Remote sensing image fusion based on fuzzy theory in pixel level and assessing the quality of resulting images

Zhongyong Xiao; Hong Jiang; Huiping Zhou; Shuquan Yu

doi:10.1117/12.760455

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8 August 2007 Remote sensing image fusion based on fuzzy theory in pixel level and assessing the quality of resulting images

Zhongyong Xiao, Hong Jiang, Huiping Zhou, Shuquan Yu

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Proceedings Volume 6752, Geoinformatics 2007: Remotely Sensed Data and Information; 67520P (2007) https://doi.org/10.1117/12.760455
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

The technology of image fusion now has been used in the process of remote sensing data. It can integrate the information from multi-sensor data so as to complement the shortage of single sensor image, then more suitable for the purpose of human visual perception, computer-aided object detection, and target recognition. Currently, there are many methods of image fusion we can get from other researcher's study, but these methods of image fusion have some disadvantages. This paper presented the approach of image fusion in pixel level with the fuzzy theory, the source of data used in this paper come from QuickBird image, the resolutions of multi-spectral with four bands and panchromatic image are 2.44m and 0.61m respectively. The process of image fusion is implemented mainly in the fuzzy tool of Matlab. Lastly, assessing the quality of resulting images and these methods of evaluation is based on visually and statistically. The findings that the fused image has remained the attributes of multi-spectral image and high resolution image with 0.61m instead of 2.44m. It is indicated that the fused image is finer than the original multi-spectral image. So the approach of this paper has presented could be a good method to process remote sensing image fusion.

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Zhongyong Xiao, Hong Jiang, Huiping Zhou, and Shuquan Yu "Remote sensing image fusion based on fuzzy theory in pixel level and assessing the quality of resulting images", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520P (8 August 2007); https://doi.org/10.1117/12.760455

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