DocumentCode :
1850483
Title :
Lossy and near-lossless compression of depth images using segmentation into constrained regions
Author :
Schiopu, Ionut ; Tabus, Ioan
Author_Institution :
Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland
fYear :
2012
fDate :
27-31 Aug. 2012
Firstpage :
1099
Lastpage :
1103
Abstract :
This paper presents a lossy coding method for depth images using a segmentation constructed by selecting regions of pixels having the depth values obeying constraints defined in terms of some bounds, which are tuned in order to obtain the target distortion. The contours describing the segmentation are transmitted using an efficient chain coding method and are thus available also at the decoder for the next stage, which is region based predictive coding with a tunable precision level. The rate comprises the cost of losslessly transmission of the contours and the cost of transmitting the residuals with the decided precision, which is the main factor influencing the distortion. We introduce a procedure optimizing the parameters involved in the segmentation and in the prediction for a given image. As a side result, the segmentations residing on the convex hull of the RD curve can be seen as optimal segmentations with various granularity.
Keywords :
data compression; decoding; image coding; image segmentation; RD curve convex hull; decoder; depth image compression; efficient chain coding method; image segmentation; losslessly transmission cost; lossy coding method; lossy compression; near-lossless compression; parameter optimization; predictive coding; residuals transmission; target distortion; tunable precision level; Bit rate; Decoding; Encoding; Image coding; Image reconstruction; Image segmentation; Quantization; depth image; lossy compression; near-lossless compression; rate-distortion; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
Conference_Location :
Bucharest
ISSN :
2219-5491
Print_ISBN :
978-1-4673-1068-0
Type :
conf
Filename :
6333998
Link To Document :
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