• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.43-48
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• 2014

Usually, image deconvolution is applied as a preprocessing step in surveillance systems to reduce the effect of motion or out-of-focus blur problem. In this paper, we propose a blind-image deconvolution filtering approach based on genetic programming (GP). A numerical expression is developed using GP process for image restoration which optimally combines and exploits dependencies among features of the blurred image. In order to develop such function, first, a set of feature vectors is formed by considering a small neighborhood around each pixel. At second stage, the estimator is trained and developed through GP process that automatically selects and combines the useful feature information under a fitness criterion. The developed function is then applied to estimate the image pixel intensity of the degraded image. The performance of developed function is estimated using various degraded image sequences. Our comparative analysis highlights the effectiveness of the proposed filter.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.672-684
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• 2020

Restoring a low resolution and motion blurred light field has become essential due to the growing works on parallax-based image processing. These tasks are known as light-field enhancement process. Unfortunately, only a few state-of-the-art methods are introduced to solve the multiple problems jointly. In this work, we design a framework that jointly solves light field spatial super-resolution and motion deblurring tasks. Particularly, we generate a straight-forward neural network that is trained under low-resolution and 6-degree-of-freedom (6-DOF) motion-blurred light field dataset. Furthermore, we propose the strategy of local region optimization on the adversarial network to boost the performance. We evaluate our method through both quantitative and qualitative measurements and exhibit superior performance compared to the state-of-the-art methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.96-104
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• 2009

In this paper, we propose a no-reference objective Quality assessment metrics of image. The blockiness and blurring of edge areas which are sensitive to the human visual system are modeled as step functions. Blocking and blur metrics are obtained by estimating local visibility of blockiness and edge width, For the blocking metric, horizontal and vertical blocking lines are first determined by accumulating weighted differences of adjacent pixels and then the local visibility of blockiness at the intersection of blocking lines is obtained from the total difference of amplitudes of the 2-D step function which is modelled as a blocking region. The blurred input image is first re-blurred by a Gaussian blur kernel and an edge mask image is generated. In edge blocks, the local edge width is calculated from four directional projections (horizontal, vertical and two diagonal directions) using local extrema positions. In addition, the kurtosis and SSIM are used to compute the blur metric. The final no-reference objective metric is computed after those values are combined using an appropriate function. Experimental results show that the proposed objective metrics are highly correlated to the subjective data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.71-72
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• 2019

본 논문에서는 계층구조 합성곱 신경망 기반의 고해상도 동영상 프레임 고속 보간 방법을 제안한다. 기존의 고해상도 동영상 프레임 보간 방법은 시간 해상도와 공간 해상도를 분리하여 보간 하기 때문에, 예측된 보간 프레임이 블러(blur) 열화를 갖는 문제를 보인다. 제안하는 방법에서는 이러한 문제를 해결하기 위하여 계층구조 합성곱 신경망 기반의 보간 방법을 이용한다. 제안하는 계층구조 합성곱 신경망은 우선 저해상도의 광학 흐름 추정지도를 생성하고 이를 고해상도로 복원하여 프레임 보간을 수행한다. 이때, 저해상도 광학 흐름 지도를 추정할 때 사용된 특징 정보들을 활용하여 고품질의 고해상도 광학 흐름 지도를 추정한다. 실험을 통하여 제안하는 방법이 고해상도 프레임을 고속으로 보간하며, 동시에 블러 열화에 대한 성능 향상을 가짐을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.179-181
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• 2022

동적 비전 센서(Dynamic Vision Sensor)라고도 알려진 이벤트 카메라는 생체에서 영감을 받은 새로운 시각 센서이다. 고정된 속도로 이미지를 생성하는 기존 카메라와 달리 이벤트 기반 카메라의 픽셀은 독립적이고 비동기적으로 작동한다. 기존 프레임 기반 카메라보다 이벤트 기반 카메라가 움직임을 포착하는데 더 적합하며 모션 블러(Motion Blur)가 없고 시간 해상도가 높다는 이점을 통해 고속카메라로 활용할 수 있다. 본 논문은 이벤트 카메라의 높은 시간 해상도와 동적 범위, 낮은 지연시간, 전력 소비량의 이점을 활용하여 움직이는 물체를 모션 블러 없이 포착하는 이벤트 기반 물체 추적 시스템을 제안한다. 실험을 통해 전체 영상을 포착하는 기존 프레임 기반 카메라에 비해 밝기 변화에 따른 동적 변화만을 추적하는 이벤트 기반 카메라는 모션 블러가 없다는 점을 검증하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.93-95
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• 2023

본 논문에서는 장편의 드라마나 영화에서 스토리 기반의 축약된 요약본을 자동으로 제작하기 위해 미디엄 숏(medium shot) 크기의 숏(shot)들을 추출하기 위한 방법을 고려한다. 미디엄 숏 정도의 크기는 보통 인물에 중심을 둔 숏들로 인물들 간의 관계에서 특히 대사나 표정으로 내용을 전달하기 위한 목적으로 적극 권장된다. 비디오 검색을 위한 인덱싱에서 신(scene) 전환 검출 및 숏 경계 검출, 그리고 이미지에서 심도와 초점기반의 화질 및 피사체 추출 등을 위해 전통적인 신호/영상처리 기법의 활용에서부터 최근의 기계학습 접목 등 다양한 연구들이 진행되고 있다. 영상문법에 근거하여 편집된 영상물에서 미디엄 숏 정도 크기의 숏들을 추출하여 배열한다면 어느 정도 원본 내용을 충실히 전달할 수 있는 축약된 요약본을 제작할 수 있다는 가정하에 해당 샷들을 블러(blur) 기반으로 검출하기 위해 이와 관련된 키워드들을 기반으로 기존 연구들을 살펴보고 적용 방법을 모색한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.205-215
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• 2013

In digital imaging system, Bayer pattern is widely used and the observed image is degraded by optical blur during image acquisition process. Generally, demosaicing and deblurring process are separately performed in order to convert a blurred Bayer image to a high resolution color image. However, the demosaicing process often generates visible artifacts such as zipper effect and Moire artifacts when performing interpolation across edge direction in Bayer pattern image. These artifacts are emphasized by the deblurring process. In order to solve this problem, this paper proposes a deblurring algorithm combined with edge directional color demosaicing method. The proposed method is consisted of interpolation step and region classification step. Interpolation and deblurring are simultaneously performed according to horizontal and vertical directions, respectively during the interpolation step. In the region classification step, characteristics of local regions are determined at each pixel position and the directionally obtained values are region adaptively fused. Also, the proposed method uses blur model based on wave optics and deblurring filter is calculated by using estimated characteristics of local regions. The simulation results show that the proposed deblurring algorithm prevents the boosting of artifacts and outperforms conventional approaches in both objective and subjective terms.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.11-20
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• 2016

This paper introduces an effective method for generating 3D stereoscopic images that gives immersive 3D experiences to viewers using mobile-based binocular HMDs. Most of previous AR systems with monocular cameras have a common limitation that the same real-world images are provided to the viewer's eyes without parallax. In this paper, based on the assumption that viewers focus on the marker in the scenario of marker based AR, we recovery the binocular disparity about a camera image and a virtual object using the pose information of the marker. The basic idea is to generate the binocular disparity for real-world images and a virtual object, where the images are placed on the 2D plane in 3D defined by the pose information of the marker. For non-marker areas in the images, we apply blur effects to reduce the visual discomfort by decreasing their sharpness. Our user studies show that the proposed method for 3D stereoscopic image provides high depth feeling to viewers compared to the previous binocular AR systems. The results show that our system provides high depth feelings, high sense of reality, and visual comfort, compared to the previous binocular AR systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.127-136
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• 2013

This paper proposes a video deblurring algorithm which maintains uniform sharpness between frames. Unlike the previous algorithms using fixed parameters, the proposed algorithm keeps uniform sharpness by adjusting parameters for each frame. First, we estimate the initial blur kernel and perform deconvolution, then measure the sharpness of the deblurred image. In order to maintain uniform sharpness, we adjust the regularization parameter and kernel according to the examined sharpness, and perform deconvolution again. The experimental results show that the proposed algorithm achieves outstanding deblurring results while providing consistent sharpness.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.768-779
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• 2018

In this paper, we propose a novel video quality function for video processing based on MSSSIM to select an appropriate video processing filter and to accommodate multiple processing filters to each pixel block in a picture frame by a mathematical selection law so as to maintain video quality and to reduce the bitrate of compressed video. In viewpoint of video compression, since the properties of video quality and bitrate is different for each picture of video frames and for each areas in the same frame, it is difficult for the video filter with single property to satisfy the object of increasing video quality and decreasing bitrate. Consequently, to maintain the subjective video quality in spite of decreasing bitrate, we propose the methodology about the MSSSIM as the measure of subjective video quality, the KL-Divergence as the measure of bitrate, and the combination method of those two measurements. Moreover, using the proposed combinatorial measurement, when we use the multiple image filters with mutually different properties as a pre-processing filter for video, we can verify that it is possible to compress video with maintaining the video quality under decreasing the bitrate, as possible.