共查询到20条相似文献,搜索用时 31 毫秒
1.
Changsoo Je Hyeon Sang Jeon Chang-Hwan Son Hyung-Min Park 《Signal Processing: Image Communication》2013,28(7):792-808
Obtaining a good-quality image requires exposure to light for an appropriate amount of time. If there is camera or object motion during the exposure time, the image is blurred. To remove the blur, some recent image deblurring methods effectively estimate a point spread function (PSF) by acquiring a noisy image additionally, and restore a clear latent image with the PSF. Since the groundtruth PSF varies with the location, a blockwise approach for PSF estimation has been proposed. However, the block to estimate a PSF is a straightly demarcated rectangle which is generally different from the shape of an actual region where the PSF can be properly assumed constant. We utilize the fact that a PSF is substantially related to the local disparity between two views. This paper presents a disparity-based method of space-variant image deblurring which employs disparity information in image segmentation, and estimates a PSF, and restores a latent image for each region. The segmentation method firstly over-segments a blurred image into sufficiently many regions based on color, and then merges adjacent regions with similar disparities. Experimental results show the effectiveness of the proposed method. 相似文献
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Blind deconvolution, which comprises simultaneous blur and image estimations, is a strongly ill-posed problem. It is by now well known that if multiple images of the same scene are acquired, this multichannel (MC) blind deconvolution problem is better posed and allows blur estimation directly from the degraded images. We improve the MC idea by adding robustness to noise and stability in the case of large blurs or if the blur size is vastly overestimated. We formulate blind deconvolution as an l(1) -regularized optimization problem and seek a solution by alternately optimizing with respect to the image and with respect to blurs. Each optimization step is converted to a constrained problem by variable splitting and then is addressed with an augmented Lagrangian method, which permits simple and fast implementation in the Fourier domain. The rapid convergence of the proposed method is illustrated on synthetically blurred data. Applicability is also demonstrated on the deconvolution of real photos taken by a digital camera. 相似文献
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基于超分辨力图像复原算法的模糊系统辨识 总被引:7,自引:4,他引:3
由于利用已有的知识和经验得到的点扩散函数(PSF)估计值与真实值之间的偏差会直接影响图像复原质量。为准确地估计PSF,使其向真实的点扩散函数类型和参量逼近,采用超分辨力图像复原MPML算法同几种常用的数字图像去模糊处理进行比较分析,通过实验表明:MPML算法具有其他几种算法的优势,同时减少了对原有信息的丢失;在此基础的同时,按照点扩散函数的分类,分析了点扩散函数的不同估计值及其对图像复原的影响,提出基于超分辨力图像复原算法的图像细节评价参数D,保证了复原图像主观效果和评价参数的一致性。对于模糊图像的系统辨识及其图像复原问题的解决具有实际意义,但对于附加较大噪声条件下的图像复原仍是需要进一步研究的问题。 相似文献
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This paper proposes a blind image deconvolution method which consists of two sequential phases, i.e., blur kernel estimation and image restoration. In the first phase, we adopt the L0-norm of image gradients and total variation (TV) to regularize the latent image and blur kernel, respectively. Then we design an alternating optimization algorithm which jointly incorporates the estimation of intermediately restored image, blur kernel and regularization parameters into account. In the second phase, we propose to take the mixture of L0-norm of image gradients and TV to regularize the latent image, and design an efficient non-blind deconvolution algorithm to achieve the restored image. Experimental results on both a benchmark image dataset and real-world blurred images show that the proposed method can effectively restore image details while suppress noise and ringing artifacts, the result is of high quality which is competitive with some state of the art methods. 相似文献
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任意方向匀速直线运动模糊的点扩展函数估计 总被引:3,自引:0,他引:3
在运动图像复原中,建立图像退化模型的关键是找到准确的点扩展函数(PSF)。提出了一种基于单幅图像的、改进的任意方向匀速直线运动模糊PSF的估计方法。利用基于图像频谱亮线灰度特征的方向鉴别方法鉴别模糊图像的模糊方向,利用微分自相关的方法对模糊图像的模糊尺寸进行计算,通过计算模糊图像沿二维直线运动方向不同距离的重叠度,来计算得到相应的PSF。通过开展仿真分析和成像实验,演示了PSF估计和图像复原过程。通过采用图像质量评价函数,将图像复原结果与现有算法进行对比,验证了所提出方法的有效性。 相似文献
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当目标在多视角观测成像系统中有相对运动时,所获取的多观测点图像是模糊的且各视角图像的模糊是不一样的,模糊核长度和方向都不同。针对这一问题,提出了多视角观测图像的三维去模糊方法。现有的图像去模糊方法主要是对单视角观测图像进行二维去模糊的,没有考虑目标多视角观测图像的模糊核之间的对应关系。文中从三维空间到二维观测面的映射关系出发,建立多视角观测图像的模糊路径之间的对应关系。先采用单观测图像去模糊的方法获取两视角观测图像的模糊核,并对模糊核进行精确化处理,得到单像素点宽的模糊核路径。再通过多视角观测图像模糊核路径之间的对应关系,估计其它观测图像的模糊核路径。最后,对多视角观测图像进行统一去模糊,并对去模糊后的多视角观测图像进行三维重建。实验结果表明,文中方法能较好地去除目标多视角观测图像的三维模糊,提高了目标的三维重建质量。 相似文献
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对单一图像进行运动模糊复原,存在模糊点扩散函数(PSF)难以估计以及图像反卷积的病态性问题。利用多个PSF具有联合可逆性的特点,针对运动目标观测,提出采用参数相同的多个成像设备共同对同一视场进行拍摄,来获取背景相同、曝光时间不同、目标模糊程度不同的观测图像;然后利用同一设备获取的序列图像进行目标的模糊PSF估计;并根据目标背景的运动模糊叠加特征,分别从观测图像中提取出完整的模糊目标图像;最后,对这些具有不同PSF的同一目标图像进行空间域迭代复原算式的联立求解。实验表明:该方法设计的目标获取装置对硬件条件要求较低,获取的图像更便于采用多点扩散函数联合进行图像复原,复原效果良好。 相似文献
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Motion blur due to camera shake during exposure is one of the most common reasons of image degradation,which usually reduces the quality of photographs seriously.Based on the statistical properties of the natural image's gradient and the blur kernel,a blind deconvolution algorithm is proposed to restore the motion-blurred image caused by camera shake,adopting the variational Bayesian estimation theory.In addition,the ring effect is one problem that is not avoided in the process of image deconvolution,and usually makes the visual effect of the restored image badly.So a dering method is put forward based on the sub-region detection and fuzzy filter.Tested on the real blurred photographs,the experimental results show that the proposed algorithm of blind image deconvolution can remove the camera-shake motion blur from the degraded image effectively,and can eliminate the ring effect better,while preserve the edges and details of the image well. 相似文献
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The blur direction and extent of motion-blurred image, which is degraded by the relative motion between the camera and object scene, are needed in the methods of image restoration, such as blind deconvolution. The recently developed identification method is based on integer-order derivative, which can directly extract the blur angle and extent from blurred image itself. However, this method is sensitive to noise. As an extension to the fractional-order derivative, a noncausal fractional-order directional derivative operator is derived. Based on this new operator, a novel method identifying blur parameters is developed in this work. The performance comparison between the fractional-order and integer-order methods are also presented, which demonstrate that the former provides better immunity to noise and capacity to identify the motion-blur direction and extent. 相似文献
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Blind image restoration by anisotropic regularization 总被引:16,自引:0,他引:16
This paper presents anisotropic regularization techniques to exploit the piecewise smoothness of the image and the point spread function (PSF) in order to mitigate the severe lack of information encountered in blind restoration of shift-invariantly and shift-variantly blurred images. The new techniques, which are derived from anisotropic diffusion, adapt both the degree and direction of regularization to the spatial activities and orientations of the image and the PSF. This matches the piecewise smoothness of the image and the PSF which may be characterized by sharp transitions in magnitude and by the anisotropic nature of these transitions. For shift-variantly blurred images whose underlying PSFs may differ from one pixel to another, we parameterize the PSF and then apply the anisotropic regularization techniques. This is demonstrated for linear motion blur and out-of-focus blur. Alternating minimization is used to reduce the computational load and algorithmic complexity. 相似文献
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相位相关技术实现离焦模糊图像运动估计 总被引:2,自引:2,他引:0
为解决离焦模糊图像的运动参数估计问题,介绍一种采用相位相关分析的图像配准技术。该方法利用傅里叶变换的平移特性,对产生平移的目标图像进行傅里叶变换,计算位移图像之间归一化互功率谱,其傅里叶逆变换对应二维脉冲函数,通过计算脉冲函数峰值坐标获取位移图像之间的亚像元级位移量。结合相位相关配准原理和线性空间不变退化模型,给出离焦成像系统点扩散函数及其光学传递函数的数学描述,侧重讨论离焦模糊对相位相关配准结果的影响,证明图像经过离焦退化后,位移图像之间归一化的互功率谱具有不变性。动态运动模糊图像最大检测误差0.339像元,标准差0.19像元。该方法具有可行性和有效性,能够满足一般要求。 相似文献
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Recognition of blurred images by the method of moments 总被引:5,自引:0,他引:5
The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed. 相似文献
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根据运动模糊图像产生的原因及特点,文中阐述了在匀速直线运动下模糊图像退化的模型,介绍了维纳滤波复原图像的原理。由于在图像获取时模糊原因的不确定性,使得点扩散函数(PSF)具有不准确性,从而使模糊图像复原的效果不佳。针对点扩散函数的确定,利用方向微分法快速判断运动模糊方向,再利用一阶差分自相关的方法鉴定运动模糊图像的模糊尺度,从而确定点扩散函数。在确定K值时,采用K值自动估计算法。通过实验仿真表明,此方法对模糊图像复原效果良好。 相似文献
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Blur identification by the method of generalized cross-validation 总被引:10,自引:0,他引:10
The point spread function (PSF) of a blurred image is often unknown a priori; the blur must first be identified from the degraded image data before restoring the image. Generalized cross-validation (GCV) is introduced to address the blur identification problem. The GCV criterion identifies model parameters for the blur, the image, and the regularization parameter, providing all the information necessary to restore the image. Experiments are presented which show that GVC is capable of yielding good identification results. A comparison of the GCV criterion with maximum-likelihood (ML) estimation shows the GCV often outperforms ML in identifying the blur and image model parameters. 相似文献
16.
Wen Li Jun Zhang Qiong-hai Dai 《Journal of Visual Communication and Image Representation》2013,24(8):1394-1413
In light-limited situations, camera motion blur is one of the prime causes for poor image quality. Recovering the blur kernel and latent image from the blurred observation is an inherently ill-posed problem. In this paper, we introduce a hand-held multispectral camera to capture a pair of blurred image and Near-InfraRed (NIR) flash image simultaneously and analyze the correlation between the pair of images. To utilize the high-frequency details of the scene captured by the NIR-flash image, we exploit the NIR gradient constraint as a new type of image regularization, and integrate it into a Maximum-A-Posteriori (MAP) problem to iteratively perform the kernel estimation and image restoration. We demonstrate our method on the synthetic and real images with both spatially invariant and spatially varying blur. The experiments strongly support the effectiveness of our method to provide both accurate kernel estimation and superior latent image with more details and fewer ringing artifacts. 相似文献
17.
在基于匀速直线运动的运动模糊图像的复原中,点扩散函数(PSF)的两个参数(运动模糊角度和运动模糊尺度)的估计是研究的重点.为了能够准确地估计出PSF的模糊角度,提出了在一种新的改进倒频谱域中采用位平面分解提取和Radon变换相结合的方法.并在已知运动模糊角度的基础上再对模糊图像采用差分自相关处理,得到运动模糊尺度.将上述整个算法用Matlab进行仿真实验.实验结果表明:该算法在获取运动模糊参数的效率和准确度方面较现有文献的同类算法有所提高,得到的复原图像也更加清晰. 相似文献
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Blur identification by residual spectral matching 总被引:3,自引:0,他引:3
The estimation of the point spread function (PSF) for blur identification, often a necessary first step in the restoration of real images, method is presented. The PSF estimate is chosen from a collection of candidate PSFs, which may be constructed using a parametric model or from experimental measurements. The PSF estimate is selected to provide the best match between the restoration residual power spectrum and its expected value, derived under the assumption that the candidate PSF is equal to the true PSF. Several distance measures were studied to determine which one provides the best match. The a priori knowledge required is the noise variance and the original image spectrum. The estimation of these statistics is discussed, and the sensitivity of the method to the estimates is examined analytically and by simulations. The method successfully identified blurs in both synthetically and optically blurred images. 相似文献
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Non-blind image deconvolution is a process that obtains a sharp latent image from a blurred image when a point spread function (PSF) is known. However, ringing and noise amplification are inevitable artifacts in image deconvolution since perfect PSF estimation is impossible. The conventional regularization to reduce these artifacts cannot preserve image details in the deconvolved image when PSF estimation error is large, so strong regularization is needed. We propose a non-blind image deconvolution method which preserves image details, while suppressing ringing and noise artifacts by controlling regularization strength according to local characteristics of the image. In addition, the proposed method is performed fast with fast Fourier transforms so that it can be a practical solution to image deblurring problems. From experimental results, we have verified that the proposed method restored the sharp latent image with significantly reduced artifacts and it was performed fast compared to other non-blind image deconvolution methods. 相似文献