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Multiview Image Coding Using Depth Layers and an Optimized Bit Allocation

机译:使用深度层和优化位分配的多视图图像编码

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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.
机译:在本文中,我们提出了一种新颖的基于小波的多视图图像压缩算法。该方法使用基于层的表示,其中3-D场景由一组深度平面及其相关的恒定视差近似。从在多个视点捕获的图像集合中提取图层,并使用3-D离散小波变换(DWT)进行变换。 DWT由跨视点的一维视差补偿DWT和跨空间维的2-D形状自适应DWT组成。最后,将小波系数与层轮廓一起进行量化和熵编码。为了提高整个编码方法的速率失真性能,我们开发了一种位分配策略,用于在编码层轮廓和小波系数之间分配可用的位预算。我们提出的方案的性能优于具有不同复杂度的多个数据集的最新编解码器。

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