• Title/Summary/Keyword: Deblurring

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PARALLEL PERFORMANCE OF THE Gℓ-PCG METHOD FOR IMAGE DEBLURRING PROBLEMS

  • YUN, JAE HEON
    • Journal of applied mathematics & informatics
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    • v.36 no.3_4
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    • pp.317-330
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    • 2018
  • We first provide how to apply the global preconditioned conjugate gradient ($G{\ell}-PCG$) method with Kronecker product preconditioners to image deblurring problems with nearly separable point spread functions. We next provide a coarse-grained parallel image deblurring algorithm using the $G{\ell}-PCG$. Lastly, we provide numerical experiments for image deblurring problems to evaluate the effectiveness of the $G{\ell}-PCG$ with Kronecker product preconditioner by comparing its performance with those of the $G{\ell}-CG$, CGLS and preconditioned CGLS (PCGLS) methods.

IMAGE DEBLURRING USING GLOBAL PCG METHOD WITH KRONECKER PRODUCT PRECONDITIONER

  • KIM, KYOUM SUN;YUN, JAE HEON
    • Journal of applied mathematics & informatics
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    • v.36 no.5_6
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    • pp.531-540
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    • 2018
  • We first show how to construct the linear operator equations corresponding to Tikhonov regularization problems for solving image deblurring problems with nearly separable point spread functions. We next propose a Kronecker product preconditioner which is suitable for the global PCG method. Lastly, we provide numerical experiments of the global PCG method with the Kronecker product preconditioner for several image deblurring problems to evaluate its effectiveness.

Robust Least Squares Motion Deblurring Using Inertial Sensor for Strapdown Image IR Sensors (스트랩다운 적외선 영상센서를 위한 관성센서 기반 강인최소자승 움직임 훼손영상 복원 기법)

  • Kim, Ki-Seung;Ra, Sung-Woong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.314-320
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    • 2012
  • This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

An Adaptive Iterative Algorithm for Motion Deblurring Based on Salient Intensity Prior

  • Yu, Hancheng;Wang, Wenkai;Fan, Wenshi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.855-870
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    • 2019
  • In this paper, an adaptive iterative algorithm is proposed for motion deblurring by using the salient intensity prior. Based on the observation that the salient intensity of the clear image is sparse, and the salient intensity of the blurred image is less sparse during the image blurring process. The salient intensity prior is proposed to enforce the sparsity of the distribution of the saliency in the latent image, which guides the blind deblurring in various scenarios. Furthermore, an adaptive iteration strategy is proposed to adjust the number of iterations by evaluating the performance of the latent image and the similarity of the estimated blur kernel. The negative influence of overabundant iterations in each scale is effectively restrained in this way. Experiments on publicly available image deblurring datasets demonstrate that the proposed algorithm achieves state-of-the-art deblurring results with small computational costs.

Image Deblurring Using Vibration Information From 3-axis Accelerometer (3축 가속도 센서의 흔들림 정보를 이용한 영상의 Deblurring)

  • Park, Sang-Yong;Park, Eun-Soo;Kim, Hak-Il
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.3
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    • pp.1-11
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    • 2008
  • This paper proposes a real-time method using a 3-axis accelerometer to enhance blurred images taken from a camera loaded in mobile devices. Blurring phenomenon is a smoothing effect occurring in photo images. Algorithms to cope with blurring phenomenon is essential since small-size mobile devices tremble severely by even a tiny hand-shaking of a user. In this paper, accurate sensing characteristics of the 3-axis accelerometer is acquired by applying the sensor in pendulum motion and the blurring phenomenon is modeled as a uniform distribution and Gaussian distribution. Also, non-Gaussian distributed model is observed in the experiment of real blurring phenomenon and a particular deblurring function is designed by reversing the model. It has been demonstrated that the application of trembling information to the deblurring function adequately removes the blurring phenomenon.

TWO DIMENSIONAL VERSION OF LEAST SQUARES METHOD FOR DEBLURRING PROBLEMS

  • Kwon, SunJoo;Oh, SeYoung
    • Journal of the Chungcheong Mathematical Society
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    • v.24 no.4
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    • pp.895-903
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    • 2011
  • A two dimensional version of LSQR iterative algorithm which takes advantages of working solely with the 2-dimensional arrays is developed and applied to the image deblurring problem. The efficiency of the method comparing to the Fourier-based LSQR method and the 2-D version CGLS algorithm methods proposed by Hanson ([4]) is analyzed.

A Logistic Regression for Random Noise Removal in Image Deblurring (영상 디블러링에서의 임의 잡음 제거를 위한 로지스틱 회귀)

  • Lee, Nam-Yong
    • Journal of Korea Multimedia Society
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    • v.20 no.10
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    • pp.1671-1677
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    • 2017
  • In this paper, we propose a machine learning method for random noise removal in image deblurring. The proposed method uses a logistic regression to select reliable data to use them, and, at the same time, to exclude data, which seem to be corrupted by random noise, in the deblurring process. The proposed method uses commonly available images as training data. Simulation results show an improved performance of the proposed method, as compared with the median filtering based reliable data selection method.

A Deblurring Algorithm Combined with Edge Directional Color Demosaicing for Reducing Interpolation Artifacts (컬러 보간 에러 감소를 위한 에지 방향성 컬러 보간 방법과 결합된 디블러링 알고리즘)

  • Yoo, Du Sic;Song, Ki Sun;Kang, Moon Gi
    • 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.

A DFT Deblurring Algorithm of Blind Blur Image (무정보 blur 이미지 복구를 위한 DFT 변환)

  • Moon, Kyung-Il;Kim, Chul
    • Journal of The Korean Association of Information Education
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    • v.15 no.3
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    • pp.517-524
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    • 2011
  • This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.

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A Video Deblurring Algorithm based on Sharpness Metric for Uniform Sharpness between Frames (프레임 간 선명도 균일화를 위한 선명도 메트릭 기반의 동영상 디블러링 알고리즘)

  • Lee, Byung-Ju;Lee, Dong-Bok;Song, Byung Cheol
    • 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.