• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.199-202
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• 2003

In this paper, we propose a new 3D coding method for heterogeneous systems over enhanced Access Grid (e-AG) with 3D display using spatio-temporal scalability. The proposed encoder produces four bit-streams: one base layer and enhancement layer l, 2 and 3. The base layer represents a video sequence for left eye with lower spatial resolution. An enhancement layer l provides additional bit-stream needed for reproduction of frames produced in base layer with full resolution. Similarly, the enhancement layer 2 represents a video sequence for right eye with lower spatial resolution and an enhancement layer 3 provides additional bit-stream needed for reproduction of its reference pictures with full resolution. In this system, temporal resolution reduction is obtained by dropping B-frames in the receiver according to network condition. The receiver system can select the spatial and temporal resolution of video sequence with its display condition by properly combining bit-streams.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.272-275
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• 2020

Light Field (LF) cameras capture both spatial and directional information of light rays. Current LF cameras have a problem of a low spatial resolution. There have been lots of existing works carried out to improve the resolution of LF images. In this paper, those existing works will be divided into two categories: hardware-based approaches and software-based approaches, and we will look into and compare several experiment results in order for LF spatial resolution enhancement. Finally, the direction for the future spatial resolution enhancement will be suggested.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.407-414
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• 2014

The aim of the present study was to carry out quantitative analysis of spatial resolution for the influence of the focus size and digital image post-processing on the Computed Radiography (CR). The modulation transfer functions of an edge measuring method (MTF) was used for the evaluation of the spatial resolution. The focus size of X-ray tube was used the small focus (0.6 mm) and the large focus (1.2 mm). We evaluated the 50% and 10% of MTF for the enhancement of edge and contrast by using multi-scale image contrast amplification (MUSICA) in digital image post-processing. As a results, the edge enhancement than the contrast enhancement were significantly higher the spatial resolution of MTF 50% in all focus. Also the spatial resolution of the obtained images in a large focus were improved by digital image processing. In conclusion, the results of this study should serve as a basic data for obtain the high resolution clinical images, such as skeletal and chest images on the CR.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.409-412
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• 1996

Ultrasonic sensors are widely used in various applications due to advantages of low cost, simplicity in construction, mechanical robustness, and little environmental restriction in usage. But the main purposes of the noncontact sensing are rather narrowly confined within object detection and distance measurement. For the application of object recognition, ultrasonic sensors exhibit several shortcomings of poor directionality which results in low spatial resolution of objects, and specularity which gives frequent erroneous range readings. To resolve these problems in object recognition, an array of the sensor has been used. To improve the spatial resolution, more number of sensors are used in essence throughout the various devices of the sensor arrays. Under the disguise of a fixed number of the sensors, the array can be shifted mechanically in several steps. In this paper we propose a practical sensor resolution enhancement method using an electronic circuit accompanying the sensor array. The circuit changes the transmitter output voltage in several steps. Using the known sensor characteristics, a set of different return echo signals provide enhanced spatial resolution. The improvement is obtained with neither the cost of the increased number of the sensors nor extra mechanical devices.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.115-118
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• 2004

Images with high resolution are desired and often required in many visual applications. When resolution can not be improved by replacing sensors, either because of cost or hardware physical limits, super resolution image reconstruction method is what can be resorted to. Super resolution image reconstruction method refers to image processing algorithms that produce high quality and high resolution images from a set of low quality and low resolution images. The method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. The method can be either the frequency domain approach or the spatial domain approach. Much of the earlier works concentrated on the frequency domain formulation, but as more general degradation models were considered, later researches had been almost exclusively on spatial domain formulations. The method in spatial domains has three stages: i) motion estimate or image registration, ii) interpolation onto high resolution grid and iii) deblurring process. The super resolution grid construction in the second stage was discussed in this paper. We applied the Maximum A­Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from a set of low resolution images and compared the results with those from other known interpolation methods.

• Journal of the Optical Society of Korea
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• v.7 no.4
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• pp.216-223
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• 2003

We report a technique that improves the spatial resolution of optical coherence tomography (OCT) by utilizing fiber-based spectral filtering. The proposed technique improves the resolution by filtering out the erbium’s characteristic peak from the amplified spontaneous emission (ASE) source spectrum, and reshaping the spectrum to Gaussian-like. We used a long period fiber grating (LPG) and an erbium doped fiber (EDF) absorber for the spectral filtering. An in-house made ASE source as well as a commercial ASE source [ASE-FL7002] was used as the OCT sources to study the proposed technique. The resolution of the OCT based on an in-house made ASE source is enhanced from 200 to 40 ㎛ with an LPG. While, the resolution of the OCT based on a commercial ASE source is enhanced from 25 to 19 ㎛ with the aid of an EDF absorber. However, sidelobes still exist in the interferogram due to imperfect spectral filtering, which limited the resolution. Further enhancement in the spatial resolution of the OCT system using the ASE source is possible with the aid of cascaded LPGs and/or carefully designed EDF absorber.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.15-22
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• 2020

In this paper, we proposed a deep learning based super-resolution method that combines Channel Attention and Spatial Attention feature enhancement methods. It is important to restore high-frequency components, such as texture and features, that have large changes in surrounding pixels during super-resolution processing. We proposed a super-resolution method using feature enhancement that combines Channel Attention and Spatial Attention. The existing CNN (Convolutional Neural Network) based super-resolution method has difficulty in deep network learning and lacks emphasis on high frequency components, resulting in blurry contours and distortion. In order to solve the problem, we used an emphasis block that combines Channel Attention and Spatial Attention to which Skip Connection was applied, and a Residual Block. The emphasized feature map extracted by the method was extended through Sub-pixel Convolution to obtain the super resolution. As a result, about PSNR improved by 5%, SSIM improved by 3% compared with the conventional SRCNN, and by comparison with VDSR, about PSNR improved by 2% and SSIM improved by 1%.

• The Journal of Information Technology
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• v.5 no.2
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• pp.69-80
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• 2002

Conventionally, we have used an acoustic microscope at single operating frequency. The resolution and quality of the measured images are determined by transducer of the microscope. In this paper, we have studied Vertical Resolution Enhancement with Acoustic Reflection Microscope using combining bases of support for SFR(Spatial Frequency Response). Increased Vertical resolution can be obtained by taking three-dimensional images at more that one frequency and numerically combining the results. As results of the experiment, we could get enhanced images with the rate of contrast in proportion to the changing rate of depth.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.345-354
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method has proven to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper, we applied the super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and are overlapped at high rate. We constructed the observation model between the HR images and LR images applied with the Maximum A Posteriori(MAP) reconstruction method which is one of the major methods in the super resolution grid construction. Based on the MAP method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.197-200
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper we applied super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and overlapped for high rate. We constructed the observation model between the HR images and LR images applied by the Maximum A Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.