Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis

Abstract

Abstract-A depth image provides partial geometric information of a 3D scene, namely the shapes of physical objects as observed from a particular viewpoint. This information is important when synthesizing images of different virtual camera viewpoints via depth-image-based rendering (DIBR). It has been shown that depth images can be efficiently coded using contour-adaptive codecs that preserve edge sharpness, resulting in visually pleasing DIBR-synthesized images. However, contours are typically losslessly coded as side information (SI), which is expensive if the object shapes are complex.In this paper, we pursue a new paradigm in depth image coding for color-plus-depth representation of a 3D scene: we pro-actively simplify object shapes in a depth and color image pair to reduce depth coding cost, at a penalty of a slight increase in synthesized view distortion. Specifically, we first mathematically derive a distortion upper-bound proxy for 3DSwIM-a quality metric tailored for DIBR-synthesized images. This proxy reduces interdependency among pixel rows in a block to ease optimization. We then approximate object contours via a dynamic programming (DP) algorithm to optimally trade off coding cost of contours using arithmetic edge coding (AEC) with our proposed view synthesis distortion proxy. We modify the depth and color images according to the approximated object contours in an inter-view consistent manner. These are then coded respectively using a contour-adaptive image codec based on graph Fourier transform (GFT) for edge preservation and HEVC intra. Experimental results show that by maintaining sharp but simplified object contours during contour-adaptive coding, for the same visual quality of DIBR-synthesized virtual views, our proposal can reduce depth image coding rate by up to 22% compared to alternative coding strategies such as HEVC intra.

Highly Efficient Multiview Depth Coding Based on Histogram Projection and Allowable Depth Distortion

“…To handle this problem, 3D Synthesized View Image Quality Metric (3DSwIM) [32] was proposed to measure the perceived quality of the synthesized image and a depth coding algorithm was proposed to improve the 3DSwIM value via preserving the depth edges. Furthermore, since the synthesized videos have annoying flicker due to temporal inconsistency of depth maps, video quality assessment models were proposed in [34] and [35].…”

Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC

“…Hence, J VSO is an important parameter to predict the D max . The event E 0 and the event E 1 is defined, for example, by (7) and (8), respectively, where J 0 curCTU and J 0 colCTU represents J VSO of the current CTU and the…”

“…Currently, 3D-HEVC is the latest 3D video coding standard [3][4][5], which can utilise inter-view dependency to compress texture video and depth video efficiently. Depth video is used to synthesise arbitrary-view video by using depth-image-based rendering (DIBR) technology [6,7], so as to provide the audience more choices of perspective. Therefore, the coding quality of the depth video is very critical for 3D-HEVC.…”

No-reference quality assessment for depth image based rendering-synthesized images based on multi-feature fusion

“…FVV is a research focus on next-generation video technology 1 – 3 Using texture and the corresponding depth images of a few viewpoints, the depth image-based rendering (DIBR) technique can synthesize the virtual viewpoints in three-dimensional space. Hence, DIBR can ease the encoding and transmission burden and realize the FVV system.…”