By Sergios Theodoridis, Rama Chellappa
This 5th quantity, edited and authored by means of international best specialists, offers a assessment of the rules, tools and methods of vital and rising study themes and applied sciences in photograph and video compression and multimedia.
With this reference resource you will:
- Quickly seize a brand new sector of study
- Understand the underlying rules of a subject matter and its application
- Ascertain how an issue pertains to different components and research of the learn concerns but to be resolved
- Quick educational reports of vital and rising subject matters of analysis in snapshot and Video Compression and Multimedia
- Comprehensive references to magazine articles and different literature on which to construct additional, extra particular and special knowledge
- Edited by way of leading people in the sphere who, via their recognition, were capable of fee specialists to put in writing on a selected topic
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Additional info for Academic Press Library in Signal Processing, Volume 5: Image and Video Compression and Multimedia
A Wiener-based displacement estimation algorithm is introduced in . A multiple frames model-based approach is proposed in . Finally, a multiple mask regularization technique is introduced in . There are some advantages of the pel-recursive methods over other existing approaches. , it can handle the motion discontinuities), the pelrecursive algorithms may overcome the problem of multiple moving objects. Moreover, as the update vector calculation is based only on previously transmitted data (causality), the decoder can estimate the same motion vector field as the encoder.
9 Standardization of video coding systems Standardization of image and video formats and compression methods has been instrumental in the success and universal adoption of video technology. An overview of coding standards is provided below and a more detailed description of the primary features of the most recent standard (HEVC) is provided in Chapter 3. Standards are essential for interoperability, enabling material from different sources to be processed, and transmitted over a wide range of networks or stored on a wide range of devices.
More specifically, the 2D motion vector field is defined as the projection of the 3D object’s motion onto the 2D image plane . In contrast, the optical flow is defined as apparent motion of the brightness pattern [7,8]. In other words, the optical flow captures the spatio-temporal variation of pixel intensities. The 2D motion vector field and the optical flow often coincide, although it is not mandatory. To better understand the difference, let us consider two simple examples. 1 shows a three-dimensional uniform sphere in pure rotation and under constant illumination.