Depth Map Coding Method Based on Edge Lossless Compression

Abstract

The invention provides a depth image coding method based on edge lossless compression, and belongs to the field of 3D video coding. The depth image coding method based on edge lossless compression is characterized by comprising the following steps that edge detection based on threshold values is conducted; chain codes are respectively used for coding foreground edges and background edges; forward differential predictive coding is conducted so as to obtain edge pixel values; downsampling is conducted; forward differential predictive coding is conducted so as to obtain seedy images; arithmetic coding is conducted so as to obtain residual sequences and chain code sequences; binary code streams are transmitted; arithmetic decoding is conducted; chain-code decoding is conducted on the foreground edges and the background edges; forward predictive differential decoding is conducted; the seedy images are restored; the seedy images are represented sparsely; reconstruction is conducted by adopting a reconstruction method based on partial differential equations and a natural near interpolation reconstruction method so that restored images can be obtained. The depth image coding method based on edge lossless compression has the advantages that the characteristic that smooth regions of depth images are segmented by sharp edges can be effectively explored, coding performance of the depth images can be improved significantly, and meanwhile drawing quality of virtual viewpoints is also improved.

Description

technical field [0001] The invention belongs to the technical field of 3D video coding, and in particular relates to a depth map coding method based on edge lossless compression. Background technique [0002] With the development of electronic products, 3D video (Three dimensional video, 3DV) has become an indispensable part of life entertainment. application. Traditional 3D video uses two cameras in different positions to collect video scenes, and then presents the videos of the two cameras to the two eyes respectively. Three-dimensionality appears in the brain. However, on the one hand, traditional 3D systems only have videos from two viewpoints, and the baseline distance between the two cameras is often much greater than the distance between our eyes and pupils. Fatigue and discomfort; on the other hand, more and more home 3D entertainment consumers require to watch 3D videos from any number of different angles. For this, it is necessary to collect and transmit videos ...

AI Technical Summary

Problems solved by technology

Although these methods can represent sharp edges well, they still cannot provide an accurate representation of depth map boundary pixels.

In order to achieve a more accurate description of depth discontinuities, this method needs to divide the image into pixel levels, but eventually leads to an increase in the bit rate for describing the tree structure

[0006] There is also a class of depth image coding methods that use edge-based lossless depth coding methods, which require edge detection or segmentation. However, the classic edge detection method cannot detect the required edges well, although some articles propose to use Sobel edge detection. , however, the number of edges detected by this edge detection method is relatively large, and it cannot simply and effectively describe the real edge information when describing the edge

Images