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Multiview Image Coding Using Depth Layers and an Optimized Bit Allocation

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3 Author(s)
Andriy Gelman ; Department of Electrical and Electronic Engineering, Imperial College London, London, U.K. ; Pier Luigi Dragotti ; Vladan Velisavljevic

In this paper, we present a novel wavelet-based compression algorithm for multiview images. This method uses a layer-based representation, where the 3-D scene is approximated by a set of depth planes with their associated constant disparities. The layers are extracted from a collection of images captured at multiple viewpoints and transformed using the 3-D discrete wavelet transform (DWT). The DWT consists of the 1-D disparity compensated DWT across the viewpoints and the 2-D shape-adaptive DWT across the spatial dimensions. Finally, the wavelet coefficients are quantized and entropy coded along with the layer contours. To improve the rate-distortion performance of the entire coding method, we develop a bit allocation strategy for the distribution of the available bit budget between encoding the layer contours and the wavelet coefficients. The achieved performance of our proposed scheme outperforms the state-of-the-art codecs for several data sets of varying complexity.

Published in:

IEEE Transactions on Image Processing  (Volume:21 ,  Issue: 9 )