Practical method of shadow detection and removal for high spatial resolution remote sensing image

Ru Li; Bing Zhang; Xia Zhang; Zhengchao Chen; Zheng Wei; Lanfen Zheng

doi:10.1117/12.746579

14 November 2007 Practical method of shadow detection and removal for high spatial resolution remote sensing image

Ru Li, Bing Zhang, Xia Zhang, Zhengchao Chen, Zheng Wei, Lanfen Zheng

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67900Q (2007) https://doi.org/10.1117/12.746579
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

High spatial resolution remote sensing image (HSRRSI) has received a warm welcome in many fields. However, building shadows of large area on HSRRSI (up to 30% in some cases) are one of the biggest hindrances for further applications in many fields. To keep a balance between precision and efficiency required by applications during shadow removal, this paper introduces a creative and practical strategy based on the theory of the pulse coupled neural network (PCNN). By applying the simplified model of PCNN, shadows on HSRRSI had been detected and removed respectively. When applied to HSRRSI, the method could not only remove the shadows, but also keep the contrast between removed areas with shadows and other areas without shadows from being too big, which might distort the image. Therefore the satisfactory result is gained.

Citation Download Citation

Ru Li, Bing Zhang, Xia Zhang, Zhengchao Chen, Zheng Wei, and Lanfen Zheng "Practical method of shadow detection and removal for high spatial resolution remote sensing image", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67900Q (14 November 2007); https://doi.org/10.1117/12.746579

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available