Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

Succinct Palette and Color Model Generation and Manipulation Using Hierarchical Representation

We propose a new method to obtain the representative colors and their distributions of an image. Our intuition is that it is possible to derive the global model from the local distributions. Beginning by sampling pure colors, we build a hierarchical representation of colors in the image via a bottom‐up approach. From the resulting hierarchy, we can obtain satisfactory palettes/color models automatically without a predefined size. Furthermore, we provide interactive operations to manipulate the results which allow the users to reflect their intention directly. In our experiment, we show that the proposed method produces more succinct results that faithfully represent all the colors in the image with an appropriate number of components. We also show that the proposed interactive approach can improve the results of applications such as recoloring and soft segmentation.     

A new effective and powerful medical image segmentation algorithm based on optimum path snakes

Novel segmentation methods based on models of deformable active contours are constantly proposed and validated in different fields of knowledge, with the aim to make the detection of the regions of interest standard. This paper propose a new method called Optimum Path Snakes (OPS), a new adaptive algorithm and free of parameters to define the total energy of a active contour model with automatic initialization and stop criteria. In the experimental assessment, the OPS is compared against some approaches commonly used in the following fields, such as vector field convolution, gradient vector flow, and other specialists methods for lung segmentation using thorax computed tomography images. The segmentation of regions with stroke was carried out with methods based on region growing, watershed and a specialist level set approach. Statistical validations metrics using Dice coefficient (DC) and Hausdorff distance (HD) were also evaluated, as well as the processing time. The results showed that the OPS is a promising tool for image segmentation, presenting satisfactory results for DC and HD, and, many times, superior to the other algorithms it was compared with, including those generated by specialists. Another advantage of the OPS is that it is not restricted to specific types of images, neither applications.     

Online Detection of Ellipsoidal Bubbles by an Innovative Optical Approach

Bubble and droplet size distribution influence chemical processes markedly. In order to enable an in‐line analysis of these distributions, a new single‐sided endoscopic version of the Optical Multimode Online Probe (OMOP) was developed. The acquired images are analyzed to gain bubble size distributions (BSDs) and main diagonals. A specific workflow was developed to detect and analyze overlapping bubbles based on standard image processing techniques. It can handle overlapping bubbles of both circular and elliptical shapes. Results confirmed that the combination of OMOP and the image processing workflow leads to robust detection of bubbles from two‐dimensional images. The new single‐sided OMOP proved to be a suitable tool for the acquisition of a BSD at industrial scale within a reasonable computing time.     

A Generalized Cubemap for Encoding 360° VR Videos using Polynomial Approximation

360^° VR videos provide users with an immersive visual experience. To encode 360^° VR videos, spherical pixels must be mapped onto a two‐dimensional domain to take advantage of the existing video encoding and storage standards. In VR industry, standard cubemap projection is the most widely used projection method for encoding 360^° VR videos. However, it exhibits pixel density variation at different regions due to projection distortion. We present a generalized algorithm to improve the efficiency of cubemap projection using polynomial approximation. In our algorithm, standard cubemap projection can be regarded as a special form with 1st‐order polynomial. Our experiments show that the generalized cubemap projection can significantly reduce the projection distortion using higher order polynomials. As a result, pixel distribution can be well balanced in the resulting 360^° VR videos. We use PSNR, S‐PSNR and CPP‐PSNR to evaluate the visual quality and the experimental results demonstrate promising performance improvement against standard cubemap projection and Google's equi‐angular cubemap.     

基于DenseNet的复杂交通场景语义分割方法

针对交通场景语义分割方法存在参数量较大、计算效率较低、精度不足等问题,文中提出基于全卷积化DenseNet的多尺度端到端语义分割模型.首先,构建一种含混合空洞卷积的密集连接模块,同时沿通道维度级联各模块,用于提取图像特征.然后,采集多尺度视觉信息并以此作为监督信号回传至原通道中.最后,通过双线性插值法获得预测输出.在CityScapes数据集上的测试实验表明,文中方法对复杂交通场景的解析能力较强,预测精度和分割效率较高.     

An Approach to Synthesize Diverse Underwater Image Dataset

Images that are taken underwater mostly present color shift with hazy effects due to the special property of water.Underwater image enhancement methods are prop...     

Image‐based Continuous Displacement Measurements Using an Improved Spectral Approach

Digital Image Correlation algorithms capable of determining continuous displacement fields are receiving growing attention in the field of mechanical properties identification. In this paper, we develop an Improved Spectral Approach (ISA) to reconstruct continuous displacements based on their Fourier decomposition. This approach leads to a time and memory‐efficient algorithm, thanks to the fast Fourier transform. Moreover, the Fourier‐based decomposition enables accurate heterogeneous measurements. Improvements consist in increasing the accuracy and convergence rate as well as dealing with non‐periodic displacements and images. Furthermore, a theoretical framework is presented to quantify the noise sensitivity of the ISA from which useful information is retrieved. The approach is evaluated using synthetic images deformed by heterogeneous displacement fields. Comparisons show that the introduced modifications lead to lower uncertainties by one order of magnitude in the case of non‐periodic images and displacement field studied. Moreover, first‐order (SO1) and second‐order (SO2) subset‐based Digital Image Correlation algorithms are compared with the ISA. The comparisons herein reveal that the uncertainties of the ISA are 6–9 times smaller than those of the SO1 due to insufficiency of the first‐order shape function for the estimation of heterogeneous displacements, while being slightly smaller than those of the SO2. Moreover, as the image smoothness decreases, the uncertainties of the SO2 deviate from those of the ISA and the exact displacements. The presented approach shows great potentials for challenging applications such as strain measurements at microstructural levels.     

Improving pore morphology of PM 316L stainless steels by prealloyed powder prepassivation in 20% nitric acid

Abstract

The effect of prepassivation of prealloyed powder of 316L stainless steels on pore morphology and powder particle shape was investigated. Image analysis technique was used to study the effect of prepassivation, compaction and sintering temperature on the pore morphology of powder metallurgy 316L stainless steels. Porosity, dimension and morphology of the pores were characterised by means of four basic parameters: fraction of surface porosity, equivalent circle diameter, shape factor and elongation factor. In addition, SEM macrographs of powder particles were also investigated by applying the image analysis technique. The Feret’s average diameter and elongation factor were employed to describe the size and roundness of powder particles respectively. Annealing treatment reduced the equivalent circle diameter of pores and simultaneously improved f_shape and f_elong towards higher values. It was proposed that the prepassivation treatment reduced irregularity of powder particles through elimination of sharp corners of powder particles by exposure to acid environment.     

A novel mesh subdivision algorithm for dense reconstruction from multi-image based on preliminary model

To solve the disadvantages of the recent three-dimensional (3D) reconstruction methods, this paper presents a dense reconstruction algorithm which incorporates image features into the mesh subdivision. A preliminary model is deformed from statistical deformation model (SDM) to catch the roughest features, and later densified under a multi-resolution frame to achieve a dense model until all image features are used. In every round of this framework, the image features are detected, and then cut into planar points. At the same time, the transitional model is re-projected into views, and all images are segmented to triangles. So the planar points are constrained by these triangles, and the corresponding relations among these triangles are certain. Then some new spatial points are generated from these planar points and subdivide the transitional model. Later, the transitional model is re-arranged to get a right topology, and becomes denser. This method contributes three novelties: (1) there is an inherited relationship between the later points and the early points; (2) if the hierarchy of multi-resolution frame and the number of new spatial points at every round are set appropriately, the transitional model evolves with a correct topology; (3) the density of the final model is proportional to the information account of views. The experiment validates these virtues.