By Shen-en Qian

ISBN-10: 0819497878

ISBN-13: 9780819497871

This ebook presents a world evaluation of optical satellite tv for pc picture and information compression theories, algorithms, and approach implementations. together with 9 chapters, it describes various lossless and near-lossless data-compression suggestions and 3 overseas satellite-data-compression criteria. the writer stocks his firsthand event and study ends up in constructing novel satellite-data-compression innovations for either onboard and on-ground use, person checks of the influence that info compression has on satellite tv for pc information functions, development compression structures, and optimizing and deploying platforms. Written with either postgraduate scholars and complicated execs in brain, this guide addresses vital problems with satellite tv for pc information compression and implementation, and it offers an end-to-end therapy of knowledge compression know-how.

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Wang, Z. and A. C. Bovik, “A universal image quality index,” IEEE Signal Process. Lett. 9(3), 81–84 (2002). 10. , A. C. Bovik, and L. ” Proc. IEEE Int. Conf. , Speech, Signal Process. 4, 3313–3316 (2002). 11. , A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13(4), 600–612 (2004). 12. Sheikh, H. , M. F. Sabir, and A. C. Bovik, “A statistical evaluation of recent full reference image quality assessment algorithms,” IEEE Trans.

Science & Information Theory, Dover Publications (2004). 38. Shannon, C. , “A Mathematical Theory of Communication,” Bell System Technical Journal 27(3), 379–423 (1948). 39. , Audio Coding: Theories and Applications, Springer, Berlin (2010). 40. , Morgan Kaufmann Publishers, San Francisco, CA (2000). 41. Jayant, N. S. and P. Noll, Digital Coding of Waveforms – Principles and Applications to Speech and Video, Prentice Hall, New York (1984). 42. Wu, H. R. and M. Yuen, “A generalized block-edge impairment metric for video coding,” IEEE Signal Process.

It is important to assess the quality after compression. Image quality criteria or distortion measures need to be defined to properly quantify the information lost due to data compression. Quality metrics can be used to ensure that no critical information has been lost during the compression process and that the scientific value of the original data is well preserved. Image quality metrics can be classified into three categories based on the reference used: 1. Full-reference (FR) metrics, 2. Reduced-reference (RR) metrics, and 3.

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Optical Satellite Data Compression and Implementation by Shen-en Qian


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