Department of Electrical and Electronic Engineering, Imperial College London, London, UK.
IEEE Trans Image Process. 2012 Sep;21(9):4092-105. doi: 10.1109/TIP.2012.2201490. Epub 2012 May 25.
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.
在本文中，我们提出了一种新的基于小波的多视点图像压缩算法。该方法使用基于层的表示，其中 3D 场景由一组深度平面及其相关的恒定视差来近似。这些层是从多个视点拍摄的图像集合中提取出来的，并使用 3D 离散小波变换（DWT）进行变换。DWT 由跨越视点的一维视差补偿 DWT 和跨越空间维度的二维形状自适应 DWT 组成。最后，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几种不同复杂度数据的最新编解码器。
