Dr. Huachao Xiao Profile

Dr. Huachao Xiao

at Xi'an Institute of Space Radio Technology

SPIE Involvement:

Author

Publications (2)

Proceedings Article | 7 October 2019 Presentation + Paper

Finer scale mapping with super resolved GF-4 satellite images

Xue Yang, Feng Li, Lei Xin, Nan Zhang, XiaoTian Lu, Huachao Xiao

Proceedings Volume 11155, 111550A (2019) https://doi.org/10.1117/12.2532674

KEYWORDS: Image classification, Remote sensing, Satellite imaging, Image processing, Image registration, Landsat

Read Abstract +

High-resolution (HR) remote sensing images are characterized by rich and detailed ground object information with more complex structures of the ground object which make the interference information is more difficult to process. It has always been the focus of domestic and foreign researchers that how to obtain more accurate and higher quality ground object information from these images. The GF-4, the world's first geostationary orbit with high spatial resolution remote sensing satellite, can provide high temporal resolution, large width and 50m pixel resolution of remote sensing data by using area array imaging technology. However, the GF-4 image is a medium resolution and low resolution (LR) image data with relatively vague details of ground objects and not obvious relationships between objects which limit the acquisition of the ground object information to some extent. Therefore, in this paper, we analyze the influence of various factors in the imaging process and construct an image degradation model according to the characteristics of GF-4 satellite images. We adopted the super resolved (SR) method based on Mixed sparse representations (MSR) to increase the spatial resolution of the GF-4 image by twice as much, which not only enriched the detailed information of the image, but also improved the image quality. For the results of SR of GF-4 imagery, we adopted the Maximum Likelihood Classification (MLC) method to perform image classification test and result verification. The experimental area selected in this paper is Yantai City, Shandong Province, China, the LANDSAT 8 OLI data is used as a training sample to calculate the overall accuracy and Kappa coefficient after classification. The results show that the overall accuracy of the superreconstructed result data is 40% higher than that of the source image data from GF-4, especially when the spectral characteristics of the ground objects are obviously different, the accuracy is more obvious. The Kappa coefficient increased 0.4, the extracted outline is more complete and the classification details are more refined.

Proceedings Article | 8 October 2015 Paper

Aircraft target onboard detecting technology via Circular Information Matching method for remote sensing satellite

Huachao Xiao, Quan Zhou, Li Li

Proceedings Volume 9675, 967507 (2015) https://doi.org/10.1117/12.2196956

KEYWORDS: Target detection, Remote sensing, Image filtering, Image processing, Satellites, Detection and tracking algorithms, Electronic filtering, Signal detection, Satellite imaging, Convolution

Read Abstract +

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years