An Adaptive Nonlocal Regularized Shadow Removal Method for Aerial Remote Sensing Images

• Published in: IEEE transactions on geoscience and remote sensing Vol. 52; no. 1; pp. 106 - 120
• Main Authors: Li, Huifang, Zhang, Liangpei, Shen, Huanfeng
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Aerial images; Applied geophysics; Compounds; Digital photography; Earth sciences; Earth, ocean, space; Exact sciences and technology; Image color analysis; Image edge detection; Image reconstruction; Internal geophysics; Land surface; nonlocal (NL) operators; Remote sensing; Sensors; shadow removal; soft shadow; spatially adaptive; detection; color; aerial photography; textures; spatially adaptive; remote sensing; classification; shadow removal; nonlocal (NL) operators; currents; airborne methods; Aerial images; interpretation; imagery; soft shadow; high resolution
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2012.2236562

Shadows are evident in most aerial images with high resolutions, particularly in urban scenes, and their existence obstructs the image interpretation and the following application, such as classification and target detection. Most current shadow removal methods were proposed for natural images, whereas shadows in remote sensing images show distinct characteristics. We have therefore analyzed the characteristics of shadows in aerial images, and in this paper, we propose a new shadow removal method for aerial images, using nonlocal (NL) operators. In the proposed method, the soft shadow is introduced to replace the traditional binary hard shadow. NL operators are used to regularize the shadow scale and the updated shadow-free image. Furthermore, a spatially adaptive NL regularization is introduced to handle compound shadows. The combination of the soft shadow and NL operators yields satisfying shadow-free results, preserving textures and holding regular color. Different types of shadowed aerial images are employed to verify the proposed method, and the results are compared with two other methods. The experimental results confirm the validity of the proposed method and the advantage of the soft-shadow approach.