• Proceedings of the KSRS Conference
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• v.2
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• pp.631-634
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• 2006

Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2485-2489
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• 2005

This paper introduces a new preprocessing scheme to replace original data of gray scale images with particular ordered data so that performance of lossless compression can be improved more efficiently. As a kind of preprocessing technique to maximize performance of entropy encoder, the proposed method converts the input image data into more compressible form. Before encoding a stream of the input image, the proposed preprocessor counts co-occurrence frequencies for neighboring pixel pairs. Then, it replaces each pair of adjacent gray values with particular ordered numbers based on the investigated co-occurrence frequencies. When compressing ordered image using entropy encoder, we can expect to raise compression rate more highly because of enhanced statistical feature of the input image. In this paper, we show that lossless compression rate increased by up to 37.85% when comparing results from compressing preprocessed and non-preprocessed image data using entropy encoder such as Huffman, Arithmetic encoder.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.100-103
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• 2007

A microlens array has been required to improve light conversion efficiency in image sensors. A microlens array can be usually fabricated by photoresist reflow, hot-embossing, micro injection molding, and UV-imprinting. Among these processes, a UV-imprinting, which is operated at room temperature with relatively low applied pressure, can be a desirable process to integrate microlens array on image sensors, because this process provides the components with low thermal expansion, enhanced stability, and low birefringence, furthermore, it is more suitable for mass production of high quality microlens array. In this study, to analyze the optical properties of the wafer scale microlens array integrated image sensor, another wafer scale simulated image sensor chip array was designed and fabricated. An aspherical square microlens was designed and integrated on a simulated image sensor chip array using a UV-imprinting process. Finally, the optical performances were measured and analyzed.

• Journal of the Korean Home Economics Association
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• v.50 no.8
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• pp.113-123
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• 2012

This research has an objective of investigating the challenges that student teachers encounter during practicum, the difference between teachers' image based on sociodemographic variables, recognition and satisfaction for practicum, and the effect of teachers' image and practicum experience on the satisfaction for the practicum. The participants of this study included 500 student teachers who enrolled in the department of early childhood education in a 2 or 3-year college or a 4-year university and completed practicum in the Chungcheong area. The instruments for this study were Teacher's Image Scale, Practicum Experience Scale, Practicum Satisfaction Scale and a questionnaire for sociodemographic variables. The results were as follows: First, the highest level of teachers' image was obtained for student teachers enrolled in a 2-year college, completed practicum in large cities and finished practicum at an institution with a size of 3-6 classes. Also, the highest level of 'recognition for practicum' of student teachers was observed when they were instructed by a guidance teacher with a degree from a graduate school and with a first degree certification in public kindergarten. Second, the satisfaction for practicum of student teachers was mostly affected by' the atmosphere of the practice institutions', while personality affected the teachers' image.

• Journal of the Korean Graphic Arts Communication Society
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• v.20 no.1
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• pp.28-44
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• 2002

Wavelet transformation in image compression is to offer higher image compressibility and high-quality by quantization and entropy encoding. More image quality is good that reconstructed image by wavelet calculation than acquire cosine transform. Therefore, wavelet itself is function if it is wavelet's feature, in this function, do processing applying difference scale and resolution. That is, this is not that fixed resolution has been decided like existent compression way, when it regulated scale, damage goes in pixel and picture looks like break without giving damage entirely in reflex even if magnify or curtail Decoding. Therefore, this paper is in Image that using new wavelet application compression way research that see applies comparing In each image noted this time compressing step by step with circle image compression efficiency recognize. Also, estimated quality pass through by printing of compressed image, investigated compression ratio of most suitable that get print of high quality and elevation of transmission speed.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.974-977
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• 1999

In this paper, we have proposed the hardware architecture which implements the algorithm for retaining the connectivity which prevents disconnecting in the gray-scale image thinning To perform the image thinning in a real time which find a skeleton in image, it is necessary to examine the connectivity of the skeleton in a real time. The proposed architecture finds the connectivity number in the 4-clock period. The architecture is consists of three blocks, PS(Parallel to Serial) Converter and State Generator and Ridge Checker. The PS Converter changes the 3$\times$3 gray level image to four sets of image pixels. The State Generator examine the connectivity of the central pixel by searching the data from the PS Converter. the 3$\times$3 gray level image determines. The Ridge Checker determines whether the central pixel is on the skeleton or not The proposed architecture finds the connectivity of the central pixel in a 3$\times$3 gray level image in the 4-clocks. The total circuits are verified by the design tools and operate correctly.

• Fashion & Textile Research Journal
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• v.12 no.1
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• pp.1-9
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• 2010

A purpose of this study was to find out how the casual and formal style clothes of stripe pattern giving variety by pattern direction, pattern width, and contrast coloration have an effect on image of wearers. 432 stimuli were made and 2,800 testee evaluated them using semantic differential scale. As a result, five image dimensions were drawn as a factor of attractiveness, activeness, gracefulness, visibility, and tenderness. In consequence of analysing the image difference by stripe pattern and clothing style, the stripe pattern and clothing style affect image presentation as a significant clue. And besides, as a result of positioning stimuli by image, pattern direction, coloration, and tone combination were important clues that decide image. Consequently, clothing style, stripe pattern, and contrast coloration were made clear as an efficient parameter in image presentation of clothing wearers.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.367-377
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• 2012

The goal of the image restoration is to find a good approximation of the original image for the degraded image, the blurring matrix, and the statistics of the noise vector given. Fast truncated Lagrange (FTL) method has been proposed by G. Landi as a image restoration method for large-scale ill-conditioned BTTB linear systems([3]). We implemented FTL method for the image restoration problem with reflective boundary condition which gives better reconstructions of the unknown, the true image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.980-997
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• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.