Image restoration for interlaced scan CCD image with space-variant motion blurs

When the speeds of objects in a scene exceed the temporal resolution of the camera shutter, motion blurs will occur. Since objects are often moving in different directions at different speeds, the degradation of a CCD image is often characterized by space-variant motion blurs. Image restoration algorithms for space-variant motion blurs are available for progressive scan CCD images, but not for interlaced scan images. To address the space-variant image restoration for interlaced scan images, a novel three-step image restoration scheme is proposed. Firstly, one interlaced scan image is divided into odd field and even field images. Secondly, these two field images are further segmented into rectangular blocks and the motion vectors are computed based on these rectangular blocks using an efficient block matching algorithm. Thirdly, image restoration is performed using a blind deconvolution algorithm in the odd or even field image. The final restored image is obtained by combining the restored odd and even field images. The scheme is illustrated by restoring a space-variant blurred moving vehicle image and a synthetic blurred image.     

Precise speed measurement using an interlaced scan image

In this paper, we propose a novel scheme for speed measurement of a moving object with translational motion. First, this scheme uses one interlaced scan CCD camera to obtain only one interlaced scan image of a moving object. The odd and even field images are extracted and resized. Second, image matte is applied in these two field images to extract the moving object’s silhouettes. The distance between two centroids in the two silhouettes is then computed. Finally, the object’s speed is calculated using the above distance and the camera imaging parameters. Simulation and real experiments prove that our scheme can fulfill the speed measurement for translational motion accurately.     

倒谱在混合模糊图像分析中的应用

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。     

Blind motion deblurring using multiple images

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.     

Restoration of images degraded by extreme mechanical vibrations

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.     

一种新的运动模糊图像超分辨力盲复原算法

研究了具有深度运动模糊效果的图像的复原算法.采用对运动模糊图像的傅里叶频谱进行Radon变换来估计运动模糊方向,在此方向上计算运动模糊图像的自相关来估计运动模糊长度,再以运动模糊方向和运动模糊长度为参量结合超分辨力图像复原处理算法对比较严重的运动模糊图像进行复原.结果表明,该综合性算法能够较为精确地估算出运动模糊图像的模糊参量并取得较好的复原效果.     

基于频谱分析的匀速运动模糊图像模糊方向识别

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。     

Motion blur parameters estimation for image restoration

This paper deals with estimation of parameters for motion blurred images. The objectives are to estimate the length (L) and the blur angle (θ) of the given degraded image as accurately as possible so that the restoration performance can be optimised. Gabor filter is utilized to estimate the blur angle whereas a trained radial basis function neural network (RBFNN) estimates the blur length. Once these parameters are estimated the conventional restoration is performed. To validate the proposed scheme, simulation has been carried out on standard images as well as in real images subjected to different blur angles and lengths. The robustness of the scheme is also validated in noise situations of different strengths. In all situations, the results have been compared with standard schemes. It is in general observed that the proposed scheme outperforms its counterparts in terms of restoration parameters and visual quality.     

基于数字射线成像的运动降质图像的恢复

当利用X射线数字成像技术对在流水线上运动的工件进行检测时,图像采集系统与工件在曝光时间内发生相对运动,造成了采集到的图像运动模糊降质。通过对运动降质产生机理的理论分析,建立了图像降质的离散退化模型。提出了利用运动模糊降质点扩展函数频域特性加上投影均值最大法来测量模糊运动方向的方法。旋转运动模糊图像的幅度谱图像,利用整列投影值最小法提取运动模糊降质点扩展函数长度。利用维纳滤波法对模糊降质图像进行了恢复,取得了较好的效果。     

基于极坐标的相向运动图像模糊的递归模型

成像过程中,被摄像目标和摄像机之间的相向运动会造成图像的辐射状模糊,辐射状模糊将减小有效视场,影响成像质量.本文在扇形网格采样的基础上,利用状态空间模型模拟了退化过程,用递归方法解决了空变问题,并利用对状态空间系统求逆的方法对退化图像进行了复原.计算机模拟显示,算法简单,复原图像清晰,取得了较满意的结果.     

A real-time,full-field,and low-cost velocity sensing approach for linear motion using fringe projection techniques

A velocity sensing approach using the fringe projection technique is presented. The moving object is projected with a sinusoidal fringe pattern. A CCD camera located at a different view angle observes the projected fringes on the dynamic object. The long exposure time of the CCD camera makes the fringes blurred by linear motion. The blurred fringes provide additional information to describe the depth displacement, and therefore the velocity vector can be identified. There is no need to take multiple-shot measurements to address the change in 3D positions at a sequence of time. Only one-shot measurement is required. Consequently, there is no need to perform image registration. The full-field approach also makes it possible to simultaneously inspect several objects.     

A novel modified cepstral based technique for blind estimation of motion blur

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.     

运动与离焦模糊图像的复原

在运动和离焦所引起的图像模糊的情况中,本文提出了一种新的基于霍夫变换区分离焦模糊和运动模糊两类模糊的方法.该方法通过比较霍夫变换矩阵中的亮点数来区分两类模糊,不仅正确率达到100%,而且抗干扰性能好;其次通过对运动模糊图像做两次方向微分,估计其模糊方向,提高了模糊方向的估计准确度;最后利用改进的Prewiit算子和费米函数计算模糊图像的刃边函数,进而得到图像的调制传递函数,再利用维纳滤波复原图像.实验结果表明:本文算法不仅具有有效性和强抗噪音能力,而且对图像的信噪比要求可以低到20 dB;与传统算法相比,提高了图像的复原质量.     

多帧融合处理技术在运动模糊图像复原中的应用

运动模糊图像是电视监控中常见的退化图像 ,也是图像处理和检验工作中的难题。针对电视摄像的特点 ,多帧融合处理技术从图像时间序列中提取景物的运动信息 ,构造复原滤波器 ,通过频率域反转滤波方式复原模糊图像。这项技术能够有效地增强电视监控中存在的运动模糊图像 ,并且适用于数字视频图像处理     

Restoration of TDI camera images with motion distortion and blur

Platform movement during exposure of imaging system severely degrades image quality. In the case of Time delay and integration (TDI) camera, abnormal movements cause not only image blur but also distortion, for image Point Spread Function (PSF) is space-variant. In this paper, we present a motion degradation model of TDI image, and provide a method to restore such degraded image. While a TDI camera is imaging, it outputs images row by row (or line by line) along the scanning axis, and our method processes in the same track. We firstly calculate the space-invariant PSF of each row using the movement information of the TDI camera. Then, we substitute pixels of the row and the ones of their neighbor rows together with the PSF into standard Richardson–Lucy algorithm. By deconvoluting we get the restored pixels of the row. The same operations are executed for all rows of the degraded TDI image. Finally, a restored image can be reconstructed from those restored rows. Both simulated and experimental results prove the effectiveness of our method.     

结合基于梯度的振铃评价算法的总变分最小化图像分块复原法

为了消除退化函数随空间变化发生变化模糊图像分块复原法子块之间的不平滑拼接缝,提出了一种结合了基于梯度的振铃评价算法梯度振铃评价(GRM)的总变分(TV)最小化分块复原法.根据图像分布及退化类型将模糊图像划分为矩形、环形或其他形状的子块,图像子块之间要留有一定的重叠区;然后对每一个图像子块进行复原,GRM方法是基于图像梯度结构相似度的图像质量评价算法,以GRM作为TV复原算法迭代过程中的收敛条件,可以更好地控制复原图像的振铃;最后去除复原图像子块含振铃波纹的重叠区,拼接得到完整图像.并以矩形分块及环形分块为例,证明该方法可以很好地抑制图像边界振铃效应,克服分块复原法本身的缺陷,得到拼接平滑的完整图像.     

高频振动模糊图像仿真与分析

研究了运动模糊图像在空间域和频域上的数学模型,根据运动图像的模糊原理,提出了时间等分运动模糊图像的仿真方法,仿真了高频振动模糊图像.理论分析指出,物体做高频谐波振动时运动模糊成像的频谱会由于Bessel函数的零点的存在而形成系列条纹,对振动模糊图像的频谱做两次Radon变换能检测出振动的方向和振幅,从而得到高频振动模糊...     

基于分时积分亚像元融合的地球静止轨道平台消颤振技术

相较于低轨卫星线阵扫描成像模式,地球静止轨道面阵成像的曝光时间相对更长,更容易受到平台颤振的影响而造成图像模糊.为了消除由平台颤振引起的像质退化,本文提出了基于分时积分亚像元融合的方法.由于地球静止轨道的凝视成像特性,相机观察区域在长时间内保持不变,因此分时短曝光可以获得多帧目标内容相同,但模糊尺度更低的短曝光图像.然后对多帧短曝光图像采用基于能量区域质心法的相位相关算法进行亚像元图像配准,计算相对偏移量并进行补偿,位移探测准确度可达0.1像元以内,满足卫星平台应用需求.再按亚像元偏移量对多帧图像进行融合,融合的过程可以提升由于曝光时间缩短而降低的单帧图像信噪比,最终可以获得图像清晰度更高、信噪比与原长曝光图像相当、信息辨识度更好的遥感图像.     

基于分时积分亚像元融合的地球静止轨道平台消颤振技术

相较于低轨卫星线阵扫描成像模式,地球静止轨道面阵成像的曝光时间相对更长,更容易受到平台颤振的影响而造成图像模糊.为了消除由平台颤振引起的像质退化,本文提出了基于分时积分亚像元融合的方法.由于地球静止轨道的凝视成像特性,相机观察区域在长时间内保持不变,因此分时短曝光可以获得多帧目标内容相同,但模糊尺度更低的短曝光图像.然后对多帧短曝光图像采用基于能量区域质心法的相位相关算法进行亚像元图像配准,计算相对偏移量并进行补偿,位移探测准确度可达0.1像元以内,满足卫星平台应用需求.再按亚像元偏移量对多帧图像进行融合,融合的过程可以提升由于曝光时间缩短而降低的单帧图像信噪比,最终可以获得图像清晰度更高、信噪比与原长曝光图像相当、信息辨识度更好的遥感图像.