Multiview image compression using a layer-based representation

We propose a novel compression method for multiview still images. The algorithm exploits the layer-based representation, which partitions the data set into planar layers characterized by a constant depth value. For efficient compression, the partitioned data is de-correlated using the separable three-dimensional wavelet transform across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. The generated transform coefficients are entropy coded. Our coding method is capable of outperforming the state-of-the-art algorithms, like H.264/AVC, for different data sets.

• Type: Journal
• Year: 2010
• Where: ICIP
• Authors: Andriy Gelman, Pier Luigi Dragotti, Vladan Velisavljevic
• Keywords: Constant Depth Value, Generated Transform Coefficients, ICIP 2010, Image Processing, Separable Three-dimensional Wavelet