Brief Introduction of
VisionOnSky Co., Ltd.
Short Biography of the Founder
VisionOnSky
Co., Ltd. is founded by scientific researcher, and is a startup company which
is concentrating on the development of state-of-the-art technology, software
realization of the new techniques and industrial applications in
photogrammetry, remote sensing and computer vision.
The company
independently developed a both effect and performance optimized semi-global
matching (SGM) algorithm which is applied to dense stereo matching of aerial
image (including oblique aerial image), satellite image and UAV image. It
generates highly dense point clouds and digital surface model (DSM) through
finding the point corresponding for each pixel. We also developed a multilevel
triangle-based ground filtering algorithm, which can transform DSM to DTM
(Digital Terrain Model) automatically, i.e., removing the height of building
and tree, only remaining the height of pure ground. The algorithm can select
different level of terrain details in the light of the requirements. The DSM
transformed to DTM can be extracted from satellite image, aerial image, UAV
image as well as LiDAR points. We presented a
block-regression (BR) based pansharpening algorithm.
The algorithm can combine a lower resolution multispectral image and a higher
resolution panchromatic image both covering a same area, and produce a new
higher resolution image, in which not only the color content are remained but
also the spatial details are enhanced by adopting the higher resolution
panchromatic image. BR algorithm can achieve a maximum enhancement of its
spatial details at the expense of a minimum spectral distortion for the
multispectral images. In the algorithm, the bands of the multispectral image
used can not be limited and the algorithm is
specially optimized for the pansharpening of very
high resolution satellite image. We also developed a series of parallel
techniques with different processing levels, which are suitable for different
steps of image processing. Not only concurrently processing of multiple tasks
but also parallel processing in a single task is supported. The series of
parallel techniques can be used either on multi-core computer or on cluster
computer.
The above
innovative techniques are realized by the form of software and we also
developed several additional software modules. These functional modules can
compose a whole flowchart. We developed modules of stereo matching, automatic
DSM extraction, DSM2DTM, orthorectification, pansharpening of satellite image, the automatic orientation
for a stereo / triplet of satellite images, change detection of surface height
for aerial, satellite and UAV images, respectively. The whole flowcharts for
aerial, satellite and UAV images, respectively, are fulfilled. After the
abovementioned flowcharts, dense point clouds, DSM, DTM, nDSM,
orthorectified image, pansharpened
image and difference of surface height are produced. The software supports
Windows OS and Linux OS, and can run on multi-core computer and cluster
computer. The parallel techniques with different processing levels can leverage
computational resources of the two types of computing platforms to the maximum
extent.
The developed
cutting-edge techniques and software can be applied to these aspects: (1)
generation of mapping products (point clouds, DSM, DTM, orthorectified
image, and pansharpened image); (2) automatically
finding of new buildings, the buildings breaking the planning, and removed
buildings, and estimating their corresponding accurate height; (3) monitoring
the construction progress of new city, big residential district and huge
engineering project; (4) testimony of land expropriation and housing
demolition; (5) estimating the exploited volume of ores located on surface; (6)
digital city and reconstruction of 3D scene; (7) collection of commercial and
military intelligence; (8) accurate estimation of height of buildings and
trees.
VisionOnSky
Co., Ltd. can provide different channels through which the capacity of
different customers is enhanced. For companies with the data-intensive
production, we promote their processing efficiency by optimizing their
procedure and offering them the methods with high efficiency. For
application-oriented companies, we help them to engage new and more profitable
applications by means of technical updating. For software companies, we help
them to improve their own software system by licensing them our technical
modules. For companies providing cloud service, we as software provider offer
them our professional software. For the users in academic research and
education, we provide them the rapid realization of techniques and experiments
in the course of research study by offering them our software and services.
The mission of VisionOnSky Co., Ltd is to promote capacity of our
customers. We cordially welcome any form of cooperation.
The founder of VisionOnSky Co., Ltd (VisionOnSky.com) is Dr. Jinghui Yang. Formerly he was a postdoc at German Aerospace
Center (DLR) and an associate professor at Institute of Photogrammetry and
Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), China. He
received PhD degree at Wuhan University, master degree at Northeastern
University, and bachelor degree at Northeastern University in 2014, 2005 and
2002, respectively. Dr. Jinghui Yang has more than 18
years’ experiences in the scientific research and software development of
automatic and high performance processing for photogrammetry and remote
sensing, image fusion. He published more than 20 scientific papers in some
premier journals of this field, such as Photogrammetric Engineering& Remote
Sensing, International Journal of Remote Sensing, Remote Sensing, Acta Geodaetica et Cartographica Sinica, the Journal of Geomatics
and Information Science of Wuhan University. In 2009, he won Chinese National
Science and Technology Progress Award because of the participation of development
of remote sensing software.
In 2017, Dr. Jinghui Yang left academic institute and founded a startup
company in order to promote technical innovation and accelerate industrial
applications of cutting-edge technology. The founded startup, namely VisionOnSky Co., Ltd., is concentrating on the development
of state-of-the-art technology, software realization of the new techniques and
industrial applications.
Published papers
by the founder in recent years:
1.
Yang
Jinghui*, and Zhang Jixian.
Parallel Performance of Typical Algorithms in Remote Sensing based Mapping on a
Multi-core Computer [J]. Photogrammetric Engineering & Remote Sensing.
2015, 81(5): 373-385. DOI: 10.14358/PERS.81.5.373
2.
Yang
J H*, Zhang J X, Huang G M. A Parallel Computing Paradigm for Pan-Sharpening
Algorithms of Remotely Sensed Images on a Multi-Core Computer [J]. Remote
Sensing. 2014, 6(7): 6039-6063. DOI:10.3390/rs6076039
3.
Yang
J H*, Zhang J X. Pansharpening: From a Generalized
Model Perspective [J]. International Journal of Image and Data Fusion. 2014,
5(4): 285-299.
4.
Zhang
J X, Yang J H*, Zhao Z, et al. Block-Regression-based Fusion of Optical and SAR
Imagery for Feature Enhancement [J]. International Journal of Remote Sensing.
2010, 31(9): 2325-2345.
5.
YANG
Jinghui*. The Generalized Model and Parallel
Computing Methods for Pixel-level Remote Sensing Image Fusion [J]. Acta Geodaetica et Cartographica Sinaca, 2015,
44(8): 943-943 [杨景辉*. 遥感影像像素级融合通用模型及其并行计算方法[J]. 测绘学报, 2015, 44(8): 943-943.]
6.
Yang
J H*, Cheng C Q, Zhang J X, Huang G M. GPU supported massively parallel
processing for geometric correction of SAR imagery [J]. Journal of Image and
Graphics, 2015, 20(3): 374-385. DOI: 10.11834/jig.20150309 [杨景辉*, 程春泉, 张继贤, 黄国满. GPU支持的SAR影像几何校正大规模并行处理[J]. 中国图象图形学报, 2015, 20(3):
374-385. ]
7.
YANG
Jinghui*, ZHANG Jixian. The
parallel decorrelation stretching with multiple
decomposition tactics for remotely sensed imagery [J]. Geomatics
and Information Science of Wuhan University, 2016,41(3): 402-407. [杨景辉*, 张继贤, 结合多种分解策略的遥感影像去相关拉伸并行处理方法[J]. 武汉大学学报信息科学版, 2016,41(3): 402-407 ]
8.
YANG
Jinghui*, ZHANG Jixian.
GPU-based acceleration for pansharpening algorithms
and performance analysis [J]. Journal of Chinese Computer Systems, 2016, 37
(3): 603-607. [杨景辉*, 张继贤. 遥感影像融合的GPU加速及性能分析[J]. 小型微型计算机系统, 2016, 37 (3): 603-607 ]
9.
J.
X. Zhang, J. H. Yang*, P. Reinartz. The Optimized
Block-Regression-based Fusion Algorithm for Pansharpening
of Very High Resolution Satellite Imagery, The International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B7,
2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic, pp.739 –
746
10.
Yang
Jinghui*, Zhang Jixian，“A Parallel Implementation
Framework for Remotely Sensed Image Fusion,” ISPRS Annals of the
Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume I-7,
pp.329-334, 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne,
Australia.
11.
Yang
Jinghui*, Zhang Jixian, et
al, Pixel Level Fusion Methods for Remote Sensing Images: A Current Review,
ISPRS Technical Commission VII Symposium, Vienna, Austria, July 2010
12.
Yang
Jinghui*, Zhang Jixian, and
Li Haitao. Generalized Model for Remotely Sensed Data
Pixel-level Fusion and its Implementation Technology [J]. Journal of Image and
Graphics, 2009, 14(4): 604-614. [杨景辉*, 张继贤, 李海涛. 遥感数据像素级融合统一模型及实现技术[J]. 中国图象图形学报, 2009, 14(4):
604-614. ]
13.
Yang
Jinghui* (2012). The Parallel Processing Framework
for Remotely Sensed Imagery. In Shan J, Zhang J (Eds.), Proceedings of the 18th
China Symposium on Remote Sensing, pp. 8-12, Wuhan, China. [杨景辉*. 遥感影像算法级并行处理框架. 单杰, 张继贤主编, 第十八届中国遥感大会论文集, 科学出版社, pp. 8-12, 2012年10月, 会议地点: 湖北, 武汉. ]
14.
YANG
Jinghui*, AI Haibin, ZHANG
Li (2011). Emergency Response Oriented Processing Flow of Remotely Sensed
Imagery and Applications. A symposium on emergency response and risk management
using surveying and mapping, Tianjin, China. [杨景辉*, 艾海滨, 张
力. 面向应急响应的遥感影像处理流程及应用, 第十三届中国科协年会第12学术交流分会—测绘服务灾害与应急管理学术研讨会, 2011年9月, 会议地点: 天津. ]
15.
Yang
Jinghui*, Li Haitao. High
performance computing techniques for remotely sensed imagery. In Advances of
earth-observed data processing and analysis, Gong Jianya,
Ed., Wuhan University press, Wuhan, China, 2007, pp.136-148. [杨景辉*, 李海涛. 遥感影像高性能处理方法. 龚健雅主编，对地观测数据处理与分析研究进展，武汉: 武汉大学出版社, 2007, pp.136-148. ]
16.
Zhang
Jixian, Yang Jinghui*, “Satellite
data fusion techniques”, a chapter of the book, Advanced Remote Sensing:
Terrestrial Information Extraction and Applications, Edited by Liang Shunlin et al, Elsevier, 2012, pp.91-110
17.
Zhang
J X, Yang J H*, Li H T, et al. Generalized Model for Remotely Sensed Data
Pixel-Level Fusion, The International Archives of the Photogrammetry, Remote
Sensing and Spatial Information Sciences, Beijing, China, 2008, Vol. XXXVII,
Part B7: 1051-1056.
18.
Shao
Long, Yang Jinghui, and Hong Youtang.
Segmentation for remote sensing image based on heterogeneity and watershed
transformation [J]. Science of Surveying and Mapping, 2014, 39(3): 19-22. [邵龙, 杨景辉, 洪友堂. 结合异质性及分水岭变换的遥感影像分割方法[J]. 测绘科学, 2014, 39(3): 19-22. ]
19.
Pan
Yuan, Yang Jinghui, Wu Wenbo.
Neural network based on rough sets reduction and its application to remote
sensing image classification [J]. Remote Sensing Information, 2012, 27(4):
86-90. DOI: 10.3969/j.issn.1000-3177.2012.04.015 [潘远, 杨景辉, 武文波. 粗糙集约简的神经网络遥感分类应用[J]. 遥感信息, 2012, 27(4): 86-90. ]
20.
Li
Haitao, Shi Yuanli, Yang Jinghui, and Han Yanshun (2009).
A cluster-based parallel processing system for HJ-1 satellites data. Proc. SPIE
7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and
Optimization Techniques, 749714 (October 30, 2009). DOI:10.1117/12.833224
21.
Jia Weijie,
Zhang Jixian, and Yang Jinghui
(2009). Automatic registration of SAR and optics image based on multi-features
on suburban areas. Urban Remote Sensing Event, 2009 Joint, pp.1-7, 20-22 May
2009. DOI: 10.1109/URS.2009.5137610
(*:
Corresponding author)