Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 103-108, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W4-103-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
26 Jun 2015
A color balancing method for wide range Remote Sensing imagery based on Regionalization
J. Liu, H. T. Li, and H. Y. Gu Key Laboratory of Geo-informatics of National Administration of Surveying, Mapping and Geoinformation, Chinese Academy of Surveying and Mapping, Beijing 100830, China
Keywords: Color balance, Regionalization, Wide range, Image mosaic Abstract. Quick mosaicking of wide range remote sensing imagery is an important foundation for land resource survey and dynamic monitoring of environment and nature disasters. It is also technically important for basis imagery of geographic information acquiring and geographic information product updating. This paper mainly focuses on one key technique of mosaicking, color balancing for wide range Remote Sensing imagery. Due to huge amount of data, large covering rage, great variety of climate and geographical condition, color balancing for wide range remote sensing imagery is a difficult problem. In this paper we use Ecogeographic regionalization to divide the large area into several regions based on terrains and climatic data, construct the algorithmic framework of a color balancing method according to the regionalization result, which conduct from region edge to center to fit wide range imagery mosaicking. The experimental results with wide range HJ-1 dataset show that our method can significantly improve the wide range of remote sensing imagery color balancing effects: making images well-proportioned mosaicking and better in keeping images' original information. In summary, this color balancing method based on regionalization could be a good solution for nationwide remote sensing image color balancing and mosaicking.
Conference paper (PDF, 1155 KB)


Citation: Liu, J., Li, H. T., and Gu, H. Y.: A color balancing method for wide range Remote Sensing imagery based on Regionalization, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 103-108, https://doi.org/10.5194/isprsarchives-XL-7-W4-103-2015, 2015.

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