A Complete Processing Chain for Shadow Detection and Reconstruction in VHR Images

The presence of shadows in very high resolution (VHR) images can represent a serious obstacle for their full exploitation. This paper proposes to face this problem as a whole through the proposal of a complete processing chain, which relies on various advanced image processing and pattern recognition tools. The first key point of the chain is that shadow areas are not only detected but also classified to allow their customized compensation. The detection and classification tasks are implemented by means of the state-of-the-art support vector machine approach. A quality check mechanism is integrated in order to reduce subsequent misreconstruction problems. The reconstruction is based on a linear regression method to compensate shadow regions by adjusting the intensities of the shaded pixels according to the statistical characteristics of the corresponding nonshadow regions. Moreover, borders are explicitly handled by making use of adaptive morphological filters and linear interpolation for the prevention of possible border artifacts in the reconstructed image. Experimental results obtained on three VHR images representing different shadow conditions are reported, discussed, and compared with two other reconstruction techniques.

[1]  Yoshifumi Yasuoka,et al.  Simulated recovery of information in shadow areas on IKONOS image by combing ALS data , 2002 .

[2]  Reena Singh,et al.  Comparison of Daubechies, Coiflet, and Symlet for edge detection , 1997, Defense, Security, and Sensing.

[3]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[4]  Taejung Kim,et al.  Semiautomatic reconstruction of building height and footprints from single satellite images , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[5]  Kuo-Liang Chung,et al.  Efficient Shadow Detection of Color Aerial Images Based on Successive Thresholding Scheme , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[6]  P. Dare.  Shadow Analysis in High-Resolution Satellite Imagery of Urban Areas , 2005 .

[7]  Qiming Qin,et al.  Shadow Segmentation and Compensation in High Resolution Satellite Images , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[8]  Fang Tao.  Color Property Analysis of Remote Sensing Imagery , 2009 .

[9]  Dong-Chen He,et al.  Detecting information under and from shadow in panchromatic Ikonos images of the city of Sherbrooke , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[10]  Jon Atli Benediktsson,et al.  Classification and feature extraction for remote sensing images from urban areas based on morphological transformations , 2003, IEEE Trans. Geosci. Remote. Sens..

[11]  Farid Melgani,et al.  Genetic SVM Approach to Semisupervised Multitemporal Classification , 2008, IEEE Geoscience and Remote Sensing Letters.

[12]  Pierre Soille,et al.  Morphological Image Analysis , 1999 .

[13]  Shugen Wang,et al.  Shadow Detection and Compensation in High Resolution Satellite Image Based on Retinex , 2009, 2009 Fifth International Conference on Image and Graphics.

[14]  Pierre Soille,et al.  Advances in mathematical morphology applied to geoscience and remote sensing , 2002, IEEE Trans. Geosci. Remote. Sens..

[15]  Peter Reinartz,et al.  Adaptive Shadow Detection Using a Blackbody Radiator Model , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Pramod K. Varshney,et al.  An Optimum Land Cover Mapping Algorithm in the Presence of Shadows , 2011, IEEE Journal of Selected Topics in Signal Processing.

[17]  Fumio Yamazaki,et al.  Characteristics of Tsunami-Affected Areas in Moderate-Resolution Satellite Images , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Juan Su,et al.  An automatic shadowdetection and compensation method for remote sensed color images , 2006, 2006 8th international Conference on Signal Processing.

[19]  Grégoire Mercier,et al.  Preprocessing of Low-Resolution Time Series Contaminated by Clouds and Shadows , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Hai-Yan Yu,et al.  MSER based shadow detection in high resolution remote sensing image , 2010, 2010 International Conference on Machine Learning and Cybernetics.

[21]  Sabine Süsstrunk,et al.  Optimization for Hue Constant RGB Sensors , 2002, CIC.

[22]  Victor J. D. Tsai,et al.  A comparative study on shadow compensation of color aerial images in invariant color models , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[23]  Wei Wei,et al.  Study on shadow detection method on high resolution remote sensing image based on HIS space transformation and NDVI index , 2010, 2010 18th International Conference on Geoinformatics.

[24]  Xinhua Zhuang,et al.  Image Analysis Using Mathematical Morphology , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Umesh Ghanekar,et al.  An Efficient Morphological Salt-and-Pepper Noise Detector , 2011 .

[26]  Walter A. Hendricks,et al.  The Sampling Distribution of the Coefficient of Variation , 1936 .

[27]  A. Bachelor.  GLOSSARY OF TERMS GLOSSARY OF TERMS , 2010 .

[28]  Touradj Ebrahimi,et al.  Shadow identification and classification using invariant color models , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[29]  Wen Liu,et al.  Characteristics of shadow and removal of its effects for remote sensing imagery , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.

[30]  Farid Melgani,et al.  Automatic Analysis of GPR Images: A Pattern-Recognition Approach , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Jocelyn Chanussot,et al.  Support Vector Reduction in SVM Algorithm for Abrupt Change Detection in Remote Sensing , 2009, IEEE Geoscience and Remote Sensing Letters.

[32]  Pooya Sarabandi,et al.  Shadow detection and radiometric restoration in satellite high resolution images , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[33]  Farid Melgani,et al.  Contextual Spatiospectral Postreconstruction of Cloud-Contaminated Images , 2008, IEEE Geoscience and Remote Sensing Letters.