• Journal of IKEEE
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• v.21 no.1
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• pp.46-65
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• 2017

This paper proposes a fast patch-based de-blurring algorithm including kernel estimation based on the angle between the edge and the blur direction. For de-blurring, image patches from the most informative edges in the blurry image are used to estimate a kernel with low computational cost. Moreover, the kernels of each patch are estimated based on the correlation between the edge direction and the blur direction. This makes the final kernel more reliable and creates an accurate latent image from the blurry image. The combination of directionally oriented kernel estimation and patch-based de-blurring is faster and more accurate than existing state-of-the art methods. Experimental results using various test images show that the proposed method achieves its objectives: speed and accuracy.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.484-494
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• 2018

The uniform motion blur removing algorithm of Cho et al. has the problem that the edge region of the image cannot be restored clearly. We propose the effective algorithm to overcome this problem by using shock filter that reconstructs a blurred step signal into a sharp edge, and convolutional neural network (CNN) that learns by extracting features from the image. Then uniform motion blur kernel is estimated from the latent sharp image to remove blur in the image. The proposed algorithm improved the disadvantages of the conventional algorithm by reconstructing the latent sharp image using shock filter and CNN. Through the experimental results, it was confirmed that the proposed algorithm shows excellent reconstruction performance in objective and subjective image quality than the conventional algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.2
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• pp.109-121
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• 2020

Depth calculation of objects in a scene from images is one of the most studied processes in the fields of image processing, computer vision, and photogrammetry. Conventionally, depth is calculated using a pair of overlapped images captured at different view points. However, there have been studies to calculate depths from a single image. Theoretically, it is known to be possible to calculate depth using the diameter of CoC (Circle of Confusion) caused by defocus under the assumption of a thin lens model. Thus, this study aims to verify the validity of the thin lens model to calculate depth from edge blur amount which corresponds to the radius of CoC. For this study, a commercially available DSLR (Digital Single Lens Reflex) camera was used to capture a set of target sheets which had different edge contrasts. In order to find out the pattern of the variations of edge blur against varying combination of FD (Focusing Distance) and OD (Object Distance), the camera was set to varying FD and target sheet images were captured at varying OD under each FD. Then, the edge blur and edge displacement were estimated from edge slope profiles using a brute-force method. The experimental results show that the pattern of the variations of edge blur observed in the target images was apart from their corresponding theoretical amounts derived under the thin lens assumption but can still be utilized to calculate depth from a single image for the cases similar to the limited conditions experimented under which the tendency between FD and OD is manifest.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.1108-1110
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• 2004

LCDs show motion image blur due to slow response time and a hold-type driving method. In this paper, we investigate motion blur phenomena and quantitatively show that the motion blur can be significantly reduced through a combination of dynamic capacitance compensation (DCC) and black data insertion.

• Journal of the Semiconductor & Display Technology
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• v.7 no.2
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• pp.29-33
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• 2008

LCD panels are increasingly used to show moving image material, for example in LCD television sets. However, moving images become blurred on LCD panels. One of the causes of motion blur is the slow reaction of LC(liquid crystal) cell to change in the pixel value. Another cause of motion blur is the hold-type characteristic of the LCD panel, during the frame time the image is shown continuously. This type of motion blur can be reduced with a scanning backlight. We have designed and fabricated a scanning backlight system that solves the hold-type characteristic problem in a way that Flat fluorescent lamp divided 6 blocks was scanned 60Hz.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.

• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.79-82
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• 2015

The handicap for investigating the aero-optical effect focuses on the accurate prediction on the index refraction fluctuation or density fluctuation. In recent years, with the development of CFD techniques and optical experimental techniques, the comprehension have developed on the aero-optical transmitting effect in many kinds of complex flow. This study mainly introduces the optical aberration in compressible mixing layer. And then the debates about the mechanism of aero-optical effects and assessment of image blur also present.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.4
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• pp.1-6
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• 2010

We can see the motion blur phenomenon on theedge of the moving picture when it moves in the LCDs. To reduce this phenomenon, we suggested a new over-deriving method, implemented on the board XUP Virtex-2 Pro Development System by using Virtex-2 Pro XUP XC2VP30 and improved the Motion Blur. In this method, we did not use additional parts except for a SDRAM. Hardware implementation for IP and data interface were handled in software. In this paper, we used the moving bar and the moving video image as a design model. We also showed that the afterimage was reduced and the vivid moving images was displayed. through this method.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.27-33
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• 2009

We propose an efficient method for single image motion deblurring using edge prediction. Previous methods for motion deblurring from a single image have been based on total variation or natural image statistics. In contrast, our method predicts sharp edges by applying bilateral and shock filters and manipulating image gradients directly, and estimates motion blur using the predicted sharp edges. Sharp edge prediction makes our method possible to deblur efficiently with less computation. Results show that our method can effectively and efficiently restore images degraded by large complex motion blur.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.81-87
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• 1999

In this research, we propose a field mismatch compensation method for interlaced scan image and a image restoration technique for removing motion blur. In order to compensate field mismatch, the edge classification-based linear interpolation technique and the method using the object-based motion compensation are described. We also propose an edge estimation method and an motion-based image segmentation algorithm. For removing motion blur, we adopt an adaptive iterative image restoration method using the motion-based segmentation result to improve the quality of restored image.