Abstract
This work has as main objective to overcome a frequent problem in remote sensing, which is the undesirable presence of atmospheric constituents as scattered clouds, fogs and mists. The presence of such elements can affect the urban and environmental monitoring, as well as subsequent steps of the digital image processing such as segmentation and classification, main responsible for extracting information of the image. Therefore, is presented a technique to detect these elements, which uses statistical measures and morphological filters. To the removal or smoothing these atmospheric elements is applied a homomorphic filter. Motivating the present work, is presented a comparative analysis of the widely used high-pass filters in homomorphic filtering, Ideal and Butterworth, with the alternative High-boost filter. The results are evaluated by the Kappa coefficient and PSNR index, pointing to the High-boost filter as the best approach to use.
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References
Delac, K., Grgic, M., Kos, T.: Sub-image Homomorphic filtering technique for improving facial identification under dificult illumination conditions. In: International Conference on Systems, Signals and Image Processing, pp. 95–98 (2006)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley Publishing Company (2008)
Hau, C.Y., Liu, C.H., Chou, T.Y., Yang, L.S.: The efficacy of semi-automatic classification result by using different cloud detection and diminution method. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2008)
Kekre, H.B., Athawale, A., Halarnkar, P.N.: High payload using High Boost filtering in Kekre’s Multiple LSB’s algorithm. In: 2nd International Conference on Advances in Computer Vision and Information Technology (2009)
Grgic, M., Delac, K.: Handbook Of Data Compression. Springer, Heidelberg (2009)
Ma, J., Gu, X., Feng, C., Guo, J.: Study of thin cloud removal method for CBERS-02 image. Science in China Series E 48 2(2005-03), 72–90 (2005)
Salomon, D., Motta, G.: Handbook Of Data Compression. Springer, Heidelberg (2009)
Seow, M., Asari, V.: Ratio rule and homomorphic filter for enhancement of digital colour image. Proceedings of Neurocomputing, 954–958 (2006)
Tasdizen, T., Whitaker, R., Burchard, P., Osher, S.: Geometric surface processing via normal maps. Proceedings of ACM Trans. Graph, 1012–1033 (2003)
Zhang, X., Qin, F., Qin, Y.: Study on the thick cloud removal method based on multi-temporal remote sensing images. In: International Conference on Multimedia Technology (ICMT), pp. 1–3 (2010)
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Sousa, D., Siravenha, A.C., Pelaes, E. (2011). Comparing Different High-Pass Filters to Improve the Accuracy of Classification of Satellite Imagery Obstructed by Clouds and Fog. In: Kim, Th., Adeli, H., Ramos, C., Kang, BH. (eds) Signal Processing, Image Processing and Pattern Recognition. SIP 2011. Communications in Computer and Information Science, vol 260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27183-0_8
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DOI: https://doi.org/10.1007/978-3-642-27183-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27182-3
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