By Yun Q. Shi, Huifang Sun
ISBN-10: 0849334918
ISBN-13: 9780849334917
Multimedia nonetheless can't accommodate the call for for giant quantities of visible information. with out the iteration of top quality video bitstreams, constrained features will proceed to stifle the development of multimedia applied sciences. Thorough grounding in coding is required in order that functions corresponding to MPEG-4 and JPEG 2000 may perhaps come to fruition.
Image and Video Compression for Multimedia Engineering offers a superior, accomplished figuring out of the basics and algorithms that bring about the production of recent tools for producing prime quality video bit streams. The authors current a couple of correct advances in addition to foreign criteria.
New to the second one version
· A bankruptcy describing the lately constructed video coding regular, MPEG-Part 10 Advances Video Coding often referred to as H.264
· primary suggestions and algorithms of JPEG2000
· colour platforms of electronic video
· updated video coding criteria and profiles
Visual information, picture, and video coding will proceed to let the construction of complex undefined, compatible to the calls for of latest functions. overlaying either photo and video compression, this publication yields a distinct, self-contained reference for practitioners tobuild a foundation for destiny research, study, and development.
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Additional resources for Image and Video Compression for Multimedia Engineering. Fundamentals, Algorithms and Standards
Example text
An example using this method for studying the effect of varying numbers of quantization levels on image quality can be found in (Gonzalez and Woods, 1992). Another possible way to study the effect is to identify pictures with the same subjective quality measure from the whole array of pictures. From this subset of test pictures we can produce, in the encoding parameter space, isopreference curves that can be used to study the effect of the parameter(s) under investigation. An example using this method to study the effect of varying both image resolution and numbers of quantization levels on image quality can be found in (Huang, 1965).
Each confirms that the visual perception of the HVS is not simple. It is worth noting that our understanding of the high-level processing unit of the HVS is far from complete. Therefore, we may understand that the SNR does not always provide us with reliable assessments of image quality. 3, which uses the IGS quantization technique to achieve high compression (using only four bits for quantization instead of the usual eight bits) without introducing noticeable false contouring. In this case, the subjective quality is improved, and the SNR decreases due to the additive high-frequency random noise.
Foley, Contrast masking in human vision, J. Opt. Soc. , 70(12), 1458-1471, 1980. Lim, J. S. Two-Dimensional Signal and Image Processing, Englewood Cliffs, NJ, Prentice Hall, 1990. Mitchell, J. , W. B. Pennebaker, C. E. Fogg, and D. J. LeGall, MPEG Video Compression Standard, Chapman and Hall, New York, 1997. Mounts, F. W. A video encoding system with conditional picture-element replenishment, Bell Syst. Tech. , 48(7), 2545-2554, 1969. T. The contrast sensitivity of human color vision to red-green and blue-yellow chromatic gratings, J.