• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.12-20
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• 2018

Efforts have been made to reconstruct low-resolution underwater images to high-resolution ones by using the image SR (Super-Resolution) method, all to improve efficiency when acquiring side-scan sonar images. As side-scan sonar images are similar with the optical images with respect to exploiting 2-dimensional signals, conventional image restoration methods for optical images can be considered as a solution. One of the most typical super-resolution methods for optical image is a sparse coding and there are studies for verifying applicability of sparse coding method for underwater images by analyzing sparsity of underwater images. Sparse coding is a method that obtains recovered signal from input signal by linear combination of dictionary and sparse coefficients. However, it requires huge computational load to accurately estimate sparse coefficients. In this study, a sparse coding based underwater image super-resolution method is applied while a selective reconstruction method for object region is suggested to reduce the processing time. For this method, this paper proposes an edge detection and object and non object region classification method for underwater images and combine it with sparse coding based image super-resolution method. Effectiveness of the proposed method is verified by reducing the processing time for image reconstruction over 32 % while preserving same level of PSNR (Peak Signal-to-Noise Ratio) compared with conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.140-148
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• 2004

Natural images can be classified into edge or flat region. Edges have also various shapes such as long edge, texture and so on. Because the conventional deinterlacing methods commonly use one specific algorithm, they are faced with the difficulty that does not adapt various shapes of images. In this paper, a selective deinterlacing method based on the characteristics of local region of image is proposed. An input image is classified into three regions; flat region, complex edge, long edge. And then for each region, the proper method is assigned according to the characteristic of the local feature. For long edge region, the modified $NEDI(New Edge Directed Interpolation)^{[1]}$ method that interpolates long edge very well is used. The linear $filter^{[2]}$ that enhances high frequency components is used for complex edge, and the bilinear interpolation method is applied to flat region. The proposed method shows improved performance in PSNR and subjective evaluation compared with previous algorithms.

• Macromolecular Research
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• v.12 no.5
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• pp.493-500
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• 2004

We have developed a novel method for patterning functional images in thin polymer films. The key materials we utilized for the imaging were dihydroxyanthraquinones protected with acid-labile tert-butoxycarbonyl (t-Boc) blocking groups. Among the tested compounds, 1,4-dihydroxyanthraquinone (quinizarin; 1) underwent the most drastic change in terms of its color and fluorescence upon protection. We prepared the t-Boc-protected quinizarin and polymers bearing the protected quinizarins as pendent groups. To investigate the possibility of a single-component imaging system, we synthesized a styrenic monomer 14 incorporating protected quinizarin and a maleimide derivative 15 bearing a photoacid generating group and subjected them to polymerization. Selective removal of the protecting groups of the quinizarin moieties in the exposed area using photolithographic techniques allowed regeneration of quinizarin and patterned fluorescence images in the polymer films.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.1
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• pp.39-45
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• 2018

Ammonia Adsorbed Fly Ash (AAFA) samples produced from coal fired plants equipped with SNCR (Selective Non-Catalytic Reduction) of nitrogen oxides with urea have been chemically analyzed, and their physical and dissolution properties have been investigated. XRD results for the ammonia component in AAFA ascertained that ABS (ammonium bisulfate) and AS (ammonium sulfate) were deposited on fly ash as $SO_3$ reacted with unreacted ammonia at SNCR. SEM and EDS images showed that fine ashes on large fly ash surface of sphere type were agglomerated, due to adhesive role of ammonium salts attached fly ashes. Dissolution test results of ammonium salts absorbed on AAFA in distilled water or sea water showed that the proportion of un-ionized $NH_3$ to $NH_4{^+}$ were primarily a function of pH and temperature. Increasing pH and temperature causes an increase in the fraction of un-ionized $NH_3$. At pHs of 9.6 and 10.7, un-ionized $NH_3$ and $NH_4{^+}$ ions are present in equal amounts at distilled water and sea water, respectively.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.273-275
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• 2005

Active thermography is being used since several years for remote non-destructive testing. It provides thermal images for remote detection and imaging of damages. Also, it is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. For energy deposition, it use external heat sources (e.g., halogen lamp or convective heating) or internal heat generation (e.g., microwaves, eddy current, or elastic wave). Among the external heat sources, the ultrasound is generally used for energy deposition because of defect selective heating up. The heat source generating a thermal wave is provided by the defect itself due to the attenuation of amplitude modulated ultrasound. A defect causes locally enhanced losses and consequently selective heating up. Therefore amplitude modulation of the injected ultrasonic wave turns a defect into a thermal wave transmitter whose signal is detected at the surface by thermal infrared camera. This way ultrasound thermography(UT) allows for selective defect detection which enhances the probability of defect detection in the presence of complicated intact structures. In this paper the applicability of UT for fast defect detection is described. Examples are presented showing the detection of defects in PCB material. Measurements were performed on various kinds of typical defects in PCB materials (both Cu metal and non-metal epoxy). The obtained thermal image reveals area of defect in row of thick epoxy material and PCB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.172-180
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• 2003

This paper propose a new change detection algorithm based on macro block unit for selective video coding scheme. The conventional method badly decides a macro block of unchanged region into a changed macro block due to a noise of the difference images. To solve the problem of the conventional method, we propose a new test statistic which is robust to the noise of the difference image. As shown in experimental results(Fig. 1∼3), the proposed algorithm shows more accurate segmentation results than the conventional method. Also, because the proposed detection method reduces the average numbers of changed macro block per frame to 55∼60% than the conventional method, it can improve the performance of the selective video coding at lower bit rates.

• Journal of radiological science and technology
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• v.42 no.1
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• pp.9-17
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• 2019

Although digital mammography is a representative method for breast cancer detection. It has a limitation in detecting and classifying breast tumor due to superimposed structures. Machine learning, which is a part of artificial intelligence fields, is a method for analysing a large amount of data using complex algorithms, recognizing patterns and making prediction. In this study, we proposed a technique to improve the diagnostic accuracy of energy-selective mammography by training data using the machine learning algorithm and using dual-energy measurements. A dual-energy images obtained from a photon-counting detector were used for the input data of machine learning algorithms, and we analyzed the accuracy of predicted tumor thickness for verifying the machine learning algorithms. The results showed that the classification accuracy of tumor thickness was above 95% and was improved with an increase of imput data. Therefore, we expect that the diagnostic accuracy of energy-selective mammography can be improved by using machine learning.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.83-89
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• 2015

Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.2
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• pp.94-103
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• 1997

The WCHF-FSJTC (wavelet circular harmonic function frequency selective joint transform correlator) using th wavelet transformed CHF as the reference image in FSJTC is proposed for rotation invariant pattern recognition. Since the wavelet transform has the property of feature extraction, the proposed system can have the better DC (discrimination cpability) and the higher SNR(signal to noise ratio) compared with the conventional CHF-CJTC(circular harmonic function conventional joint transform correlator). And since the structure of the proposed system is FSJTC which can eliminate auto-correlation and cross-correlation between input images, it can eliminate false alarm caused by the overlapping among correlation peaks. The used wavelet functio is the morlet function, which is proper for the reference image used in this paper. the optimal dialation parameter and oscillation frequency of the wavelet function are also achieved with varying the parameters of the wavelet function. The computer simulation shows that the proposed system has the best performance when the dilation parameter is 0.8 and the oscillation frequency is 0.48.

• Journal of Ceramic Processing Research
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• v.13 no.spc1
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• pp.93-95
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• 2012

We report on the growth and characterization of the nano- and micro scale GaN structures selectively grown on the vertex of GaN stripes using the metal organic vapor phase epitaxy method and conventional photolithography technique. The triangular shaped nano- and micro GaN structures which have semi-polar {11-22} facets were formed only on the vertex of the lower GaN stripes. Crystalline defects reduction was observed by transmission electron microscopy for upper GaN stripes. We also have grown the InGaN/GaN multi-quantum well structures on the semi-polar facets of the upper GaN stripes. Cathodoluminescence images were taken at 366, 412 and 555 nm related to GaN band edge, InGaN/GaN layer and defects, respectively.