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Hyperspectral remote-sensing image has high data dimensionality and a small amount of labeled pixels, which causes the curse of dimensionality phenomenon. Therefore, feature extraction is needed ahead of recognition for reducing dimensionality and improving classification accuracy. A novel multiclass feature extraction method, i.e., M-ary discriminant analysis (M-ary DA), is presented for solving...
In this paper we show that a minimal state space realisation in Jordan canonical form for linear continuous-time systems described by rational transfer function could be obtained in a natural and basic way by using the concept of Nerode equivalence. whilst the state space realisation is known, the contribution of this note is that the proposed realisation procedure is directly introduced and not like...
Conventional iris recognition requires controlled conditions (e.g., close acquisition distance and stop-and-stare scheme) and high user cooperation for image acquisition. Non-cooperative acquisition environments introduce many adverse factors such as blur, off-axis, occlusions and specular reflections, which challenge existing iris segmentation approaches. In this paper, we present two iris segmentation...
Telemetry data, containing the data of multiple subsystems such as power system, implies the on-orbit operation status information of the satellite. We can obtain performance characteristics and fault symptom of the satellite subsystems through analyzing these data. Using classification algorithm we can provide normal data for anomaly detection and find the data from various subsystems which have...
The bag of visual words (BoW) model is one of the most successful model in image classification task. However, the major problem of the BoW model lies in the determination of visual words, which consists of codebook training and feature encoding phases. The traditional K-means and hard-assignment method completely ignore the structure of the local feature space, leading to high loss of information...
Parametric linear autoregressive (AR) model has been widely used in image processing but is known to induce unstable results. The recently emerged nonparametric kernel regression is an effective structural method for forestalling outliers but often brings over-smoothed output. This paper introduces a hybrid algorithm for image interpolation through combining the strength of parametric and nonparametric...
Millions of video surveillance cameras distribute around the world, and capture tremendous number of video data endlessly. Video browsing by frame is time consuming and inefficient, since needless information is abundant in the raw videos. Video synopsis is an effective way to solve this problem by producing a short video abstraction, while keeping the essential activities of the original video. However,...
Deep reactive ion etching (DRIE) technique is a new and powerful tool in Micro-Electro-Mechanical Systems (MEMS) fabrication. A 3D DRIE simulation can help researcher understand the time-evolution of Bosch process used in DRIE. Due to the high complexity of the algorithm used in the simulation, it is necessary to develop an algorithm that can accelerate the simulation. This paper presents a parallel...
A novel layered object tracking algorithm for FLIR imagery is proposed based on mean shift algorithm and feature matching. First, infrared object is modeled by kernel histogram. Bhattacharyya coefficient is used to measure the similarity between object model and candidate model. The object is then localized by mean shift algorithm rapidly and efficiently. Because of the low contrast between infrared...
An object-oriented storage system NLOV (network logical object volume) based on BerkeleyDB is implemented. It provides a block level object-oriented storage interface. It uses NBD and AOE as transport protocols and supports interoperation between the two protocols. Compared with other object-oriented storage system, such as Lustre and Ceph, NLOV has good simplicity, better flexibility and applicability...
Bi-cubic interpolation algorithm is commonly used in image scaling, but traditional cubic interpolation has its own shortcomings such as complicated computation, long computational time and so on. For these problems, the paper studies traditional cubic kernel function and proposes an optimized algorithm with adjustable coefficients. This algorithm utilizes an modifying coefficient lambda to amend...
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