An Automatic Precise Registration Method Based on the Relative Geometric Calibration Between Bands for Satellite Multi-spectral Image

2017 ◽  
pp. 309-319
Author(s):  
He Wei ◽  
Long Xiaoxiang ◽  
Yu Jing ◽  
Zhang Chi
Keyword(s):  
Spectral Image ◽  
Registration Method ◽  
Geometric Calibration

scholarly journals Detection and Compensation of Band-to-band Registration Error for Multi-spectral Imagery Caused By Satellite Jitter

2014 ◽  
Vol II-1 ◽  
pp. 69-76 ◽  
Author(s):  
Y. Zhu ◽  
M. Wang ◽  
Q. Zhu ◽  
J. Pan
Keyword(s):  
High Frequency ◽  
Compensation Method ◽  
Registration Accuracy ◽  
Spectral Image ◽  
Registration Method ◽  
Registration Error ◽  
Along Track ◽  
The Impact ◽  
Attitude Sensor

Satellite jitter has become a more and more important factor which affects the quality of imagery products with development of the high resolution satellite. This paper focused on analyzing the impact on multi-spectral image caused by satellite jitter and proposed a jitter detection and compensation method to improve the band-to-band registration efficiently when jitter exists without observation by attitude sensor. Firstly, the design of multi-spectral camera and the mainstream band-to-band registration method is introduced to explain factors influencing the registration accuracy. As one of factors, satellite jitter is an unexpected satellite movement and do have impact on registration on both across and along track but easy to be ignored for the lack of high frequency and accuracy attitude data. So next the jitter detection and compensation method is proposed, in which there are six main steps to achieve the analysis of registration accuracy with and without jitter and improvement of registration accuracy after compensation when the jitter cannot be ignored. Finally, three sets of multi-spectral images of ZY-3 were used to verify the proposed method. As a result, the error caused by satellite jitter was suppressed efficiently from 0.2pixels to 0.02pixels and registration accuracy (RMSE) was improved from 0.32 pixels to 0.11 pixels by the proposed method. The results indicate that the proposed method can detect and compensate the distortion of multi-spectral image caused by satellite jitter accurately and efficiently.

Spectral Image Registration Method Based on SURF Maximum Submatrix

2019 ◽  
Vol 56 (6) ◽  
pp. 063002
Author(s):  
刘加林 Liu Jialin ◽  
王慧琴 Wang Huiqin ◽  
王可 Wang Ke ◽  
吴萌 Wu Meng ◽  
赵丽娟 Zhao Lijuan ◽  
...  
Keyword(s):  
Image Registration ◽  
Spectral Image ◽  
Registration Method

scholarly journals A High-Precision Registration Technology Based on Bundle Adjustment in Structured Light Scanning System

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jianying Yuan ◽  
Qiong Wang ◽  
Xiaoliang Jiang ◽  
Bailin Li
Keyword(s):  
High Precision ◽  
Large Scale ◽  
Structured Light ◽  
Bundle Adjustment ◽  
Scanning System ◽  
Control Points ◽  
Registration Method ◽  
Global Control ◽  
3D Data ◽  
Structured Light Scanning

The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

scholarly journals A Preprocess Method of External Disturbance Suppression for Carotid Wall Motion Estimation Using Local Phase and Orientation of B-Mode Ultrasound Sequences

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Qinghui Zhang ◽  
Junqiu Li ◽  
Zhenping Qiang ◽  
Libo He
Keyword(s):  
Motion Estimation ◽  
Wall Motion ◽  
Structural Information ◽  
External Disturbance ◽  
Estimation Accuracy ◽  
Ultrasound Images ◽  
Local Phase ◽  
Registration Method ◽  
Anisotropic Diffusion Filter ◽  
Disturbance Suppression

Estimating the motions of the common carotid artery wall plays a very important role in early diagnosis of the carotid atherosclerotic disease. However, the disturbances caused by either the instability of the probe operator or the breathing of subjects degrade the estimation accuracy of arterial wall motion when performing speckle tracking on the B-mode ultrasound images. In this paper, we propose a global registration method to suppress external disturbances before motion estimation. The local vector images, transformed from B-mode images, were used for registration. To take advantage of both the structural information from the local phase and the geometric information from the local orientation, we proposed a confidence coefficient to combine them two. Furthermore, we altered the speckle reducing anisotropic diffusion filter to improve the performance of disturbance suppression. We compared this method with schemes of extracting wall displacement directly from B-mode or phase images. The results show that this scheme can effectively suppress the disturbances and significantly improve the estimation accuracy.

scholarly journals Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds

2021 ◽  
Vol 13 (11) ◽  
pp. 2195
Author(s):  
Shiming Li ◽  
Xuming Ge ◽  
Shengfu Li ◽  
Bo Xu ◽  
Zhendong Wang
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Registration Method ◽  
Cloud Data ◽  
Linear Feature ◽  
Data Registration ◽  
Source Point ◽  
Urban Remote Sensing ◽  
Single Data

Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity. Accurate co-registration can make up for the limitations of a single data source, but many existing registration methods face critical challenges. Therefore, in this paper, we propose a systematic incremental registration method that can successfully register MLS and photogrammetric point clouds in the presence of a large number of missing data, large variations in point density, and scale differences. The robustness of this method is due to its elimination of noise in the extracted linear features and its 2D incremental registration strategy. There are three main contributions of our work: (1) the development of an end-to-end automatic cross-source point-cloud registration method; (2) a way to effectively extract the linear feature and restore the scale; and (3) an incremental registration strategy that simplifies the complex registration process. The experimental results show that this method can successfully achieve cross-source data registration, while other methods have difficulty obtaining satisfactory registration results efficiently. Moreover, this method can be extended to more point-cloud sources.

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