Multi-scale Orientation Research Articles

Accelerated cardiac cine MRI using spatiotemporal correlation-based hybrid plug-and-play priors (SEABUS)

Objective. The plug-and-play prior (P3) can be flexibly coupled with multiple iterative optimizations, which has been successfully applied to the inverse problems of medical imaging. In this work, for accelerated cardiac cine magnetic resonance imaging (CC-MRI), the Spatiotemporal corrElAtion-based hyBrid plUg-and-play priorS (SEABUS) integrating a local P3 and a nonlocal P3 are introduced. Approach. Specifically, the local P3 enforces pixelwise edge-orientation consistency by conducting reference frame guided multiscale orientation projection on a subset containing a few adjacent frames; the nonlocal P3 constrains the cubewise anatomic-structure similarity by performing cube matching and 4D filtering (CM4D) on all frames. By using effectively a composite splitting algorithm (CSA), SEABUS is incorporated into a fast iterative shrinkage-thresholding algorithm and a new accelerated CC-MRI approach named SEABUS-FCSA is proposed. Main results. The experiment and algorithm analysis demonstrate the efficiency and potential of the proposed SEABUS-FCSA approach, which has the best performance in terms of reducing aliasing artifacts and capturing dynamic features in comparison with several state-of-the-art accelerated CC-MRI technologies. Significance. Our approach aims to propose a new hybrid P3 based iterative algorithm, which is not only used to improve the quality of accelerated cardiac cine imaging but also extend the FCSA methodology.

HR optical and SAR image registration using uniform optimized feature and extend phase congruency

ABSTRACT With increasing spatial resolution, the differences in nonlinear radiation and geometric properties between optical and synthetic aperture radar (SAR) images will be magnified, which will lead to lower registration accuracy. This paper addresses this problem and proposes an automatic registration method for HR optical and SAR images using the uniform optimized feature and the extended phase congruency (EPC) model. First, we combine two different gradient operators and a quadtree algorithm to improve the detection performance of the multi-scale Harris detector, especially for the repeatability and uniformity of feature points in optical and SAR images with large nonlinear radiation and severe speckle noise. Next, we use the EPC model with illumination and contrast invariance to generate the multi-scale orientation index map (MS-OIM) and the multi-orientation phase congruency amplitude map (MO-PCAM) and then build a novel GLOH-like local descriptor to obtain corresponding features based on the two feature maps above. Finally, the fast sample consensus (FSC) method is utilized to remove false matches and calculate the transformation parameters of sensed image based on the piecewise linear model. The detection results on synthetic data show that the proposed detector has better repeatability and uniformity than the other three classical detectors. The registration results obtained on real data indicate that our method is effective for optical and SAR images with speckle noise interference and nonlinear radiometric differences and achieves high registration accuracy.

A Multi-scale Approach to Interculturalism: From Globalised Politics to Localised Policy and Practice

Interculturalism (IC) is presently discussed as a foundational basis for local public policy aimed at managing migration-related diversity within ethno-culturally plural societies, especially at the local level. Despite its increased saliency over the last decade, IC is neither theoretically new nor was it always intended for mere application in strictly city contexts of diversity. Rather, it has a global origin as a political basis for international relations and negotiations. In discussing these origins, this article has two main interrelated aims. Firstly, it provides an overview of the multi-scale approach of IC, with the purpose of disentangling analytically the different empirical bases where it can frame the diversity agenda. Secondly, it explores whether a lack of appreciation and awareness of this multi-scale orientation may affect IC’s capacity to address the challenges of diversity governance at the local level. Methodologically, the article will undertake a textual analysis of a select number of leading documents framing its practice within the broader policy literature produced by the four main institutions that have advocated the intercultural approach within a global agenda. These are the United Nations Educational, Scientific and Cultural Organization (UNESCO) and United Nations University, on one hand, and the European Union and the Council of Europe on the other. The main findings show us the importance of a multi-scale thinking in diversity and IC studies, to avoid contributing to greater confusion in its applications.

Robust Multiscale-Oriented Thermoresponsive Fibrous Hydrogels with Rapid Self-Recovery and Ultrafast Response Underwater.

Hydrogels with ultrafast response to environmental stimuli, possessing robust structural integrity and rapid self-recovery, have been considered as promising platforms for numerous applications, for example, in biomimetic materials and nanomedicine. Inspired by the bundled fibrous structure of actin, we developed a robust and ultrafast thermoresponsive fibrous hydrogel (TFH) by fully utilizing the weak noncovalent bonds and strong covalently cross-linked semiflexible electrospun fibrous nets. The TFH exhibits an ultrafast response (within 10 s), rapid self-recovery rate (74% within 10 s), tunable tensile strength (3-380 kPa), and high toughness (∼1560 J/m2) toward temperature. A multiscale orientation is considered to play a key role in the excellent mechanical properties at the fibrous mesh, fiber, and molecular scales. Furthermore, to take advantage of this TFH adequately, a novel kind of noodle-like hydrogel for thermo-controlled protein sorption based on the TFH is prepared, which exhibits high stability and ultrafast sorption properties. The bioinspired platforms hold promise as artificial skins and "smart" sorption membrane carriers, which provide a unique bioactive environment for tissue engineering and nanomedicine.

RETRACTED ARTICLE: A feature based change detection approach using multi-scale orientation for multi-temporal SAR images

ABSTRACT Excellent operation regardless of weather conditions and superior resolution independent of sensor light are the most attractive and desired features of synthetic aperture radar (SAR) imagery. This paper proposes an exclusive multi-scale with multiple orientation approach for multi-temporal SAR images. This approach integrates pre-processing and change detection. Pre-processing is performed on the SAR imagery through speckle reducing anisotropic diffusion and discrete wavelet transform. The processed speckle-free images are designed by Log-Gabor filter bank in terms of multi-scale with multiple orientations. The maximum magnitude of multiple orientations is concatenated to obtain feature-based scale representation. Each scale is dealt with multiple orientations and is compared by band-wise subtraction to retrieve difference image (DI) coefficient. The series of the difference coefficients from each scale are add-on together to estimate a DI. Thus, the resultant image of multi-scale orientation gives perception of detailed information with specific contour. Constrained k-means clustering algorithm is preferred to achieve change and un-change map. Performance of the proposed approach is validated on three real SAR image datasets. The effective change detection is examined by using confusion matrix parameters. Experimental results are described to show the efficacy of the proposed approach.

A Novel Multi-Sensor Image Matching Algorithm Based on Adaptive Multiscale Structure Orientation

Automatic and reliable multi-sensor image matching is a very challenging task due to the significant nonlinear radiometric differences between multi-sensor images. In this paper, a novel dense descriptor based on adaptive multiscale structure orientation is proposed for capturing the geometrical structure information of an image. The dense descriptor of the proposed matching algorithm is not only illumination and contrast invariant but also robust against the image noise. Further, an improved similarity measurement is introduced for adapting the orientation reversal caused by the intensity inversion between multi-sensor images. Based on the robust dense descriptor and the improved similarity measurement, we developed a novel and practical template matching algorithm to match multi-sensor images reliably. We evaluate the proposed matching algorithm by comparing it with other state-of-the-art algorithms. The experimental results show the proposed algorithm has a significant advantage on matching accuracy.

Nonrigid Registration Regularized by Shape Information: Application to Atlas Construction of Cardiac CT Images.

Cardiac atlases play an important role in the computer-aided diagnosis of cardiovascular diseases, in particular they need to deal with large and highly variable image datasets. In this paper, we propose a new nonrigid registration algorithm incorporating shape information, to produce comprehensive atlases. For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information. Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration. We demonstrate the merits of the new registration algorithm on the 3D data sets of 15 patients. The experimental results show that the new registration algorithm can outperform the conventional intensity-based registration method. The obtained atlas can represent the cardiac structures more accurately.

Robust multi-scale orientation estimation: Directional filter bank based approach

Orientation estimation is considered as an important task in many subsequent pattern recognition and image enhancement systems. In a noisy environment, the gradient-based estimator provides poor results. A pre-smoothing Gaussian function with an appropriate scale is conventionally used to get improved gradients. Later on, a family of pre-smoothing Gaussian functions with a range of scales is employed for estimation, this is referred to as multi-scale orientation estimator. To provide groundwork for comparison, a more formal framework of multi-scale orientation estimation, based on scale-space axioms, in spatial domain is presented. Then for improvement purposes a Fourier domain approach, where directional filter bank (DFB) structure is embedded in multi-scale orientation estimation framework, is proposed. This is referred to as multi-scale DFB approach. The paper presents the comparison work for estimation of local orientations using multi-scale approaches both in spatial and Fourier domain. In the Fourier-domain approach, two linear combinations are deployed, one across the directional image, and the other across the scales. This is opposed to only one linear combination across the scales, used in simple spatial domain techniques. Further more, the DFB-based Fourier domain approach extracts the best local orientation by comparing and contrasting all possible orientations with their respective strength measures. The strength measure used in Fourier method is based on local variance, free from inaccurate gradient calculation. Simulations are conducted over noisy test images as well as real fingerprints. Our objective results indicate that multi-scale Fourier domain approach always yields better estimates at variable level of noise as compared to stand alone multi-scale spatial domain approaches. The improvements made by Fourier domain estimate can largely be attributed to the use of double linear combination both across the directional bands and across the scales.

Fast and Robust Pedestrian Detection Algorithm with Multi-Scale Orientation Features

PDF HTML阅读 XML下载 导出引用 引用提醒 基于多尺度方向特征的快速鲁棒人体检测算法 DOI: 10.3724/SP.J.1001.2011.03987 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(61039003, 60872143); 国家重点基础研究发展计划(973)(2011CB706900, 2010CB731800) Fast and Robust Pedestrian Detection Algorithm with Multi-Scale Orientation Features Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:提出一种多尺度方向(multi-scale orientation,简称MSO)特征描述子用于静态图片中的人体目标检测.MSO 特征由随机采样的图像方块组成,包含了粗特征集合与精特征集合.其中,粗特征是图像块的方向,而精特征由Gabor 小波幅值响应竞争获得.对于两种特征,分别采用贪心算法进行选择,并使用级联Adaboost 算法及SVM 训练检测模型.基于粗特征的Adaboost 分类器能够保证高的检测速度,而基于精特征的SVM 分类器则保证了检测精度.另外,通过MSO 特征块的平移,使得所提算法能够检 Abstract:The multi-scale orientation (MSO) features for pedestrian detection in still images are put forwarded in this paper. Extracted on randomly sampled square image blocks (units), MSO features are made up of coarse and fine features, which are calculated with a unit gradient and the Gabor wavelet magnitudes respectively. Greedy methods are employed respectively to select the features. Furthermore, the selected features are inputted into a cascade classifier with Adaboost and SVM for classification. In addition, the spatial location of MSO units can be shifted, are used to the handle multi-view problem and assembled; therefore, the occluded features are completed with average features of training positives, given an occlusion model, which enable the proposed approach to work in crowd scenes. Experimental results on INRIA testset and SDL multi-view testset report the state-of-arts results on INRIA include it is 12.4 times the faster than SVM+HOG method. 参考文献 相似文献 引证文献

Preservation of multiscale lamellar twinning texture and crystallographic orientation in the replacement of leucite by analcime

Preservation of multiscale lamellar twinning texture and crystallographic orientation in the replacement of leucite by analcime

Efficient fingerprint search based on database clustering

Fingerprint identification has been a great challenge due to its complex search of database. This paper proposes an efficient fingerprint search algorithm based on database clustering, which narrows down the search space of fine matching. Fingerprint is non-uniformly partitioned by a circular tessellation to compute a multi-scale orientation field as the main search feature. The average ridge distance is employed as an auxiliary feature. A modified K-means clustering technique is proposed to partition the orientation feature space into clusters. Based on the database clustering, a hierarchical query processing is proposed to facilitate an efficient fingerprint search, which not only greatly speeds up the search process but also improves the retrieval accuracy. The experimental results show the effectiveness and superiority of the proposed fingerprint search algorithm.

Texture of welded joints of 316L stainless steel, multi-scale orientation analysis of a weld metal deposit

Weld material of type 316L is widely used in stainless steel X weldments in fast breeder reactors. As it is difficult to cut test specimens from an X weldment, the two-phase microstructure of 316L welds was simulated by manually filling a mould with longitudinally deposited weld beads. The material consists of γ columnar grains which form a matrix where δ-ferrite dendrites can be found. The crystallographic texture of the material was investigated on the basis of a multi-scale approach. Neutron diffraction analysis showed that on a macroscopic scale both phases had predominantly the same fibre texture with some reinforcements, {1 0 0} γ being parallel to {1 0 0} δ. Further analysis on an increasingly fine scale were then carried out by EBSD and by TEM, showing that the ferrite dendrites were nearly parallel to the neighbouring austenite columnar grains