Arbitrary View Generation Based on DIBR and Depth-Aided Image Inpainting

LUO Kai; LI Dongxiao; FENG Yamei; ZHANG Ming

doi:10.11834/jig.20100314

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Arbitrary View Generation Based on DIBR and Depth-Aided Image Inpainting
Vol. 15, Issue 3, Pages: 443(2010)
Published：2010
DOI： 10.11834/jig.20100314
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DOI：

LUO Kai, LI Dongxiao, FENG Yamei, ZHANG Ming. Arbitrary View Generation Based on DIBR and Depth-Aided Image Inpainting[J]. Journal of Image and Graphics, 2010, 15(3): 443. DOI： 10.11834/jig.20100314.

摘要

基于深度的图像绘制（DIBR）是高级视频应用的关键技术，为提高视点变换的图像质量，提出一种基于DIBR和图像修复的任意视点绘制方法。首先对深度图像进行形态学处理，以减少视点变换产生的空洞，平滑目标视点内部的物体轮廓；利用视点变换方程生成目标视点；对含有空洞的目标视点采用图像修复算法进行后处理，设计了含有深度项的代价函数，在深度的约束下进行纹理搜索，将最佳匹配块填补到空洞；在修复空洞的过程中采用亮度优先的策略以适应不同的色度采样格式。实验的主观效果对比和PSNR数据都显示本文算法比其他算法更为优越。

Abstract

Depth-image-based rendering (DIBR) is a key technology to the advanced video applications. In order to improve the image quality generated by view warping

this paper proposes an arbitrary view generation method based on DIBR and image inpainting. The depth image is processed by morphological operations to reduce the holes generated during image warping and to smooth the object contour in the target image. The view warping equation is utilized to generate an arbitrary view. The image inpainting method is employed to restore holes inside the warped view. Depth cue is incorporated into the cost function for texture estimation. The pixels in the most match block corresponds to the holes in the target image are copied to the holes. During the restoration process

luma-first strategy is applied to adapt to various color sampling format. Experimental results show the proposed algorithm has superiority in both subjective details and PSNR statistics.