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OH, Taegeun,LEE, Sanghoon,GIL, Gye-Tae The Institute of Electronics, Information and Comm 2009 IEICE TRANSACTIONS ON COMMUNICATIONS - Vol.92 No.1
<P>A cell planning and resource allocation scheme called EBRD (Enhanced Bandwidth and Region Division) is presented for improving channel capacity and for maintaining a proper QoS (Quality of Service) over the downlink OFDMA (Orthogonal Frequency Division Multiple Access) system. Through an optimal combination of sectorization and frequency overlay, the EBRD scheme improves both channel capacity and outage probability. In order to analyze the performance of the proposed algorithm, the outage probability is obtained as a closed numerical form. In the simulation, the EBRD scheme outperforms 3-sectorization in terms of throughput and outage probability.</P>
No-Reference Sharpness Assessment of Camera-Shaken Images by Analysis of Spectral Structure
Taegeun Oh,Jincheol Park,Seshadrinathan, Kalpana,Sanghoon Lee,Bovik, Alan Conrad IEEE 2014 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.23 No.12
<P>The tremendous explosion of image-, video-, and audio-enabled mobile devices, such as tablets and smart-phones in recent years, has led to an associated dramatic increase in the volume of captured and distributed multimedia content. In particular, the number of digital photographs being captured annually is approaching 100 billion in just the U.S. These pictures are increasingly being acquired by inexperienced, casual users under highly diverse conditions leading to a plethora of distortions, including blur induced by camera shake. In order to be able to automatically detect, correct, or cull images impaired by shake-induced blur, it is necessary to develop distortion models specific to and suitable for assessing the sharpness of camera-shaken images. Toward this goal, we have developed a no-reference framework for automatically predicting the perceptual quality of camera-shaken images based on their spectral statistics. Two kinds of features are defined that capture blur induced by camera shake. One is a directional feature, which measures the variation of the image spectrum across orientations. The second feature captures the shape, area, and orientation of the spectral contours of camera shaken images. We demonstrate the performance of an algorithm derived from these features on new and existing databases of images distorted by camera shake.</P>
Blind Sharpness Prediction Based on Image-Based Motion Blur Analysis
Taegeun Oh,Sanghoon Lee [Institute of Electrical and Electronics Engineers 2015 IEEE transactions on broadcasting Vol.61 No.1
<P>For high bit rate video, it is important to acquire the video contents with high resolution, the quality of which may be degraded due to the motion blur from the movement of an object(s) or the camera. However, conventional sharpness assessments are designed to find focal blur caused either by defocusing or by compression distortion targeted for low bit rates. To overcome this limitation, we present a no-reference framework of a visual sharpness assessment (VSA) for high-resolution video based on the motion and scene classification. In the proposed framework, the accuracy of the sharpness estimation can be improved via pooling weighted by the visual perception from the object and camera movements and by the strong influence from the region with the highest sharpness. Based on the motion blur characteristics, the variance and the contrast over the spectral domain are used to quantify the perceived sharpness. Moreover, for the VSA, we extract the highly influential sharper regions and emphasize them by utilizing the scene adaptive pooling. Based on the subjective results, we demonstrate that the VSA can measure the video sharpness more accurately than other sharpness measurements for high-resolution video.</P>