DocumentCode
1660388
Title
M-channel multiple description coding based on uniformly offset quantizers with optimal deadzone
Author
Lili Meng ; Jie Liang ; Yao Zhao ; Huihui Bai ; Chunyu Lin ; Kaup, Andre
Author_Institution
Inst. of Inf. Sci., Beijing Jiaotong Univ., Beijing, China
fYear
2013
Firstpage
2026
Lastpage
2030
Abstract
This paper proposes an improved source-splitting-based two-rate M-channel multiple description coding scheme, where the source is split into M subsets. In each description, one subset is coded at a high rate, and others are predictively coded at a low rate. Uniform offsets among low-rate quantizers of different descriptions are achieved by employing unequal deadzones and by quantizing the predictions. When several descriptions are received, the optimal reconstruction of each subset is achieved by finding the intersection of all received quantization bins. The closed-form expression of the expected distortion is obtained. The proposed scheme is applied to lapped transform-based multiple description image coding and achieves improved performance. The optimal deadzone selection and its impact are also given in this paper.
Keywords
image coding; quantisation (signal); signal reconstruction; transforms; M subsets; closed-form expression; expected distortion; lapped transform; low-rate quantizers; multiple description image coding; optimal deadzone; optimal reconstruction; predictive coding; received quantization bins; source-splitting; two-rate M-channel multiple description coding; unequal deadzones; uniformly offset quantizers; Bit rate; Closed-form solutions; Encoding; Image coding; Image reconstruction; PSNR; Quantization (signal); Multiple description coding; deadzone quantization; predictive coding; random quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location
Vancouver, BC
ISSN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2013.6638009
Filename
6638009
Link To Document