Motion Blur Identification Using Image derivative

Norouzi, Narges; Moghaddam, Mohsen Ebrahimi

doi:10.1109/isspit.2008.4775692

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…N. Norouzi et al, put forward a method of derivative, which can detect image blurred length. However, the error is very serious under the condition of noise [5].…”

Section: 、Introductionmentioning

confidence: 99%

“…N. Norouzi et al, put forward a method of derivative, which can detect image blurred length. However, the error is very serious under the condition of noise [5].For the image blur problem caused by the optical camera, this paper proposes the NSC algorithm, which mainly includes image denoising pretreatment based on the NSCT filter and fuzzy regression model construction based on the spectrum characteristics. …”

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confidence: 99%

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Small Celestial Body Image Restoration Based on Spectrum Characteristics

Tao¹,

Kang²,

Liu³

2016

Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

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Abstract.To remove the blur of the image from optical navigation camera, a image restoration method based on spectrum characteristics is proposed. In this method, image denoising pretrea tment is first implemented by the NSCT filter. Then, to obtain the minimum amplitude distanc e, the paper optimizes the image spectrum characteristic by using the simulated annealing al gorithm. And then the minimum amplitude distance can be obtained. There the point spread fu nction is established. Finally, blurred image is recovered by the Lucy -Richardson algorithm.T he recovery quality is evaluated by the Laplace gradient and the average gray level gradient. T he simulation results demonstrate that the proposed method in the paper improves the quality of the restored small celestial body image, and the visual effect is also very ideal. 1、IntroductionIn the process of the deep space exploration, the imaging system of the optical optical camera is vulnerable to the flight speed and the cosmic rays [1], which cause the image fuzzy and inconvenience for image information analysis. Thus, how to restore fuzzy image is a difficulty of image information process in the deep space exploration.The image restoration of small celestial body mainly consists of the image denoising pretreatment and the image degradation process estimation. At present, there are many relevant researches about the image denoising pretreatment. For instance, the median filtering algorithm has a very good effect on the salt and pepper noise, but it is not ideal to other interference noises [1]. The bilateral filter algorithm can eliminate the image noise, while it cannot make image detail intact [2]. The degradation function is important to determine the degradation process. The degradation function of the optical camera is the point-spread function (PSF) [3]. For the point-spread function, a lot of researches have been done by domestic and foreign scholars. X. H. Wang et al, considered that the distance between the spectrum center and the adjacent black belt is inversely proportional to the blurred length [4]. But it is only a project of the degradation function estimation, and does not have a specific quantitative formula. N. Norouzi et al., put forward a method of derivative, which can detect image blurred length. However, the error is very serious under the condition of noise [5].For the image blur problem caused by the optical camera, this paper proposes the NSC algorithm, which mainly includes image denoising pretreatment based on the NSCT filter and fuzzy regression model construction based on the spectrum characteristics. 2、NSC algorithm 2.1、NSCT filterThe non -subsampled contourlet (NSCT) filter is composed of the non -subsampled pyramid (NSP) [6] and the non -subsampled direction filter group (NSDFB) [7]. The redundant representation is adopted by the NSCT filter, which can effectively capture image characteristics, and distinguish between noise and image edge [9]. Thus, it has a very good denoising effect.The non-subsampled pyramid (NSP) is used for ...

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“…N. Norouzi et al, put forward a method of derivative, which can detect image blurred length. However, the error is very serious under the condition of noise [5].…”

Section: 、Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Small Celestial Body Image Restoration Based on Spectrum Characteristics

Tao¹,

Kang²,

Liu³

2016

Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

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“…In space domain, Sun et al [1] identify motion parameters from Radon transform of image gradients, and estimate the motion blur parameters by noisy image gradients. Norouzi et al [2] use image derivative to identify blur. Generally, estimate parameters in space domain need large amount of calculation.…”

Section: Introductionmentioning

confidence: 99%

Blind Estimation of Blur Parameters by 2D-DFT on Polar Coordinate System Presented on Rectangular Grids

Zhang

Wang

2013

2013 Seventh International Conference on Image and Graphics

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We propose a blind identification method to estimate blur parameters of a noisy image. The noisy image is blurred and degraded due to linear motion and defocusing. In a polar coordinate system, 2D-Fourier transform of a degraded image is derived. The blur parameters are blindly estimated from the magnitude of the spectrum in the polar system, and represented on a rectangular grid. In this grid representation, vertical and horizontal projections are calculated to estimate the length and the orientation of uniform linear motion blur. As for defocus blur, only horizontal projection is used to get a blurring radius. Experimental results show that the method is accurate and computationally efficient. The estimated results are close to true values, even when the image is heavily contaminated by additive salt and pepper noise.

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