共查询到19条相似文献,搜索用时 140 毫秒
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利用地基光学望远镜观测空间目标时,大气湍流是影响成像质量的主要因素。由于大气湍流引起成像波面的畸变,导致望远镜所获得的图像模糊。为了从模糊图像中复原出目标的原始图像,提出了一种基于大气相干长度的湍流点扩展函数估计方法,进行了理论推导,并利用Sobel方法对迭代相同次数后的盲卷积复原图进行像质评价,找出像质评价结果峰值处对应的大气相干长度;再将此值代入点扩展函数的估计公式中,得到点扩展函数更加准确的估计;然后利用此点扩展函数对湍流模糊图像进行盲卷积图像复原,最后得到目标的复原图像。从多种像质评价结果来看,该方法无需测量大气相干长度,且复原效果较理想。 相似文献
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一种混合模糊含噪图像的参数辨识方法 总被引:1,自引:0,他引:1
在航空摄影、景象匹配导航等领域,由光学相机采集的图像往往同时存在着运动模糊和散焦模糊。成像中的噪声进一步加大了混合模糊图像点扩展函数的参数辨识难度。提出了一种双谱混合模糊含噪图像的点扩展函数参数辨识方法。首先计算出经混合模糊后的标准测试图像所对应的运动和散焦模糊的双谱,然后通过曲线拟合出双谱中各自的统计特性与运动模糊尺度或散焦半径之间的函数关系,由此训练出的BP神经网络可以完成对其它含有噪声的混合模糊图像点扩展函数的参数辨识。实验结果表明,该方法适用于含有噪声的一定模糊参数范围内的混合模糊图像。在信噪比为25dB的情况下,辨别出的模糊参数偏差不超过0.5个像素。 相似文献
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基于频谱分析的匀速运动模糊图像模糊方向识别 总被引:5,自引:0,他引:5
点扩展函数的设置是图像复原中的关键问题,对于匀速直线运动模糊图像,运动方向和模糊长度决定了点扩展函数。根据运动模糊图像和原始图像在频谱上存在的对应关系,即运动模糊图像频谱存在着对应于传递函数零点的暗条纹,提出对运动模糊图像,通过二维傅里叶变换、二值化以及Radon变换检测运动模糊图像频谱图上暗条纹的方向和位置,来实现运动方向测量的方法。用该方法对模糊图像进行检测,模糊方向的识别精度小于1°。实验证明该方法可以实现平面内任意方向运动的测量。 相似文献
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介绍了超分辨率复原方法的概念和理论基础;重点总结了常用的超分辨率复原方法,并对相关的理论依据、优缺点和适用范围进行了详尽分析;对超分辨率复原方法的未来发展进行了展望.超分辨率复原方法分为频域法和空域法.频域复原法原理简单清楚,计算方便,但是所建立的运动模型都是平移模型,不具有一般性,同时难以利用正则化约束,因而导致难以使用图像的先验信息进行超分辨率复原.空域复原法可以很方便地建立复杂的运动模型,同时考虑了几乎所有的图像降质因素,例如噪声、降采样、由非零孔径时间造成的模糊、光学系统降质和运动模糊等,还可以加入更完善的先验知识,相比于频域复原法,空域超分辨率复原模型更符合实际的图像退化过程,是目前应用最广泛的一类超分辨率复原方法. 相似文献
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为了去除X射线工业CT图像中的杯状伪影,提高CT图像的识别能力和量化分析精度,提出一种基于分度投影和权函数的射束硬化校正方法。首先分析得出杯状伪影主要是由X射线连续谱穿过被测物体过程中出现的射束硬化所导致。然后扫描阶梯模型,采集不同厚度下的投影数据并求出线衰减系数,通过拟合曲线,得到硬化模型函数和权函数校正模型函数,并确定权函数。接着,扫描被测圆柱形工件,采集不同分度下的投影数据。最后,针对每一个分度投影数据,采用权函数与当前分度投影数据乘积的方法进行硬化校正。对含有杯状伪影的实际CT图像进行了校正实验,结果表明,与多项式拟合法相比,该方法校正后的灰度图像没有放大噪声,且信噪比提高3.29%,有效地消除了杯状伪影,同时较好地保留了图像边界细节。 相似文献
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Jian-Feng Cai Hui Ji Chaoqiang Liu Zuowei Shen 《Journal of computational physics》2009,228(14):5057-5071
Recovery of degraded images due to motion blurring is a challenging problem in digital imaging. Most existing techniques on blind deblurring are not capable of removing complex motion blurring from the blurred images of complex structures. One promising approach is to recover the clear image using multiple images captured for the scene. However, in practice it is observed that such a multi-frame approach can recover a high-quality clear image of the scene only after multiple blurred image frames are accurately aligned during pre-processing, which is a very challenging task even with user interactions. In this paper, by exploring the sparsity of the motion blur kernel and the clear image under certain domains, we propose an alternative iteration approach to simultaneously identify the blur kernels of given blurred images and restore a clear image. Our proposed approach is not only robust to image formation noises, but is also robust to the alignment errors among multiple images. A modified version of linearized Bregman iteration is then developed to efficiently solve the resulting minimization problem. Experiments show that our proposed algorithm is capable of accurately estimating the blur kernels of complex camera motions with minimal requirements on the accuracy of image alignment. As a result, our method is capable of automatically recovering a high-quality clear image from multiple blurred images. 相似文献
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倒谱在混合模糊图像分析中的应用 总被引:2,自引:1,他引:2
降晰参数识别在模糊图像恢复过程中具有很重要的作用。在各种图像捕获系统中,有两种形式的图像模糊比较常见:一种是由光学系统散焦造成的散焦模糊;另一种是物体与照相机之间的相对运动造成的运动模糊。相对单个模糊模型的参数识别来说,混合了散焦和运动模糊的图像,其模糊参数的识别要复杂得多。许多识别方法一般都是用来分析某一特定的模糊模型的,而对两种模糊混合在一起的情况来说是很难区分的。提出了一种倒谱分析方法,在倒谱域同时对这两种模型参数进行识别。在分析过程中,仍需要利用这两种模糊模型在频域的特征,首先应用一些调整性的变换,然后再转换到倒谱域,以便更准确地评估模糊参数。 相似文献
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In the problem of blind image deconvolution, estimation of blurring kernel is the first and foremost important step. Quality of restored image highly depends upon the accuracy of this estimation. In this paper we propose a modified cepstrum domain approach combined with bit-plane slicing method to estimate uniform motion blur parameters, which improves the accuracy without any manual intervention. A single motion blurred image under spatial invariance condition is considered. It is noted that the fourth bit plane of the modified cepstrum carries an important cue for estimating the blur direction. With the exploration of this bit plane no other post processing is required to estimate blur direction. The experimental evaluation is carried out on both real-blurred photographs and synthetically blurred standard test images such as Berkeley segmentation dataset and USC-SIPI texture image database. The experimental results show that the proposed method is capable of estimating blur parameters more accurately than the existing methods. 相似文献
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Motion blur is caused by camera shakes or object motions during exposure when the shutter speed is relatively slow. As for the object motion blur, the degradation of a CCD image is often characterized by space-variant motion blurs, since objects are often moving in different directions at different speeds. But most image restorations for space-variant motion blurs are addressed only for progressive scan CCD images. To address the space-variant image restorations for interlaced scan images, we propose a novel image restoration scheme. First, one interlaced scan image frame is required, which is divided into the odd field and the even field images. These two field images are further segmented into rectangular blocks. The motion vectors are computed in these rectangular blocks using an efficient block matching algorithm. Second, image restoration is performed in these rectangular blocks using a constrained least square algorithm in the odd or even field image, which can both preserve edge structures and remove noises. Our novel scheme is illustrated by restoring a space-variant blurred moving boat image and a synthetic blurred image. 相似文献
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A method of numerically calculating the optical transfer function appropriate to any type of image motion and vibration, including random, has been recently developed. This method has been verified experimentally with real vibrations, and the close agreement justifies implementation in image restoration from blur deriving from any type of image motion, including random displacement. Here, image restorations of actual physically degraded images are presented, based on a constrained least squares improvement of the original Wiener filter. Even for extreme vibrations where the blur extent is much larger than the blurred detail, restoration is quite complete. The key to restoration is the determination of the optical transfer function unique to the particular image motion and vibration causing the blur. Results are also presented for low vibration frequency motion of random blur extent, as well as for high vibration frequencies. 相似文献
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针对现有模糊方向鉴别算法检测小尺度运动模糊图像存在误差的问题,基于运动模糊图像二次傅里叶变换后的频谱特性,分析了其误差成因,并提出了一种适用于小尺度运动模糊图像模糊方向鉴别的新算法。首先对小尺度运动模糊图像的频谱进行细化,通过中值滤波对细化图像去噪,避开了频谱噪声带来的估计误差问题;其次,选取灰度中值作为阈值进行二值化,同时去除二值图像的中心十字亮线和中心亮斑,使模糊方向特征更加明显;然后用投影变换计算出亮条纹方向得到小尺度模糊图像的方向估计。最后通过仿真验证了算法在运动模糊尺度为3~10像素的小尺度情况下的实效性。实验结果表明,该算法相比其他同类算法对于小尺度运动模糊图像的模糊方向估计精度更高。 相似文献