Abstract
In the paper is presented a new method for compression of multispectral images, based on the Inverse Difference Pyramid decomposition. The method is applicable for any number of multispectral images of same object. The processing is performed as follows. First, the histograms of the multispectral images are calculated and compared. The image, whose histogram is most similar with these of the remaining ones, is chosen to be a reference one. The image decomposition starts with the reference image, which is processed with some kind of orthogonal transform, using a limited number of transform coefficients only. With the so obtained coefficients values is calculated the coarse approximation of the processed image. The IDP decomposition then branches out into several directions, corresponding to the number of multispectral images. The first approximation for all multispectral images is that of the reference image. Each branch is developed individually, using the same approximation. In result of this processing is obtained high compression and very good visual quality of the restored images. This approach gives better results than these, obtained with methods, based on the JPEG and JPEG 2000 standards.
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References
Gelli, G., Poggi, G.: Compression of multispectral images by spectral classification and transform coding. IEEE Trans. Image Process. 8(4), 476–489 (1999)
Dragotti, P., Poggi, G., Ragozini, A.: Compression of multispectral images by three-dimensional SPIHT algorithm. IEEE Trans. Geosci. Remote Sens. 38(1), 416–428 (2000)
Fowler, J., Fox, D.: Embedded wavelet-based coding of 3D oceanographic images with land masses. IEEE Trans. Geosci. Remote Sens. 39(2), 284–290 (2001)
Tang, X., Pearlman, W., Modestino, J.: Hyperspectral image compression using three-dimensional wavelet coding. In: Proc. SPIE, vol. 5022, pp. 1037–1047 (2003)
Cagnazzo, M., Poggi, G., Verdoliva, L., Zinicola, A.: Region-oriented compression of multispectral images by shape-adaptive wavelet transform and SPIHT. In: Proc. IEEE Int. Conf. Image Process, pp. 2459–2462 (2004)
Gersho, A., Gray, R.: Vector quantization and signal compression. Kluwer AP, Dordrecht (1992)
Kaarna, A.: Integer PCA and wavelet transform for lossless compression of multispectral images. In: Proc. of IGARSS 2001, pp. 1853–1855 (2001)
Markas, T., Reif, J.: Multispectral image compression algorithms. In: Storer, J., Cohn, M. (eds.), pp. 391–400. IEEE Computer Society Press, Los Alamitos (1993)
Aiazzi, B., Baronti, S., Lastri, C.: Remote-Sensing Image Coding. In: Barni, M. (ed.) Document and Image Compression, ch. 15. CRC Taylor&Francis (2006)
Cagnazzo, M., Parrilli, S., Poggi, G., Verdoliva, L.: Improved Class-Based Coding of Multispectral Images With Shape-Adaptive Wavelet Transform. IEEE Geoscience and Remote Sensing Letters 4(4), 565–570 (2007)
Wu, J., Wu, C.: Multispectral image compression using 3-dimensional transform zeroblock coding. Chinese Optic Letters 2(6), 1–4 (2004)
Kountchev, R., Kountcheva, R.: Image Representation with Reduced Spectrum Pyramid. In: Tsihrintzis, G., Virvou, M., Howlett, R., Jain, L. (eds.) New Directions in Intelligent Interactive Multimedia, pp. 275–284. Springer, Heidelberg (2008)
Bronshtein, I., Semendyayev, K., Musiol, G., Muehlig, H.: Handbook of Mathematics, 5th edn. Springer, Heidelberg (2007)
Kountchev, R., Todorov, V., Kountcheva, R.: Multi-view Object Representation with Inverse Difference Pyramid Decomposition. WSEAS Trans. on Signal Processing 5(9), 315–325 (2009)
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Kountchev, R., Nakamatsu, K. (2010). Compression of Multispectral Images with Inverse Pyramid Decomposition . In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15393-8_25
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DOI: https://doi.org/10.1007/978-3-642-15393-8_25
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