： K. Koishida V. Cuperman A. Gersho Signal Compression Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

This paper proposes a bandwidth-scalable coding scheme based on the G.729 standard as a base layer coder. In the scheme, according to the channel conditions, the output speech of the decoder can be selected to be narrowband (4-kHz bandwidth) or wideband (8-kHz bandwidth). The proposed scheme consists of two layers: base and enhancement. The base coder uses the G.729 algorithm to encode narrowband speech. The enhancement coder is based on a full-band CELP model and it encodes wideband speech while making use of the available base layer information. Two bandwidth-scalable coders are designed: one is scalable with the 8 kbit/s G.729 base coder and another with the 6.4 kbit/s G.729 (Annex D) base coder. Subjective tests show that, for wideband speech, the proposed coders at 16 kbit/s achieve better performance than the 16 kbit/s MPEG-4 CELP with bandwidth scalability.

关键词： Bandwidth Code standards Narrowband Wideband Scalability Decoding Speech enhancement Laboratories MPEG 4 Standard Speech analysis

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