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Supplemental Material for Enhancing the optical performance of organic light-emitting diodes using nanoscale random rubbed structure by Cheol Shin, Seungwon Lee, Kwang Wook Choi, Young Hyun Hwang, Young Wook Park and Byeong-Kwon Ju in Nanomaterials and Nanotechnology

The science inquiry-experiment is new subject developed for high school students according to the 2015 revised science national curriculum. The subject was focused on improving scientific inquiry ability of high school students on the basis of the inquiry and experiment. We examined characteristics of inquiry activities presented in science inquiry-experiment textbooks. In order to do this, types of inquiry activities presented in science inquiry-experiment textbooks were comparatively analyzed according to units and publishers. Types of inquiry activities were categorized into experiment & observation, data interpretation, investigation-discourse & presentation, discussion, expression, science writing, and simulation. Experiment and observation, data interpretation, investigation-discourse & presentation, and expression were more among them, the other hand, discussion, science writing and simulation were somewhat presented. As a result, there were some differences in activity types and frequency according to the publishers. Science inquiry-experiment teachers need to proceed with the teaching and learning process by appropriately modifying inquiry contents and types of inquiry. It is necessary to continuously monitor whether the objectives of the 2015 revised science national curriculum are being applied and reflected through on-site science classes, and supplement them through subsequent studies.

In this study, the types of inquiry activities presented in grade 3 and 4 science textbooks according to the 2015 revised science curriculum were analyzed. They were compared according to grade level and five areas. The science textbooks for elementary 3rd and 4th graders contain many different types of inquiry activities, and are designed to cultivate science and core competencies through student-focused inquiry classes. As a result of analyzing the types of inquiry activities presented in the five areas of motion and energy(physics), materials(chemistry), life(life sciences), earth and space(earth sciences), and integration, the experiment and observation activities were the most common. Earth and space were the most simulated because of the nature of subjects that were difficult to experiment and observe. In order to achieve the goal of science education in elementary school, inquiry activities should be presented in consideration of students’ cognitive level, curriculum content, and subject areas.

Objective Despite increased survival in patients with cardiac arrest, it remains difficult to determine patient prognosis at the early stage. This study evaluated the prognosis of cardiac arrest patients using brain injury, inflammation, cardiovascular ischemic events, and coagulation/fibrinolysis markers collected 24, 48, and 72 hours after return of spontaneous circulation (ROSC). Methods From January 2011 to December 2016, we retrospectively observed patients who underwent therapeutic hypothermia. Blood samples were collected immediately and 24, 48, and 72 hours after ROSC. Neuron-specific enolase (NSE), S100-B protein, procalcitonin, troponin I, creatine kinase-MB, pro-brain natriuretic protein, D-dimer, fibrin degradation product, antithrombin-III, fibrinogen, and lactate levels were measured. Prognosis was evaluated using GlasgowPittsburgh cerebral performance categories and the predictive accuracy of each marker was evaluated. The secondary outcome was whether the presence of multiple markers improved prediction accuracy. Results A total of 102 patients were included in the study: 39 with good neurologic outcomes and 63 with poor neurologic outcomes. The mean NSE level of good outcomes measured 72 hours after ROSC was 18.50 ng/mL. The area under the curve calculated on receiver operating characteristic analysis was 0.92, which showed the best predictive power among all markers included in the study analysis. The relative integrated discrimination improvement and categoryfree net reclassification improvement models showed no improvement in prognostic value when combined with all other markers and NSE (72 hours). Conclusion Although biomarker combinations did not improve prognostic accuracy, NSE (72 hours) showed the best predictive power for neurological prognosis in patients who received therapeutic hypothermia.

Additional file 1. Supplementary Table S1. Time-Course Changes of Reflux Symptom Scores between the Two Groups. Supplementary Table S2. Frequency Distribution of Atypical Symptom among GERD Patients with Typical Symptom. Supplementary Table S3. Intention-to-treat (ITT) and per-protocol (PP) analysis of the Rate of the Sufficient Improvement according to GERD symptoms.

The purpose of this study was to analyze the teaching practice cases of pre-service science teachers in the United Kingdom, and to examine implications for pre-service teacher training. For this purpose, we analyzed the whole pre-service science teachers’ teaching practice in Postgraduate Certificate of Education (PGCE) course of the United Kingdom focusing on the lesson observation commentary (LOC), lesson observation summary (LOS) and the final profile of developmental phases, which were commented and evaluated by the mentor (science teacher) and the tutor (supervising professor) according to teacher qualification status (QTS). It implies that the improvement of the curriculum for the pre-service teacher training and the teacher training system to apply their pedagogical content knowledges to the actual field are needed, not just the type of education that fills the credits. In addition, it is necessary to increase the duration of pre-service teacher training, to elaborate teacher qualification standards, and to prepare ways for co-teaching by the mentor and the tutor. It is necessary to build up a teacher education system through the collaboration between schools and the college of education.

The purpose of this study was to investigate the level of scientific creativity according to the gender and talented division of scientifically gifted middle school students. To do this, the question to assess the scientific creativity was developed and applied it to 276 scientifically gifted students, and we compared the creativity level according to the gender and talented division. The scientific creativity of middle school scientifically gifted students was evaluated on the basis of six factors such as sensitivity, fluency, elaboration, logicality, empiricality, and originality. As a result, even though the scientific creativity of scientifically gifted students was found to be very low, their level scientific creativity depends on the gender and talented division. There was the significant correlation between factors of the scientific creativity of middle school scientifically gifted students. Especially, it showed a high correlation among originality, elaboration and empiricality. It suggested that educational approaches should be needed to improve their scientific creativity including teaching and learning methods and strategies in accordance with the gender and talented division, and continuously carried out.

The purpose of this study was to examine writing characteristics of scientifically gifted students about biological sciences. To do this study, we analysed their scientific writings related to biological sciences, which were written by scientifically gifted students of 16 groups (20 males and 20 females). They were being taught in the Science Education Institute for the Gifted adjacent for University. Scientific writings related to biological sciences were analysed through categories such as biotechnology, bioethics, sciences in a life, and human health and disease. Scientifically gifted students were lacking in the ability to construct writings and to logically express own contentions according to writings of them. Writings related to biotechnology and bioehics of biological sciences were not better than ones related to sciences in a life, and human health and disease. The results of this study suggested that it should be necessary to develop gifted educational programs to strengthen the scientific writing ability. Especially, scientifically gifted students need to be provided with educational contents about biological issues related to bioethics and biotechnology. keywords : scientifically gifted students, biological sciences, scientific writing, biotechnology, bioethics, gifted educational programs. 교신저자 : 심규철(skcshim@kongju.ac.kr) 2015년 2월 10일 접수, 2015년 3월 24일 수정원고 접수, 2015년 3월 30일 채택 I. 서 론 과학 글쓰기 활동은 과학적 의사소통 방법 중 하 나로 과학 교육과 영재 교육에서 중요하게 다루어 지고 있다(강성주, 박희경, 2011; 이혜정, 심규철, 2012). 과학 글쓰기는 주로 과학적 사실이나 개념, 법칙 등에 대한 사고 과정을 글로 표현하거나 자연 현상을 기반으로 관찰된 사실이나 실험 결과, 변환 된 데이터 등을 의미있는 산출물로 구성하는 과정 에 주로 활용된다. 그러므로 과학 글쓰기는 자신이 표현하려고 하는 것에 대하여 깊이 생각하고 재구 성하여 표현하는 활동이라 할 수 있으며(남경식, 2008; 이혜정 · 심규철, 2012; Furtak & Ruiz-Primo, 2008; Prain, 2006), 과학 개념 이해 와 과학적 사고력, 문제 해결 능력과 과학에 대한 흥미를 지속시킬 수 있는 도구로 활용될 수 있다 (김형자, 변정호, 권용주, 2012; 손정우, 2006; Hand et al., 2004; Prain, 2006). 과학 교육에서 과학 글쓰기 활동을 탐구활동 과 정에서의 관찰, 경향성, 분류, 발견 등의 사고 과정 을 강조하는 관찰하여 글쓰기, 분류하여 글쓰기, 요 약하여 글쓰기, 묘사하여 글쓰기, 서사하여 글쓰기 등의 유형으로 구분하기도 한다(손정우, 2006; 천 재훈, 손정우, 2004). 또한 연역적 사고력을 활용한 생명과학 관련 주제에 대한 과학영재들의 글쓰기 특성 분석 89 과학적 설명과 예측을 활용한 글쓰기 활동으로 구 분하기도 한다(천재훈, 2006). 그리고 과학적 사실 (내용)이나 자신의 관점에 대한 충분한 증거 제시, 과학적 사실과 자신의 의견 구분, 관점에 대한 적 절한 평가 준거 사용 등이 이루어질 수 있도록 하 는 비판적 사고를 활용한 다양한 관점에서 글쓰기, PMI를 활용한 글쓰기, 개념 만화를 활용한 글쓰기, 대화문 완성하는 글쓰기, 과학 오류 찾아 쓰기 활 동 등이 있다(손정우, 2006, 2009; 천재훈, 손정우, 2004). 이외에도 창의적 사고를 강조하는 비유를 통한 과학 글쓰기 활동, 은유를 통한 글쓰기, 상상 하여 글쓰기, 짧은 글 확장하여 글쓰기, 마인드맵을 활용한 글쓰기 활동 등으로 구분하고 있기도 하다 (박지영, 신영준, 2007; 손정우, 2010). 최근에는 통합 교과적 논술이 강조되면서 구체적 인 지식과 사고 과정을 중시하는 논술형 글쓰기가 강조되고 있기도 하다(권순희, 2011). 논술형 과학 글쓰기의 경우, 과학적 사고력, 창의적 사고력, 논 리적 사고력 뿐만 아니라 사고의 유연성이 강조되 고 있는데(천재훈, 2006), 글을 쓰는 과정에서 학 생들은 과학적 개념을 이해하고 정보를 활용하여 문제를 해석하며 자신의 사고 과정을 되돌아보게 하는 장점이 있다(강성주, 박희경, 2011; 이혜정, 심규철, 2012; Prain, 2006). 또한 과학 글쓰기 활 동을 통해 과학 지식에 대한 이해와 다른 사람과의 의사소통 능력을 함양할 수 있다. 따라서 과학 글 쓰기는 언어라는 도구를 통한 사고화 과정이며 문 제 해결 과정이라 할 수 있다(교육과학기술부, 2007; 배희숙, 2008; 이호진, 최경희, 2004). 논술 형 과학 글쓰기의 전체 구성은 서론부, 본론부, 결 론부의 구조를 취하며, 서론부에서는 문제를 제기 하고, 본론부에서는 제기된 문제에 대해 근거를 통 해 논증하고, 결론부에서는 이를 간단히 요약해서 정리하는 것이 바람직하다(이수형, 2010). 글의 유 형에 있어서는 서론부에 상황이나 설명, 예시 등을 제시하여 서술하는 경우가 많다(원진숙, 1995). 또 한 과학 글쓰기에 있어 문장 표현의 자연스러움과 올바른 어법 및 과학 글쓰기 적합한 단어 선택에 대한 지도는 학생들의 글쓰기 표현력을 향상시킬 수 있는 것으로 알려져 있다(이성영, 2001). 학생 들이 과학 글쓰기를 할 때 글쓰기 표현, 유형, 목 적, 방법 등을 다양하게 시도하면 학생들의 학습 능력이 향상되고 더 높은 수준의 사고를 할 수 있 기 때문이다(김주연, 2011; 이남은, 차희영, 천재 순, 2009; Hand & Prain, 2002). 한편 과학 영재들을 대상으로 교육 방법이나 평 가 도구로서 과학 글쓰기의 활용이나 과학의 과정 및 탐구 능력의 신장을 위한 방법으로서의 연구가 진행되어 왔으나(강성주, 박희경, 2011; 박은희, 홍 훈기, 2011; 손정우, 2010; 이혜정, 심규철, 2012), 과학 영재들의 학문 분야의 특성을 고려한 연구는 부족한 가운데 있다. 특히, 생명과학 관련 과학 글 쓰기 활동이나 생명과학 특성과 관련한 글쓰기에 대한 연구는 매우 부족한 상황이다. 이에 본 연구 에서는 과학영재들의 생명과학 글쓰기에서 나타난 글쓰기 특성을 조사 · 분석하여 과학 논리 및 논술 등의 교육 프로그램 개발, STS 관련 쟁점을 활용한 교수.학습 전략 및 방법 개발, 교육 자료 개발 등을 위한 과학 영재교육의 시사점을 얻고자 하였다. 중 학교 과학영재들의 생명과학 글쓰기 특성 분석을 통해 다음과 같은 연구 문제를 알아보고자 하였다. · 과학영재들의 생명과학 글쓰기에 나타난 글의 구성과 유형은 어떠한가? · 과학영재들의 생명과학 글쓰기에 나타난 논리 적 사고력과 표현력은 어떠한가?

This paper looks into the measurement of modeling ability in different fields like science, mathematics, operations research and management science and emulates the ideas to system analysis and design where modeling is a very useful skill. An assessment tool was designed to measure the graphical modeling ability in systems analysis and design. It was administered to 92 students and submitted to 10 MIS experts and tested statistically for its reliability and validity.

Blurred frames may happen sparsely in a video sequence acquired by consumer devices such as digital camcorders and digital cameras. In order to avoid visually annoying artifacts due to those blurred frames, this paper presents a novel motion deblurring algorithm in which a blurred frame can be reconstructed utilizing the high-resolution information of adjacent unblurred frames. First, a motion-compensated predictor for the blurred frame is derived from its neighboring unblurred frame via specific motion estimation. Then, an accurate blur kernel, which is difficult to directly obtain from the blurred frame itself, is computed using both the predictor and the blurred frame. Next, a residual deconvolution is applied to both of those frames in order to reduce the ringing artifacts inherently caused by conventional deconvolution. The blur kernel estimation and deconvolution processes are iteratively performed for the deblurred frame. Simulation results show that the proposed algorithm provides superior deblurring results over conventional deblurring algorithms while preserving details and reducing ringing artifacts.

An automatic classification system of the music genres is proposed. Based on the timbre features such as mel-frequency cepstral coefficients, the spectro-temporal features are obtained to capture the temporal evolution and variation of the spectral characteristics of the music signal. Mean, variance, minimum, and maximum values of the timbre features are calculated. Modulation spectral flatness, crest, contrast, and valley are estimated for both original spectra and timbre-feature vectors. A support vector machine (SVM) is used as a classifier where an elaborated kernel function is defined. To reduce the computational complexity, an SVM ranker is applied for feature selection. Compared with the best algorithms submitted to the music information retrieval evaluation exchange (MIREX) contests, the proposed method provides higher accuracy at a lower feature dimension for the GTZAN and ISMIR2004 databases.

Pectobacterium carotovorum subsp. carotovorum causes soft rot disease in various plants, including Chinese cabbage. The simple extracellular leucine-rich repeat (eLRR) domain proteins have been implicated in disease resistance. Rice leucine-rich repeat protein (OsLRP), a rice simple eLRR domain protein, is induced by pathogens, phytohormones, and salt. To see whether OsLRP enhances disease resistance to bacterial soft rot, OsLRP was introduced into Chinese cabbage by Agrobacterium-mediated transformation. Two independent transgenic lines over-expressing OsLRP were generated and further analyzed. Transgenic lines over-expressing OsLRP showed enhanced disease resistance to bacterial soft rot compared to non-transgenic control. Bacterial growth was retarded in transgenic lines over-expressing OsLRP compared to non-transgenic controls. We propose that OsLRP confers enhanced resistance to bacterial soft rot. Monitoring expression of defense-associated genes in transgenic lines over-expressing OsLRP, two different glucanases and Brassica rapa polygalacturonase inhibiting protein 2, PDF1 were constitutively activated in transgenic lines compared to non-transgenic control. Taken together, heterologous expression of OsLRP results in the activation of defense response and enhanced resistance to bacterial soft rot.

Adaptive interpolation filtering for sub-pel motion compensation is one of key techniques of ITU-T key technology area (KTA) codec. However, the adaptive interpolation filtering has a limitation in coding efficiency because of its frame-based update strategy of filter coefficients. Although switched interpolation filter with offset is presented as a sort of block-adaptive filtering for KTA codec, its coding efficiency is generally lower than that of the best adaptive interpolation filter. In order to overcome such a problem, this paper presents an advanced block-adaptive interpolation filtering using well-trained dictionaries which store optimized filter coefficients. We derive those filter coefficients by using learning-based super-resolution. The proposed block-adaptive interpolation filtering for quarter-pel motion compensation consists of two steps: up-scaling of half-pel accuracy and subsequent up-scaling of quarter-pel accuracy. The dictionary optimized for each step is employed to produce the precise up-scaled pixels. Simulation results show that the proposed algorithm improves higher coding efficiency than the previous adaptive interpolation filters for KTA.

Compared with conventional full-band speaker recognition systems, Advanced Missing Feature Theory (AMFT) produces a much lower error rate, but requires increased computational complexity. We propose a weighting function for the score calculation algorithm in AMFT. The weighting function is estimated by calculating the number of reliable spectral components. A modified mask is also proposed to reduce the number of reliable components based on the estimated weighting function. In the proposed Hard-mask MFT-8 (HMFT-8), only 8 elements are selected out of 10 spectral components in a feature vector. Compared with the full-band system and the AMFT, the proposed HMFT-8 gives a lower identification error rate by 16.95% and 2.67%, respectively. In terms of computational complexity, AMFT and HMFT-8 require 307 and 41 arithmetic and conditional operations for each frame, respectively.

In this paper, a novel genre classification algorithm is proposed for music recommendation system. Especially, to improve the classification accuracy, the band-pass filter for octave-based spectral contrast (OSC) feature is designed considering the psycho-acoustic model and actual frequency range of musical instruments. The GTZAN database including 10 genres was used for 10-fold cross validation experiments. The proposed multiple-octave based OSC produces better accuracy by 2.26% compared with the conventional OSC. The combined feature vector based on the proposed OSC and mel-frequency cepstral coefficient (MFCC) gives even better accuracy.

This paper presents a video super-resolution algorithm to interpolate an arbitrary frame in a low resolution video sequence from sparsely existing high resolution key-frames. First, a hierarchical block-based motion estimation is performed between an input and low resolution key-frames. If the motion-compensated error is small, then an input low resolution patch is temporally super-resolved via bi-directional overlapped block motion compensation. Otherwise, the input patch is spatially super-resolved using the dictionary that has been already learned from the low resolution and its corresponding high resolution key-frame pair. Finally, possible blocking artifacts between temporally super-resolved patches and spatially super-resolved patches are concealed using a specific de-blocking filter. The experimental results show that the proposed algorithm provides significantly better subjective visual quality as well as higher peak-to-peak signal-to-noise ratio than those by previous interpolation algorithms.

Music recordings have been digitalized such that huge size of music database is available to the public. Thus, the automatic classification system of music genres is required to effectively manage the growing music database. Mel-Frequency Cepstral Coefficient (MFCC) is a popular feature vector for genre classification. In this paper, the combined super-vector with Decorrelated Filter Bank (DFB) and Octave-based Spectral Contrast (OSC) using texture windows is processed by Support Vector Machine (SVM) for genre classification. Even with the lower order of the feature vector, the proposed super-vector produces 4.2 % improved classification accuracy compared with the conventional Marsyas system.

This paper proposes a computationally efficient learning-based super-resolution algorithm using k-means clustering. Conventional learning-based super-resolution requires a huge dictionary for reliable performance, which brings about a tremendous memory cost as well as a burdensome matching computation. In order to overcome this problem, the proposed algorithm significantly reduces the size of the trained dictionary by properly clustering similar patches at the learning phase. Experimental results show that the proposed algorithm provides superior visual quality to the conventional algorithms, while needing much less computational complexity.

This paper presents a motion-compensated scaler to interpolate an arbitrary frame in a low resolution video sequence by using sparsely existing high resolution key frames. In order to minimize visually annoying blocking artifact caused by block motion compensation, hierarchical motion estimation is bi-directionally performed for forward and backward key frames. Also, bi-directional overlapped block motion compensation based on the predicted motion vectors is applied to the high resolution key frames. Simulation results show that the proposed algorithm provides significantly better subjective visual quality as well as higher PSNR than previous interpolation algorithms. The proposed algorithm can provide a differentiated functionality to cutting-edge digital cameras, camcorders, etc.

DEA is a useful nonparametric method of measuring the relative efficiency of a DMU and yielding a reference target for an inefficient DMU. However, it is very difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually. The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.

The objective of this study was to evaluate the types and concentrations of volatile organic compounds (VOCs) in the newly-manufactured express bus under three different modes of operation (ambient...

Available solar radiation is an important crop growth monitoring and water balance that determines South Korea's crop productivity but has been poorly characterized. This paper studied the method of estimates for the available solar energy and crop growth monitoring based on data of Satellite imagery and meteorological observed data between 1982 and 2005 in South Korea. The objectives of this study are: a) assess of daily and monthly global radiation which most closely associated with rice growth; b) estimates for the available solar energy of the South Korea. Results from the study not only monitor the solar radiation in investigation area, but also illustrate the powerful potential to provide information about solar radiation based geostationary satellite imagery data.

Blurred frames may sparsely exist in a video sequence acquired by digital camcorder or digital camera. In order to remove the visually annoying artifact due to those blurred frames, this paper presents a novel motion deblurring algorithm where a blurred frame can be reconstructed utilizing adjacent unblurred frames. Firstly, a motion-compensated predictor of the blurred frame is derived from its neighboring unblurred frame using motion estimation. Then, an accurate blur kernel, which is difficult to obtain from a single blurred frame, is computed using both the predictor and the blurred frame. Next, again using those both frames, a residual deconvolution is proposed to reduce ringing artifacts inherent to conventional deconvolution. Simulation results show that the proposed algorithm provides superior deblurring results over conventional deblurring algorithms while preserving details with reduced ringing artifacts.

This paper presents a video super-resolution algorithm to interpolate an arbitrary frame in a low resolution video sequence from sparsely existing high resolution key pictures. Firstly, hierarchical motion estimation is performed between the input and the key low resolution frames on a patch basis. If motion-compensated error is small, an input LR patch is super-resolved by bi-directional overlapped block motion compensation. Otherwise, the input patch is spatially super-resolved using the dictionary which is learned from the key low resolution and its corresponding high resolution pictures beforehand. Finally, possible blocking artifacts between a motion-compensated patch and a spatially super-resolved patch are concealed using a specific de-blocking process. Experimental results show that the proposed algorithm provides significantly better subjective visual quality as well as objective quality than previous interpolation algorithms.

This paper presents a noise-robust super-resolution algorithm. In learning phase, a dictionary classified according to noise level is constructed, and then a high-resolution image is synthesized using the dictionary in the inference phase. Experimental results show that the proposed algorithm outperforms the existing algorithms even for noisy images.

As the nano-lithography technology continues to develop towards advanced generation of ArF immersion lithography, the quality of ArF EAPSM becomes the most valuable factor for worldwide Maskshop. Therefore outturn of ArF EAPMS increase continuously, and people who work in the fields of semiconductor engineering give consequence to good quality of ArF EAPSM until the EUV lithography generation. Because 300mm wafer litho-facility use higher exposure energy, wider shot field and more shots per a wafer for achieving more memory(DRAM or Flash) chips than 200mm exposure facility, photo engineer wants unchanged initial condition of mask quality(CD MTT, CD Uniformity, repeating defect, phase shift and transmittance). In other words, mask manufacturer must focus on the concept of ArF EAPSM 'life time'. We have investigated the influence grade inducing the lithographic variation between the growth of exposure energy based Haze phenomena, thin organic pellicle membrane characteristics, and we have verified that the ArF pellicle durability is one of the most important evidence for improvement of life time of ArF EAPSM. In this study, related with ArF EAPSM life time, we tried to evaluate the influence of ArF pellicle characteristic consisting of pellicle membrane transmittance strength (durability against ArF laser source) and non acid mask condition for the period of non Haze contamination without added re-pellicle → re-cleaning cycle. Metrological inspection and evaluation was conducted with several equipment and analysis including mask inspection, Scatterometer, IC, ArF laser accelerator.

This study proposes fast super-resolution algorithms to up-scale an input low-resolution image into a high-resolution image. Conventional learning-based super-resolution algorithms require large memory space to store a huge amount of synthesis information, and they require significant computation because of the large number of two-dimensional matching operations. To mitigate this problem, the authors train a dictionary using one-dimensional patch-based training and K-means clustering at the learning phase, and they use one-dimensional matching and interpolation based on the trained dictionary at the synthesis phase. Such one-dimensional content-adaptive interpolation is applied separately in horizontal and vertical directions. In addition, the authors propose a hybrid algorithm in which directional interpolation is utilised for vertical interpolation to further reduce the dictionary size and the so called staircase artefact. Simulation results show that the proposed algorithm has higher peak-to-peak signal-to-noise ratio (PSNR) and structure similarity (SSIM) values while providing significantly smaller dictionary size and faster computation than the latest learning-based super-resolution algorithm.

Conventional learning-based superresolution algorithms tend to boost noise components existing in input images because the algorithms are usually learned in a noise-free environment. Even though a specific noise reduction algorithm is applied to noisy images prior to superresolution, visual quality degradation is inevitable due to the mismatch between noise-free images and denoised images. Accordingly, we present a noise-robust superresolution algorithm that overcomes this problem. In the learning phase, a dictionary classified according to noise level is constructed, and then a high-resolution image is synthesized using the dictionary in the inference phase. Experimental results show that the proposed algorithm outperforms existing algorithms for various noisy images.