A Cloud Removal Algorithm to Generate Cloud and Cloud Shadow Free Images Using Information Cloning
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One of the main problems of optical remote sensing is clouds and cloud shadows caused by specific atmospheric conditions during data acquisition. These features limit the usage of acquired images and increase the difficulty in data analysis, such as normalized difference vegetation index values, misclassification, and atmospheric correction. Accurate detection and reliable cloning of cloud and cloud shadow features in satellite images are very useful processes for optical remote sensing applications. In this study, an automated cloud removal algorithm to generate cloud and cloud shadow free images from multitemporal Landsat-8 images is introduced. Cloud and cloud shadow areas are classified by using process-based rule set developed by using spectral and spatial features after applying simple linear iterative clustering superpixel segmentation algorithm to the image to find cloud pixel groups easily and correctly. Segmentation-based cloud detection method gives better results than pixel-based for detection of cloud and cloud shadow patches. After detection of clouds and cloud shadows, cloud-free images are created by cloning cloudless regions from multitemporal dataset. Spectral and structural consistency are preserved by considering spectral features and seasonal effects while cloning process. Statistical similarity tests are applied to find best cloud-free image to use for cloning process. Cloning results are tested with the structural similarity index metric to evaluate the performance of cloning algorithm.
KeywordsLandsat 8 Cloud Cloud shadow Cloud determination Cloning Information reconstruction Flood Fill
- Chun, F., Jian-wen, M., Qin, D., & Xue, C. (2004). An improved method for cloud removal in ASTER data change detection. In Proceedings of IEEE international geoscience and remote sensing symposium, 2004. IGARSS’04, IEEE (Vol. 5, pp. 3387–3389).Google Scholar
- Gundersen, E. (2013). Cloudless Atlas with Landsat. https://www.mapbox.com/blog/cloudless-atlas-with-landsat/. Accessed 4 Nov 2016.
- Hancher, M. (2016). Only clear skies on Google Maps and Earth. Google Official. https://googleblog.blogspot.com.tr/2013/06/only-clear-skies-on-google-maps-and.html. Accessed 6 June 2014.
- Irish, R. R. (2000). Landsat 7 automatic cloud cover assessment. In Proceedings of SPIE—The international society for optical engineering (p. 348).Google Scholar
- Jiao, Q., Luo, W., Liu, X., & Zhang, B. (2007). Information reconstruction in the cloud removing area based on multi-temporal CHRIS images. In Y. Wang, J. Li, B. Lei, & J. Yang (Eds.), Proceedings of SPIE, MIPPR 2007: Remote sensing and GIS data processing and applications; and innovative multispectral technology and applications, International Symposium on Multispectral Image Processing and Pattern Recognition, 2007. (Vol. 6790, p. 679029). Wuhan, China: SPIE. https://doi.org/10.1117/12.750462.
- Kalkan, K., & Maktav, D. (2016). Segmentation based cloud and cloud shadow detection in satellite imagery. Journal of Aeronautics and Space Technologies, 10(1), 45–54.Google Scholar
- Loyd, C. (2012). Cloudless atlas. https://www.flickr.com/photos/vruba/. Accessed 2 Nov 2016.
- MathWorks, I. (2014). Corr2, 2-D correlation coefficient. MATLAB Image Processing Toolbox. http://www.mathworks.com/help/images/ref/corr2.html. Accessed 2 Nov 2016.
- USGS. (2004). SLC-off gap-filled products gap-fill algorithm methodology. http://landsat.usgs.gov/documents/L7SLCGapFilledMethod.pdf. Accessed 4 Nov 2016.
- Wang, Z., Jin, J., Liang, J., Yan, K., & Peng, Q. (2005). A new cloud removal algorithm for multi-spectral images. In L. Zhang, J. Zhang, & M. Liao (Eds.), Proceedings of SPIE, MIPPR 2005: SAR and multispectral image processing (vol. 6043, p. 60430W). Wuhan, China: SPIE. https://doi.org/10.1117/12.654869.
- Wang, B., Ono, A., Muramatsu, K., Fujiwara, N., Bin, W., Atsuo, O. N. O., et al. (1999). Automated detection and removal of clouds and their shadows from Landsat TM images. IEICE Transactions on Information and Systems, 82(2), 453–460.Google Scholar
- Zhang, X., Qin, F., & Qin, Y. (2010). Study on the thick cloud removal method based on multi-temporal remote sensing images. In 2010 international conference on multimedia technology, IEEE (pp. 1–3).Google Scholar