• Journal of Korea Game Society
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• v.17 no.1
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• pp.17-26
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• 2017

Several algorithms have been introduced to render motion blur in real time by solving the visibility problem in the spatio-temporal domains. However, some algorithms render at interactive frame rates but have artifacts or noise. Therefore, we propose a new algorithm that renders real-time motion blur using extruded triangles. Our method uses two triangles in the previous and the current frame to make an extruded triangle then send it to the rasterization. To solve the occlusion between extruded triangles for a given pixel, we introduce a combining solution using a sorting in front to back order and bitwise operations in the spatio-temporal dimensions.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.85-99
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• 2015

TDI CCD sensors are being used for most of the electro-optical camera mounted on the low earth orbit satellite to meet high performance requirements such as SNR and MTF. However, the CMOS sensors which have a lot of implementation advantages over the CCD, are being upgraded to have the TDI function. A few methods for improving the issue of motion blur which is apparent in the CMOS sensor than the CCD sensor, are being introduced. Each pixel can be divided into a few sub-pixels to be read more than once as is the same case with three or four phased CCDs. The fill factor can be reduced intentionally or even a kind of mask can also be implemented at the edge of pixels to reduce the blur. The motion blur can also be reduced in the TDI CMOS sensor by reducing the integration time from the full line scan time. Because the integration time can be controlled easily by the versatile control electronics, one of two performance parameters, MTF and SNR, can be concentrated dynamically depending on the aim of target imaging. MATLAB simulation has been performed and the results are presented in this paper. The goal of the simulation is to compare dynamic MTFs affected by the different methods for reducing the motion blur in the TDI CMOS sensor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.30 no.3
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• pp.1-8
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• 2016

In this paper, we proposed a new driving scheme to reduce the motion blur and save the power for OLEDs(organic light emitting diodes). We adopted a DVS (dynamic voltage scaling) method to reduce power consumption and the division of TV field to improve motion blur. In the proposed scheme, BEW (Blur Edge Width) was decreased to the ratio of 1/4 compared to the conventional scheme under the optimal conditions. In this scheme, the gray levels to which the DVS method can be applied were divided into much smaller groups depending on the number of subfields. Therefore, our scheme does not guarantee less power consumption for every image compared to the conventional scheme. However, the new scheme can move the gray levels adopting the DVS to higher gray levels. Thus, we can save power even when having images at high gray levels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10B
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• pp.1953-1962
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• 1999

While acquiring the image, the shaking of the image capturing equipment or the object seriously damages the image quality. This phenomenon, which degrades the clarity and the resolution of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function defined as Peak-trace domain. In The Peak-trace domain, the noise dominant region for calculating the noise variance and the signal dominant region for extracting the degree and the length of the motion blur are defined and analyzed. Using the information of the Peak-trace in the signal dominant region, we can find the direction of the motion regardless of the noise corruption. Weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the length of the motion blur based on one dimensional Cepstrum. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

• 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 the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.80-84
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• 2014

Dark channel prior means that, for undistorted outdoor images, at least one color channel of a pixel or its neighbors have values close to 0, and thus the prior can be used to estimate the amount of distortion for given distorted images. In other words, if an image is distorted by blur, its dark channel values are averaged with neighbor pixel values and thus increase. This paper proposes a method that estimates blur strengths by analyzing the variation of dark channel values caused by blur. Through experiments with images distorted by Gaussian and horizontal motion blur with given strengths, the usefulness of the proposed method is verified.

• ETRI Journal
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• v.38 no.3
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• pp.502-509
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• 2016

Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, and $135^{\circ}$) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.281-289
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• 2000

While acquiring images, the relative motion between the imaging device and the object scene seriously damages the image quality. This phenomenon is called motion blur. The peak-trace approach, which is our recent previous work, identifies important parameters to characterize the point spread function (PSF) of the blur, given only the blurred image itself. With the peak-trace approach the direction of the motion blur can be extracted regardless of the noise corruption and does not need much Processing time. In this paper stochastic peak-trace approaches are introduced. The erroneous data can be selected through the ML classification, and can be made small through weighting. Therefore the distortion of the direction in the low frequency region can be prevented. Using the linear prediction method, the irregular data are prohibited from being selected as the peak point. The detection of the second peak using the proposed moving average least mean (MALM) method is used in the Identification of the motion extent. The MALM method itself includes a noise removal process, so it is possible to extract the parameters even an environment of heavy noise. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.774-779
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• 2016

The conventional methods using color signal for tracking the movement of the object require a lot of calculation and the performance is not accurate. In this paper, we propose a method to effectively track the moving objects using the depth information from a depth camera. First, it separates the background and the objects based on the depth difference in the depth of the screen. When an object is moved, the depth value of the object becomes blurred because of the phenomenon of Motion Blur. In order to solve the Motion Blur, we observe the changes in the characteristics of the object (the area of the object, the border length, the roundness, the actual size) by its velocity. The proposed algorithm was implemented in the simulation that was applied directly to the tracking of a golf ball. We can see that the estimated value of the proposed method is accurate enough to be very close to the actual measurement.

• 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.