Rate Control for Spatial Scalability Video Coding

Randa Atta

ISBN 10: 6202069961 / ISBN 13: 9786202069960

Published by LAP LAMBERT Academic Publishing, 2017

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - This book investigates the problem of bit allocation for spatial and spatio-temporal scalability video coding of H.264/SVC. Little prior work deal with the H.264/SVC bit allocation problem considering the correlation between the enhancement and base layers. Nevertheless, most of the bit allocation algorithms suffer from high computational complexity which grows significantly with the number of layers. In this book, single-pass spatial and spatio-temporal bit allocation algorithms based on dependent Rate-Distortion (R-D) modeling are proposed. In both algorithms, the R-D model parameters are adaptively updated during the coding process. Experimental results demonstrate that the proposed algorithms achieve improvements in the coding gain as compared to the multi-pass model-based algorithm and the Joint Scalable Video Model (JSVM) FixedQPEncoder.

Seller Inventory # 9786202069960

Bibliographic Details

• Title: Rate Control for Spatial Scalability Video Coding
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2017
• Language: English
• ISBN 10: 6202069961
• ISBN 13: 9786202069960
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 10D millimeters 220 millimeters width by 150 millimeters height by 10 millimeters depth
• Weight: 262 grams

About this title

Synopsis

This book investigates the problem of bit allocation for spatial and spatio-temporal scalability video coding of H.264/SVC. Little prior work deal with the H.264/SVC bit allocation problem considering the correlation between the enhancement and base layers. Nevertheless, most of the bit allocation algorithms suffer from high computational complexity which grows significantly with the number of layers. In this book, single-pass spatial and spatio-temporal bit allocation algorithms based on dependent Rate-Distortion (R-D) modeling are proposed. In both algorithms, the R-D model parameters are adaptively updated during the coding process. Experimental results demonstrate that the proposed algorithms achieve improvements in the coding gain as compared to the multi-pass model-based algorithm and the Joint Scalable Video Model (JSVM) FixedQPEncoder.

About the Author

Randa Atta received the Ph.D. degree in Electronic Systems Engineering from the University of Essex, England in 2004. Currently, she is a Professor at Port Said University. She is the author or co-author of three books. Her research interests are image/video processing/coding and pattern recognition.