An Accurate and Efficient Nonlinear Depth Quantization Scheme

As known, depth information exists as floating distance data, when firstly captured by depth sensor. In view of storage and transmission, it is necessary to be quantized into several depth layers. Generally, it is mutually contradictory between the efficiency of depth quantization and the accuracy of view synthesis. Actually, since 3D-warping rounding calculation exists during view synthesis, depth changes within a certain range will not cause different warped position. This phenomenon provides a good way to quantize depth data more efficiently. However, 3D-warping rounding calculation can also bring additional view synthesis distortion, if the warped-interval and image-resolution-interval are misaligned. Hence, to achieve efficient depth quantization without introducing additional view synthesis distortion, an accurate and efficient nonlinear-depth quantization scheme (AE-NDQ) is presented in which the alignment between warped-interval and image-resolution-interval is taken into consideration during the depth quantization. Experimental results show, compared with the efficient nonlinear-depth-quantization (E-NDQ), AE-NDQ needs almost the same bits to represent the depth layers but maintains more accurate on view synthesis. For the traditional 8-bits nonlinear-depth-quantization (NDQ), AE-NDQ needs less bits to represent the depth layers, while has the same accuracy of the synthesized view.