The Essential Guide To Video Processing by Alan C. Bovik PDF

By Alan C. Bovik

This entire and state-of-the paintings method of video processing offers engineers and scholars a finished creation and comprises complete insurance of key purposes: instant video, video networks, video indexing and retrieval and use of video in speech processing. Containing the entire crucial equipment in video processing along the most recent criteria, it's a entire source for the pro engineer, researcher and graduate student.

  • Numerous conceptual and numerical examples
  • All the newest criteria are completely coated: MPEG-1, MPEG-2, MPEG-4, H.264 and AVC
  • Coverage of the most recent concepts in video security

"Like its sister quantity "The crucial advisor to photo Processing," Professor Bovik’s crucial consultant to Video Processing offers a well timed and entire survey, with contributions from best researchers within the quarter. hugely steered for everybody with an curiosity during this interesting and fast-moving field." ―Prof. Bernd Girod, Stanford college, USA

* Edited via a number one individual within the box who created the IEEE foreign convention on photo Processing, with contributions from specialists of their fields.
* a number of conceptual and numerical examples
*All the newest criteria are completely lined: MPEG-1, MPEG-2, MPEG-4, H.264 and AVC.
* assurance of the newest ideas in video defense

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Vincent, and P. Blanchfield. Hybrid de-interlacing algorithm based on motion vector reliability. IEEE Trans. Circuits Syst. , 15:1019–1025, 2005. [8] G. de Haan. Deinterlacing-an overview. Proc. IEEE, 86:1839–1857, 1998. [9] H. A. Aly and E. Dubois. Image up-sampling using total-variation regularization with a new observation model. IEEE Trans. , 14:1647–1659, 2005. References [10] P. Mertz and F. Gray. A theory of scanning and its relation to the characteristics of the transmitted signal in telephotography and television.

5 CONCLUSION This chapter has provided an overview of the basic theory related to sampling and interpolation of time-varying imagery. In contrast to other types of signals, it has been shown that it is not desirable to limit the spectrum of the continuous signal to a fixed threedimensional frequency band prior to sampling since this leads to excessive loss of spatial resolution. It is sufficient to ensure that the replicated spectra due to sampling do not overlap. However, optimal reconstruction requires the use of motion-compensated temporal interpolation.

The primary reason for this is that both hold only approximately for real data. Furthermore, they are based on second-order image derivatives that are difficult to compute reliably due to the high-pass nature of the operator; usually image smoothing must be performed first. Since color is a very important attribute of images, a possible extension of the above models would include chromatic image components. The assumption is that in areas of uniform intensity but substantial color detail, the inclusion of a color-based constraint could prove beneficial.

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