Wavelet based deep learning for depth estimation from single fringe pattern of fringe projection profilometry

Depth estimation from single fringe pattern is a fundamental task in the field of fringe projection three-dimensional (3D) measurement. Deep learning based on a convolutional neural network (CNN) has attracted more and more attention in fringe projection profilometry (FPP). However, most of the studies focus on complex network architecture to improve the accuracy of depth estimation with deeper and wider network architecture, which takes greater computational and lower speed. In this letter, we propose a simple method to combine wavelet transform and deep learning method for depth estimation from the single fringe pattern. Specially, the fringe pattern is decomposed into low-frequency and high-frequency details by the two-dimensional (2D) wavelet transform, which are used in the CNN network. Experiment results demonstrate that the wavelet-based deep learning method can reduce the computational complexity of the model by 4 times and improve the accuracy of depth estimation. The proposed wavelet-based deep learning models (UNet-Wavelet and hNet-Wavelet) are efficient for depth estimation of single fringe pattern, achieving better performance than the original UNet and hNet models in both qualitative and quantitative evaluation.     

Wall position and thickness estimation from sequences of echocardiographic images

Presents a new method for endocardial (inner) and epicardial (outer) contour estimation from sequences of echocardiographic images. The framework herein introduced is fine-tuned for parasternal short axis views at the papillary muscle level. The underlying model is probabilistic; it captures the relevant features of the image generation physical mechanisms and of the heart morphology. Contour sequences are assumed to be two-dimensional noncausal first-order Markov random processes; each variable has a spatial index and a temporal index. The image pixels are modeled as Rayleigh distributed random variables with means depending on their positions (inside endocardium, between endocardium and pericardium, or outside pericardium). The complete probabilistic model is built under the Bayesian framework. As estimation criterion the maximum a posteriori (MAP) is adopted. To solve the optimization problem, one is led to (joint estimation of contours and distributions' parameters), the authors introduce an algorithm herein named iterative multigrid dynamic programming (IMDP). It is a fully data-driven scheme with no ad-hoc parameters. The method is implemented on an ordinary workstation, leading to computation times compatible with operational use. Experiments with simulated and real images are presented.     

一种用于分析条纹图案的自动相位测量法

本文提出一种以离散余弦变换(DCT)为基础的自动相位测量方法并以实验和模拟运算进行验证。     

瞬态干涉图条纹预处理方法研究

本文就含冲击波的瞬态流场干涉图的预处理方法，特别是细化算法进行了研究，通过处理的瞬态流场干涉图可满足后续的计算机自动数值处理要求。     

A high-performance measurement method for artery intimamedia thickness in medical ultrasound images

A high-performance measurement method for the artery intima-media thickness (IMT) in medical ultrasound images is proposed. The scheme mainly consists of two parts. The first part is the detection process, including adaptive gray stretching for image enhancing, gradient transforming to restrain the over-segmentation, and the watershed algorithm for edge extraction. The intima can be detected automatically and exactly. The second part, combined with regional positioning and boundary fitting stages, is used to measure the IMT. Experimental results show that the proposed scheme can yield a good measurement result, and the calculation time can satisfy the practical requirement.     

Correlation estimation from compressed images

This paper addresses the problem of correlation estimation in sets of compressed images. We consider a framework where the images are represented under the form of linear measurements due to low complexity sensing or security requirements. We assume that the images are correlated through the displacement of visual objects due to motion or viewpoint change and the correlation is effectively represented by optical flow or motion field models. The correlation is estimated in the compressed domain by jointly processing the linear measurements. We first show that the correlated images can be efficiently related using a linear operator. Using this linear relationship we then describe the dependencies between images in the compressed domain. We further cast a regularized optimization problem where the correlation is estimated in order to satisfy both data consistency and motion smoothness objectives with a Graph Cut algorithm. We analyze in detail the correlation estimation performance and quantify the penalty due to image compression. Extensive experiments in stereo and video imaging applications show that our novel solution stays competitive with methods that implement complex image reconstruction steps prior to correlation estimation. We finally use the estimated correlation in a novel joint image reconstruction scheme that is based on an optimization problem with sparsity priors on the reconstructed images. Additional experiments show that our correlation estimation algorithm leads to an effective reconstruction of pairs of images in distributed image coding schemes that outperform independent reconstruction algorithms by 2–4 dB.     

干涉条纹中心线提取与细化的新方法

干涉条纹分析是光学干涉计量的重要分析方法,本文提出基于改进Yangtagai求极值点法与改进Hilditch细化法相结合的干涉条纹中心线提取与细化方法,该方法具有条纹断点少、抗噪声能力强以及处理速度快的特点。通过实验证实了本文提出方法的有效性。     

单幅干涉条纹图相位提取新算法

散斑干涉测量中,得到的干涉条纹图必须通过提取当中的真实相位才能够得出所测的物理量。从干涉条纹图中提取相位常用的相移法,过程复杂、对环境要求较高,而且要通过解包裹运算才能求得真实相位,容易产生误差。通过希尔伯特变换,基于离散余弦求解泊松方程的方法,提出从单幅干涉条纹中提取真实相位的新算法。通过实验分析,本文提出的新方法能够有效地从单幅干涉条纹中提取真实相位,并且在现实情况中,本文提出的新方法从单幅干涉条纹图中提取相位误差小于相移法,而且运行速度快,为从干涉条纹图中提取真实相位提供了新的参考。     

Least-squares font metric estimation from images

The problem of determining font metrics from measurements on images of typeset text is discussed, and least-squares procedures for font metric estimation are developed. When it is shown that kerning is not present, sidebearing estimation involves solving a set of linear equations, called the sidebearing normal equations. More generally, simultaneous sidebearing and kerning term estimation involves an iterative procedure in which a modified set of sidebearing normal equations is solved during each iteration. Character depth estimates are obtained by solving a set of baseline normal equations. In a preliminary evaluation of the proposed procedures on scanned text images in three fonts, the root-mean-square set width estimation error was about 0.2 pixel. An application of font metric estimation to text image editing is discussed.     

Direct method for rotation estimation from spherical images using 3D mesh surfaces with SPHARM representation

Since a large field of view obviously bears important advantages, the use of spherical images is becoming increasingly important in various computer vision and image processing applications. This paper presents a novel rotation estimation approach for spherical images based on 3D mesh representation of gray level intensity. Once the 3D meshes of the underlying spherical images are obtained, the 3D rotation can be estimated directly and efficiently, without feature extraction and matching process. Subsequently, we propose a direct method for 3D object rotation estimation using spherical harmonics representation with SVD decomposition and ICP algorithm for estimation refinement. Experimental results validate our approach and prove its suitability and robustness for rotation estimation. Moreover, it performs well against noisy images, brightness changes, image compression and occlusions. A comparative study of our proposed approach with four similar methods for 3D rotation estimation between spherical images, is realized to prove its effectiveness.     

一种快速光栅条纹中心亚像素坐标提取方法

光栅条纹中心的精确提取会直接影响到线结构光视觉的测量与重建精度。为了解决传统的Steger算法计算量大,且在光条不均匀时提取不精确等问题。基于改进的Steger算法,提出了针对光栅条纹中心的快速亚像素坐标提取方法。通过高斯滤波、形态学等方法得到去复杂背景的激光条纹图像,用自适应阈值法缩小ROI区域,用霍夫变化求取光栅边缘线,求出边缘线中点,然后直线拟合,最后用改进算法提取中心坐标。实验结果表明:与模板法、传统Steger算法等光栅条纹中心提取算法相比,算法的鲁棒性更强,最大提取误差在0.3个像素,平均误差为0.1个像素,平均运行时间相比传统算法减少0.4 s。     

A method for brain 3D surface reconstruction from MR images

Due to the encephalic tissues are highly irregular, three-dimensional （3D） modeling of brain always leads to compli- cated computing. In this paper, we explore an efficient method for brain surface reconstruction from magnetic reso- nance （MR） images of head, which is helpful to surgery planning and tumor localization. A heuristic algorithm is pro- posed foi＂ surface triangle mesh generation with preserved features, and the diagonal length is regarded as the heuristic information to optimize the shape of triangle. The experimental results show that our approach not only reduces the computational complexity, but also completes 3D visualization with good quality.     

A new eigenstructure method for sinusoidal signal retrieval inwhite noise: estimation and pattern recognition

A new approach, in a framework of an eigenstructure method using a Hankel matrix, is developed for sinusoidal signal retrieval in white noise. A closed-form solution for the singular pairs of the matrix is defined in terms of the associated sinusoidal signals and noise. The estimated sinusoidal singular vectors are applied to form the noise-free Hankel matrix. A pattern recognition technique is proposed for partitioning signal and noise subspaces based on the singular pairs of the Hankel matrix. Three types of cluster structures in an eigen-spectrum plot are identified: well-separated, touching, and overlapping. The overlapping, which is the most difficult case, corresponds to a low signal-to noise ratio (SNR). Optimization of Hankel matrix dimensions is suggested for enhancing separability of cluster structures. Once features have been extracted from both singular value and singular vector data, a fuzzy classifier is used to identify each singular component. Computer simulations have shown that the method is effective for the case of “touching” data and provides reasonably good results for a sinusoidal signal reconstruction in the time domain. The limitations of the method are also discussed     

Illuminant-tilt estimation from images of isotropic texture

The authors present a new illuminant-tilt-angle estimator that works with isotropic textures. It has been developed from Kube and Pentland's (1988) frequency-domain model of images of three-dimensional texture, and is compared with Knill's (1990) spatial-domain estimator. The frequency and spatial-domain theory behind each of the estimators is related via an alternative proof of the basic phenomena that both estimators exploit: that is that the variance of the partial derivative of the image is at a maximum when the partial derivative is taken in the direction of the illuminant's tilt. Results obtained using both simulated and real textures suggest that the frequency-domain estimator is more accurate     

散斑干涉条纹图降噪技术比较研究

电子散斑干涉条纹图在形成的过程中引入大量的散斑噪声,有效地去除噪声是电子散斑干涉技术研究的重要课题之一。对电子散斑干涉条纹的降噪方法进行了比较研究,仿真结果表明,传统的空域降噪方式在滤除噪声的同时对图像造成了一定的模糊,降低了图像的对比度。只有在降噪的同时充分地考虑条纹的方向性和条纹密度,才能更好地保留条纹图的结构和对比度,并为下一步提取相位图进行测量奠定一个好的基础。     

投影条纹相位测量的一种新的计算方法

投影条纹用于三维物体的面形测量,已取得许多进展,其相位解调的计算方法,主要有相对法和富里叶变换法等,在本文中我们提出一种新的相位解调的计算方法,就是把被物体调制后的干涉条纹,分为许多小段,分别用多项式进行拟合,再把每一段分别与未被物体调制的前干涉条纹,逐点进行相位比较,求出物体对干涉条纹的相位调制量,再求出对应的物体面形高度,文中还给出一弓形物体的调制和相位解调的计算机模拟结果。     

A robust method for fingerprinting digital images

In this paper, a method to fingerprint digital images is proposed, and different watermarked copies with different identification string are made. After determining the number of the customers and the length of the watermark string, this method chooses some values inside the digital image using a characteristic function, and adds watermarks to these values in a way that can protect the product against the attacks happened by comparing two fingerprinted copies. The watermarks are a string of binary numbers -1s and 1s. Every customer will be distinguished by a series of 1s and -1s generated by a pseudo-random generator. The owner of the image can determine the number of customers and the length of the string as well as this method will add another watermarking values to watermark string to protect the product.     

基于光谱空间信息的高光谱遥感图像混合噪声评估

综合利用高光谱图像的光谱信息和空间信息,提出了一种新的混合噪声评估方法.首先通过滤波算法进行图像中均匀图像块的自动选取;然后利用多元线性回归模型,将均匀图像块内像素点的信号值和噪声值进行分离,并实现了图像中加性、乘性噪声的粗评估;最后根据噪声模型构建似然函数,利用最大似然估计法求解噪声模型参数.通过仿真图像和真实高光谱图像进行实验,验证了该方法的准确性和鲁棒性.     

Remarks on the differential method for the estimation of movement in television images

In this paper a physical interpretation is given of a method for the estimation of movements in television images. The method, already presented by the author in other papers, is based on a linear regression of the image derivatives, both spatial and temporal. It is shown that a centered finite differences approximation of the image differentials is mandatory to obtain good performances. Experimental results are issued to support theoretical conclusions.