Dauphin is a new statistical signal processing language designed for easier formulation of detection, classification and estimation algorithms. This paper demonstrates the ease of developing signal processing algorith...
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ISBN:
(纸本)9781467367950
Dauphin is a new statistical signal processing language designed for easier formulation of detection, classification and estimation algorithms. This paper demonstrates the ease of developing signal processingalgorithms in Dauphin. We illustrate this by providing exemplar code for two classifiers: Bayesian and K-means, and for an estimator: the Kalman filter. In all cases, and especially the last named, the code provides a more conceptually defined approach to these problems than other languages such as Matlab. Some Dauphin features under development are also highlighted, for instance a infinite list construct called streams, which is designed to be used as a natural representation of random processes.
The quick atmospheric correction (QUAC) algorithm is a relatively fast and robust atmospheric compensation algorithm for hyperspectral imageprocessing utilizing in scene information. An adjustment of some key paramet...
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ISBN:
(纸本)9781467367950
The quick atmospheric correction (QUAC) algorithm is a relatively fast and robust atmospheric compensation algorithm for hyperspectral imageprocessing utilizing in scene information. An adjustment of some key parameters in QUAC is made leading to improved results for coastal scenes. In general the QUAC results compare well with two first principles radiative transfer (RT) model based algorithms. Some suggestions for future work are made including automating the setting of key QUAC parameters and accounting for the coastal zone aerosols more accurately in the RT algorithms.
Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between...
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ISBN:
(纸本)9781628414899
Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the l(1) norm. The l(1) enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than the classical approach. Next, the proposed approach is applied to two image data sets and achieved improved performances over standard Isomap.
In this paper, we describe how to establish an embedded framework for real-time top-view people counting. The development of our system consists of two parts, i.e. establishing an embedded signal processing platform a...
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ISBN:
(纸本)9781509059119
In this paper, we describe how to establish an embedded framework for real-time top-view people counting. The development of our system consists of two parts, i.e. establishing an embedded signal processing platform and designing a people counting algorithm for the embedded system. For the hardware platform construction, we use Kinect as the camera and exploit NVIDIA Jetson TK1 board as the embedded processing platform. We describe how to build a channel to make Kinect for windows version 2.0 communicate with Jetson TK1. Based on the embedded system, we adapt a water filling based scheme for top-view people counting, which integrates head detection based on water drop, people tracking and counting. Gaussian Mixture Model is used to construct and update the background model. The moving people in each video frame are extracted using background subtraction method. Additionally, the water filling algorithm is used to segment head area as Region Of Interest(ROI). Tracking and counting people are performed by calculating the distance of ROI center point before and after the frame. The whole framework is flexible and practical for real-time application.
This paper introduces a video processing method designed specifically to give researchers access to players' behaviors within any commercially available off-the-shelf PC game. Insights into players' experience...
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This paper introduces a video processing method designed specifically to give researchers access to players' behaviors within any commercially available off-the-shelf PC game. Insights into players' experiences with videogame violence are achieved from automatically processing significant elements of the audio-visual communication/feedback (i.e. moving image and sound) over long periods of uninhibited game play. The method exploits a wealth of significant and (behaviorally) influential information that is conveyed to the player as they progress through a game. Such information can relate to virtual progress (e.g. maps, mission logs), player reserves (e.g. acquisitions) or vitality (e.g. health or stamina levels), to name but a few. By analyzing what is transmitted to the player during play, feedback-based game metrics are produced that utilize the same content that the player perceives and processes during their gameplay, thus, tying the method directly to individual `player experiences.' This method was developed for a project that addressed the persistent concerns over the impact of game violence and its translation into societal violence. The method provided the project with an alternative approach to understanding the use and function of violence within game systems, taking research in a new direction from the approach and research-designs employed by experimental psychological over the last few decades.
In this paper, the concept of the two-dimensional discrete Fourier transformation (2-D DFT) is defined in the general case, when the form of relation between the spatial-points (x, y) and frequency-points (omega(1), o...
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ISBN:
(纸本)9781628414899
In this paper, the concept of the two-dimensional discrete Fourier transformation (2-D DFT) is defined in the general case, when the form of relation between the spatial-points (x, y) and frequency-points (omega(1), omega(2)) is defined in the exponential kernel of the transformation by a nonlinear form L(x, y;omega(1), omega(2)). The traditional concept of the 2-D DFT uses the Diaphanous form x omega(1) + y omega(2) and this 2-D DFT is the particular case of the Fourier transform described by the form L(x, y;omega(1), omega(2)). Properties of the general 2-D discrete Fourier transform are described and examples are given. The special case of the N x N-point 2-D Fourier transforms, when N = 2(r), r > 1, is analyzed and effective representation of these transforms is proposed. The proposed concept of nonlinear forms can be also applied for other transformations such as Hartley, Hadamard, and cosine transformations.
Compressive sensing (CS) theory states that a signal which can be sparsely represented in a known basis may be reconstructed from its samples which have been obtained below the Nyquist rate. image reconstruction with ...
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ISBN:
(纸本)9781628418583
Compressive sensing (CS) theory states that a signal which can be sparsely represented in a known basis may be reconstructed from its samples which have been obtained below the Nyquist rate. image reconstruction with a single detector using CS theory has been shown to give promising results. In this work, we investigate the application of CS theory to single detector infrared (IR) rosette scanning systems. The single detector pseudo-imaging rosette scanning system scans the scene with a specific pattern and performs processing to estimate the target location without forming an image. These systems suffer from low performance compared to costly focal plane array (FPA) detectors. Using the CS framework, these scanning systems may be improved by reconstructing the samples obtained by the rosette scanning pattern. For this purpose, we consider surface to air engagement scenarios where the IR images contain aerial targets and flares. The IR images have been reconstructed from samples obtained with the rosette scanning pattern and other baseline sampling strategies. It has been shown that the proposed scheme exhibits good reconstruction performance and large size FPA imaging performance can be achieved using a single IR detector with a rosette scanning pattern.
Synthetic Aperture Radars (SAR) provide high resolution ground images by utilizing the aircraft motion to synthesize a large aperture. The presence of residual phase error in the SAR images causes defocusing in the im...
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ISBN:
(纸本)9781509007752
Synthetic Aperture Radars (SAR) provide high resolution ground images by utilizing the aircraft motion to synthesize a large aperture. The presence of residual phase error in the SAR images causes defocusing in the images. Autofocus algorithm compensates these phase errors to obtain a focused image. In most scenarios a priori information about the type of phase error is known which can be effectively utilized in autofocus techniques. The paper proposes a new autofocus algorithm which is based on Wiener filter theory and implements a multistage Wiener filter to compensate the phase error in SAR images.
In this paper, a general, efficient, split algorithm to compute the two-dimensional quaternion discrete Fourier transform (2-D QDFT), by using the special partitioning in the frequency domain, is introduced. The parti...
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ISBN:
(纸本)9781628414899
In this paper, a general, efficient, split algorithm to compute the two-dimensional quaternion discrete Fourier transform (2-D QDFT), by using the special partitioning in the frequency domain, is introduced. The partition determines an effective transformation, or color image representation in the form of 1-D quaternion signals which allow for splitting the N x M-point 2-D QDFT into a set of 1-D QDFTs. Comparative estimates revealing the efficiency of the proposed algorithms with respect to the known ones are given. In particular, a proposed method of calculating the 2(r) x 2(r)-point 2-D QDFT uses 18N(2) less multiplications than the well-known column-row method and method of calculation based on the symplectic decomposition. The proposed algorithm is simple to apply and design, which makes it very practical in color imageprocessing in the frequency domain.
Electro-Optical (EO) surveillance systems are capable of performing autonomous search, detection, tracking and designation of potential targets. The detection and tracking of target at long range is a challenge due to...
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ISBN:
(纸本)9781479979615
Electro-Optical (EO) surveillance systems are capable of performing autonomous search, detection, tracking and designation of potential targets. The detection and tracking of target at long range is a challenge due to atmospheric degradation and background clutter. The detection process heavily depends on its image quality. Various types of image enhancement techniques are being exploited to improve the detection capability. The performance of these techniques varies with operational scenario as the surveillance is a very subjective process by nature. Reconfigurable architecture based upon FPGA has been chosen to implement real-time image enhancement, for improved range performance (detection/recognition/identification) of EO systems considering the scenarios such as naval and land platforms. The architectural design based on FPGA and real time implementation results for these imageprocessingalgorithms along with improvement in the quality of image has been presented.
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