• Current Optics and Photonics
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• v.4 no.3
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• pp.200-209
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• 2020

We describe an approach that uses a bilateral filter to reduce the ringing artifact in motion-blurred restoration image. It takes into account the specific physical structure of the ringing artifact combined with the properties of the human visual system. To properly reduce the ringing artifact, each of the adjacent pixels is limited in a straight line which has a given direction. To protect the edges and the texture regions of an image, our algorithm divides the image into texture regions and flat regions, and the artifact reduction algorithm is only applied to the flat region. Finally, we use 8 typical images and 5 objective quality evaluation indices to evaluate our algorithm. Experimental results show that our algorithm can obtain better results in subjective visual effect and in objective image quality evaluation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.52-55
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• 1996

Though the increment of using computer vision system in modern industry, there are lots of difficulties to measure precisely because of measurement error distortion phenomenon. Between these reasons, the distortion of edge is dominant reason which is occured by the blurred image. The blurred image is happened when camera can not discriminate its precise focus. To correct and generalize distortion phenomenon is imprrtant. Thus we must fix the discrimination criteria which is collected by image recognition of precise focus. The edge of image means discontinuous point of intensity, and the component of edge is discribed as high frequency component at special domain specturm of image. The good condition of focus means there are much high frequency energy in image. The method of discribing high frequency energy is gradient operater which determines the condition of focus.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4060-4079
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• 2020

Blur is an important type of image distortion. How to evaluate the quality of blurred image accurately and efficiently is a research hotspot in the field of image processing in recent years. Inspired by the multi-scale perceptual characteristics of the human visual system (HVS), this paper presents a no-reference image blur/sharpness assessment method based on multi-scale local features in the spatial domain. First, considering various content has different sensitivity to blur distortion, the image is divided into smooth, edge, and texture regions in blocks. Then, the Gaussian scale space of the image is constructed, and the categorized contrast features between the original image and the Gaussian scale space images are calculated to express the blur degree of different image contents. To simulate the impact of viewing distance on blur distortion, the distribution characteristics of local maximum gradient of multi-resolution images were also calculated in the spatial domain. Finally, the image blur assessment model is obtained by fusing all features and learning the mapping from features to quality scores by support vector regression (SVR). Performance of the proposed method is evaluated on four synthetically blurred databases and one real blurred database. The experimental results demonstrate that our method can produce quality scores more consistent with subjective evaluations than other methods, especially for real burred images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.490-495
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• 1996

Though the increment of using computer vision system in modern industry, there are lots of difficulties to measure precisely because of measurement error distortion phenomenon. Among these reasons, the distortion of edge is dominant reason which is occurred by the blurred image. The blurred image is happened when camera can not discriminate its precise focus. To calibrate and generalize distortion phenomenon is important. Thus, we must fix the discrimination criteria which is collected by image recognition of precise focus. Also, radial distortion causes an inward or outward displacement of a given image point from its ideal location. This type of distortion is mainly caused by flawed radial curvature curve of the elements. Thus, we were analyzed the distortion in terms of the changed with lens magnification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.645-650
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• 2015

Image restoration is required when the image is blurred due to out of focus or motion during the image acquisition. This type of image restoration is known as ill-posed inverse problem because the estimate of an original image should be derived from only one blurred image. This paper introduces a reference image to facilitate the restoration process. The experimental result shows that computation time is significantly reduced, compared with other methods. The proposed method obtains the estimate of the kernel used in blurring processing. New cost function is defined to update both the image and the kernel alternately. In the last stage, Wiener filter produces the estimate of an original image using the kernel and the reference image.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.693-696
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• 2008

Motion blurs are caused by relative motion between the camera and the scene. The blurred image needs to be restored because undesired blur effect degrades the quality of the image. In this paper, we propose a new method for the identification of blur parameters. Experiment shows that the proposed method identifies blur extent regardless of the size of the blur and the object in the original image.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1251-1259
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• 2007

Motion blurs are caused by relative motion between the camera and the scene. The blurred image needs to be restored because undesired blur effect degrades the quality of the image. In this paper, we propose a new method for the identification of blur extent. Experiment shows that the proposed method identifies blur extent regardless of the size of the blur and the object in the original image.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.75-81
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• 2012

In this paper, restoration methods were applied to restore analog medicine images with an aged image added and then blurred by noises. To restore the aged image blurred by the blurring function and added by noises, it was applied to the restoration methods which are inverse filtering and wiener filtering which are linear restoration techniques and Lucy-Richardson's algorithm which is nonlinear restoration technique. Moreover, ROC curve, a subjective evaluation method, was applied to evaluate the image quality of the restoration image. The wiener filtering using the ratio of constants acquired better image than the inverse filtering, but both of them couldn't improve ability to make a diagnosis. The restoration image applied to Lucy-Richardson algorithm was the best performance of the applied techniques and its sensitivity and specitivity were improved by 15[%] as much performance as the original aged image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.165-175
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• 2005

If the interlaced scan type camera moves while an image is filming from the camera, blur is often created from the misalignment of the two images of even and odd lines. This paper proposed an algorithm which removes the misalignment of the even and odd line images cased by the vibration of the interlaced scan type camera. The blurred original image is separated into the even and the odd line images as half size. Based on these two images, two full sized images are generated using interpolation technique. If a big difference between these two interpolated images is generated, the original image is taken while the camera is moving. In this case, a deblurred image is obtained with the alignment of these separated two images through feature point extraction, feature point matching, sub-pixel matching, outlier detection, and image mosaicking processes. This paper demonstrated that the proposed algorithm can create clear images from blurred images caused by various camera motions.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.529-534
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• 1986

A holographic iverse filter has been used for optical image deblurring by modeling the PSF(point spread function)of blurred system. This paper presents the optical image restoration of an accidentally blurred photograph by using a simgle inverse filter which is obtained from a blurrec PSF by analyzing the Fourier spectrum of the supposely defocused photograph itself. The filter, a positive transparency having gamma of 2, has amplitude and phase informations simulatneously.