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Pattern Recognition and Image Analysis

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01.01.2020 | APPLIED PROBLEMS

An Invalid Cloud Region Masking Method for Remote Sensing Image Compression

verfasst von: Huaichao Wang, Hai Zhou, Jing Wang

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 1/2020

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Abstract

An invalid cloud region masking method based on local edge context is proposed for the compression of remote sensing images. Through analyzing the characteristics of various compression algorithms and taking the local edge information of the cloud region into account, the decompression quality is improved. First, according to the cloud mask information, labeling the connected cloud region, second, performing region growth on the labeled mask image, then differing the two mask images to obtain the local edge context, and finally different invalid cloud regions are filled with the average of the respective local edge context pixels. Using the image testing set generated from QuickBird and OrbView images, our method’s impact on six common remote sensing image compression algorithms is analyzed experimentally. The experimental results show that our masking method can improve the decompressed image quality when the compression ratio is certain. When the image quality is fixed, it can further reduce the compressed bitrate. For onboard application, our masking method can increase the onboard imaging time of the satellites, and eventually improve the onboard specifications of remote sensing satellites.

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Y. Wang and L. Xing, “Remote sensing satellite networking technology and remote sensing system: A survey,” in Proc. 2015 12th IEEE Int. Conf. on Electronic Measurement & Instruments (ICEMI’2015) (Qingdao, China, 2015), IEEE, Vol. 3, pp. 1251–1256. https://doi.org/10.1109/ICEMI.2015.7494508

L. Thakar, C. Dutta, P. S. Sura, and S. Udupa, “Design & realization of multi mission data handling system for remote sensing satellite,” in Proc. 2016 Int. Conf. on Advances in Computing, Communications and Informatics (ICACCI) (Jaipur, India, 2016), IEEE, pp. 967–972. https://doi.org/10.1109/ICACCI.2016.7732170

B. Kucherov, O. Přibyl, and V. Artyushenko, “Increasing efficiency of getting results of satellite remote sensing for smart cities,” in Proc. 2017 Smart City Symposium Prague (SCSP) (Prague, Czech Republic, 2017), IEEE, Paper ID 43, pp. 1–6. https://doi.org/10.1109/SCSP.2017.7973854

J. E. Fowler, “Shape-adaptive coding using binary set splitting with k-d trees,” in Proc. 2004 Int. Conf. on Image Processing (ICIP 2004) (Singapore, 2004), IEEE, Vol. 2, pp. 1301–1304. https://doi.org/10.1109/ICIP.2004.1419737

J. Hua, Z. Liu, Z. Xiong, Q. Wu, and K. Castleman, “Microarray BASICA: Background adjustment, segmentation, image compression and analysis of microarray images,” in Proc. 2003 Int. Conf. on Image Processing (ICIP 2003) (Barcelona, Spain, 2003), IEEE, Vol. 1, pp. I-585–I-588. https://doi.org/10.1109/ICIP.2003.1247029

D. Taubman, “High performance scalable image compression with EBCOT,” IEEE Trans. Image Process. 9 (7), 1158–1170 (2000). https://doi.org/10.1109/83.847830 CrossRef

M. Cagnazzo, G. Poggi, L. Verdoliva, and A. Zinicola, “Region-oriented compression of multispectral images by shape-adaptive wavelet transform and SPIHT,” in Proc. 2004 Int. Conf. on Image Processing (ICIP 2004) (Singapore, 2004), IEEE, Vol. 4, pp. 2459–2462. https://doi.org/10.1109/ICIP.2004.1421600

P.-S. Yeh, P. Armbruster, A. Kiely, B. Masschelein, G. Moury, C. Schaefer, and C. Thiebaut, “The new CCSDS image compression recommendation,” in Proc. 2005 IEEE Aerospace Conference (Big Sky, MT, USA, 2005), IEEE, pp. 4138–4145. https://doi.org/10.1109/AERO.2005.1559719

A. Hagag, X. Fan, and F. E. Abd El-Samie, “Lossy compression of satellite images with low impact on vegetation features,” Multidim. Syst. Signal Process. 28 (4), 1717–1736 (2017). https://doi.org/10.1007/s11045-016-0443-y CrossRef

10.

Z. Liu, J. Hua, Z. Xiong, Q. Wu, and K. Castleman, “Lossy-to-lossless ROI coding of chromosome images using modified SPIHT and EBCOT,” in Proc. 2002 IEEE International Symposium on Biomedical Imaging (Washington, DC, USA, 2002), IEEE, pp. 317–320. https://doi.org/10.1109/ISBI.2002.1029257

11.

P. Jangbari and D. Patel, “Review on region of interest coding techniques for medical image compression,” Int. J. Comput. Appl. 134 (10), 1–5 (2016). https://doi.org/10.5120/ijca2016907859 CrossRef

12.

H. Shen, W. D. Pan, and D. Wu, “Predictive lossless compression of regions of interest in hyperspectral images with no-data regions,” IEEE Trans. Geosci. Remote Sens. 55 (1), 173–182 (2017). https://doi.org/10.1109/TGRS.2016.2603527 CrossRef

13.

J. González-Conejero, J. Serra-Sagristà, C. Rubies-Feijoo, and L. Donoso-Bach, “Encoding of images containing no-data regions within JPEG2000 framework,” in Proc. 2008 15th IEEE Int. Conf. on Image Processing (ICIP 2008) (San Diego, CA, USA, 2008), pp. 1057–1060. https://doi.org/10.1109/ICIP.2008.4711940

14.

J. González-Conejero, J. Bartrina-Rapesta, and J. Serra-Sagristà, “JPEG2000 encoding of remote sensing multispectral images with no-data regions,” IEEE Geosci. Remote Sens. Lett. 7 (2), 251–255 (2010). https://doi.org/10.1109/LGRS.2009.2032370 CrossRef

15.

D. Gupta and S. Choubey, “Discrete wavelet transform for image processing,” Int. J. Emerging Technol. Adv. Eng. 4 (4), 598–602 (2014).

16.

Y. Fisher (Ed.), Fractal Image Compression: Theory and Application (Springer, New York, NY, 1995). https://doi.org/10.1007/978-1-4612-2472-3

17.

A. M. Tekalp, Digital Video Processing, 2nd ed. (Prentice Hall PTR, Upper Saddle River, NJ, 2015).

18.

K. Suzuki, I. Horiba, and N. Sugie, “Linear-time connected-component labeling based on sequential local operations,” Comput. Vision Image Understanding 89 (1), 1–23 (2003). https://doi.org/10.1016/S1077-3142(02)00030-9 CrossRefMATH

19.

L.-F. He, Y.-Y. Chao, and K. Suzuki, “An algorithm for connected-component labeling, hole labeling, and Euler number computing,” J. Comput. Sci. Technol. 28 (3), 468–478 (2013). https://doi.org/10.1007/s11390-013-1348-y MathSciNetCrossRefMATH

20.

L. He, X. Zhao, Y. Chao, and K. Suzuki, “Configuration-transition-based connected-component labeling,” IEEE Trans. Image Process. 23 (2), 943–951 (2014). https://doi.org/10.1109/TIP.2013.2289968 MathSciNetCrossRefMATH

21.

J. Wu and H. Guo, “A method for sonar image segmentation based on combination of MRF and region growing,” in Proc. 2015 Fifth Int. Conf. on Communication Systems and Network Technologies (CSNT 2015) (Gwalior, India, 2015), IEEE, pp. 457–460. https://doi.org/10.1109/CSNT.2015.224

22.

G. Yu, T. Vladimirova, and M. N. Sweeting, “Image compression systems on board satellites,” Acta Astronaut. 64 (9–10), 988–1005 (2009). https://doi.org/10.1016/j.actaastro.2008.12.006 CrossRef

Titel: An Invalid Cloud Region Masking Method for Remote Sensing Image Compression
verfasst von: Huaichao Wang
Hai Zhou
Jing Wang
Publikationsdatum: 01.01.2020
Verlag: Pleiades Publishing
Erschienen in: Pattern Recognition and Image Analysis / Ausgabe 1/2020
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI: https://doi.org/10.1134/S1054661820010162

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