Won-Chul Choi

Evaluation of Seebeck coefficients in n- and p-type silicon nanowires fabricated by complementary metal?oxide?semiconductor technology

Silicon-based thermoelectric nanowires were fabricated by using complementary metal-oxide-semiconductor (CMOS) technology. 50 nm width n- and p-type silicon nanowires (SiNWs) were manufactured using a conventional photolithography method on 8 inch silicon wafer. For the evaluation of the Seebeck coefficients of the silicon nanowires, heater and temperature sensor embedded test patterns were fabricated. Moreover, for the elimination of electrical and thermal contact resistance issues, the SiNWs, heater and temperature sensors were fabricated monolithically using a CMOS process. For validation of the temperature measurement by an electrical method, scanning thermal microscopy analysis was carried out. The highest Seebeck coefficients were - 169.97 μV K(-1) and 152.82 μV K(-1) and the highest power factors were 2.77 mW m(-1) K(-2) and 0.65 mW m(-1) K(-2) for n- and p-type SiNWs, respectively, in the temperature range from 200 to 300 K. The larger power factor value for n-type SiNW was due to the higher electrical conductivity. The total Seebeck coefficient and total power factor for the n- and p-leg unit device were 157.66 μV K(-1) and 9.30 mW m(-1) K(-2) at 300 K, respectively.

Noise reduction of hyperspectral images using a joint bilateral filter with fused images

In this paper, we propose a denoising method for hyperspectral images using a joint bilateral filter. The joint bilateral filter with the fused image of hyperspectral image bands is applied on the noisy image bands. This fused image is a single grayscale image that is obtained by the weighted summation of hyperspectral image bands. It retains the features and details of each hyperspectral image band. Therefore the joint bilateral filter with the fused image is powerful in reducing noise while preserving the characteristics of the individual spectral bands. We evaluated the performance of the proposed noise reduction method on hyperspectral imaging systems, which we developed for visible and near-infrared spectral regions. Experimental results show that the proposed method outperforms the conventional approaches, such as the basic bilateral filter.

Automatic Extraction of Corresponding-Points for Image Registration

Recently, multi-sensor image fusion systems and related applications have been widely investigated. In an image fusion system, robust and accurate multi-modal image registration is essential. In the conventional method, the image registration process starts with manually-pointed corresponding pairs in both sensored images. Using these corresponding pairs, a transform matrix is initialized and refined through an optimization process. In this paper, we propose a new automatic extraction method for such corresponding pairs. The Harris corner detector is employed to extract feature points in both EO/IR images individually. Patches around the detected feature points are matched with a probabilistic criterion, mutual information (MI), which is a preferred measure for image registration due to its robust and accurate performance. Simulation results show that the proposed scheme has a low time complexity and extracts corresponding pairs well.

Average approach to amplify-and-forward relay networks

In this paper, the analysis of an average received signal-to-noise ratio (SNR) for a cooperative communication network with amplify-and-forward (AF) relays is presented. In AF systems, the overall instantaneous SNR at the receiving end can be expressed as the form of a harmonic mean of perhop SNRs. This means that the received SNR can be analyzed by applying the statistical expectation of the harmonic mean of two exponential random variables, which was derived in a closed-form expression. The proposed result can help examining the performance of AF relay systems by using the average sense approach. The simulation results demonstrate the exact derivation of the expectation of harmonic means. The result also shows that the destination node can obtain larger average received SNR as the number of relay nodes is increased.

Development of a demeaning filter for small object detection in infrared images

The demeaning filter detects a small object by removing a background with a mean filter as well as the covariance of an object and backgrounds. The factors considered in the design of the demeaning filter are the method of demeaning, which involves subtracting the local mean value from all pixel values, and the acquisition of templates for both the object and the background. This study compares the sliding window method and the grid method as a demeaning method, and studies the method of acquisition of an object template. Moreover, a method involving the use of previous frames, a mean filter, and an opening operation are studied in an effort to acquire a background template. Based on the results of this study, a practical design of a demeaning filter that is able to detect a small object in an IR image in real time is proposed. Experiment results demonstrate the superiority of the proposed design in detecting a small object following a 2-D Gaussian distribution even under severe zero-mean Gaussian noise.

Visualization of Hyperspectral Images Using Bilateral Filtering with Spectral Angles

This paper presents an extended bilateral filter with spectral angles and a visualization scheme for hyperspectral image data. The conventional bilateral filter used to be implemented using a position vector and a luminance value at each pixel in the scene. Since hyperspectral image data can provide a spectrum vector that has hundreds of bands at each pixel, we propose an extended bilateral filter using spectral angles. The proposed bilateral filter can be used for extracting and preserving the spectrum edges of the hyperspectral image. A visualization scheme for hyperspectral images exploiting the proposed bilateral filter has been also proposed. When objects that have the similar tristimulus intensity but different spectrums are mixed, they can be separated through the proposed visualization scheme. The resulting images show that the proposed scheme facilitates anomaly detection in the hyperspectral scenes.

Design of multiple demeaning filters for small target detection in infrared imageries

In this paper, we propose multiple demeaning filters for small target detection in infrared (IR) images. The use of a demeaning filter is a promising method which detects a small object by removing the background components with a mean filter. The main factors in the design of a demeaning filter are two types of demeaning methods and the size of its window. We compare two demeaning methods, the sliding window method and the grid method, and we analyze the trade-off between the window size and the performance of the demeaning filters and present limitations related to their use. To overcome the drawbacks of a conventional demeaning filter, the use of multiple demeaning filters with filters of various sizes is considered. The proposed method not only has the advantage of being able to detect a small object in a densely cluttered environment, but it also can be used with low complexity with an integral image. Experimental results demonstrate the robustness and stability of the proposed multiple demeaning filters with low computational complexity compared with conventional methods.

Derivations of decoder and beamforming vector for amplify—and—forward relays based on the Cauchy-Schwartz inequality

For multiple amplify—and—forward (AF) relays, optimal decoder and beamforming vector have been presented [3], [4]. The derivations of these optimal ones have been based on the generalized eigenvalue problem. In this work, we show the derivations using the Cauchy-Schwartz inequality. Moreover, the intimate relation between decoder and beamforming vector is analyzed.

An adaptive space-time coding based relay allocation scheme in AF cooperative systems

An adaptive relay allocation scheme for multi-user cooperative communication systems with amplify-and-forward (AF) relays is investigated. We consider maximizing system capacity while guaranteeing the QoS (Quality of Service) of each user. Proposed relay allocation scheme uses space-time coding technique. It performs well in allocating relay nodes to multiple source-destination pairs. The proposed algorithm enhances system performance without loss of diversity.

Automatic tracking system with target classification

In this paper, we propose an overall target tracking scheme performing image stabilization, detection, tracking, and classification in the IR sensored image. Firstly, in the image stabilization stage, a captured image is stabilized from visible frame-to-frame jitters caused by camera shaking. After that, the background of the image is modeled as Gaussian. Based on the results of the background modeling, the difference image between a Gaussian background model and a current image is obtained, and regions with large differences are considered as targets. The block matching method is adopted as a tracker, which uses the image captured from the detected region as a template. During the tracking process, positions of the target are compensated by the Kalman filter. If the block matching tracker fails to track targets as they hide themselves behind obstacles, a coast tracking method is employed as a replacement. In the classification stage, key points are detected from the tracked image by using the scale-invariant feature transform (SIFT) and key descriptors are matched to those of pre-registered template images.