KEYWORDS: Cameras, Image compression, Image processing, Data compression, Photography, 3D modeling, 3D acquisition, Distortion, Electronics, 3D image processing
This paper proposes a novel multiple-image coding technique using Ray-Space interpolation. Ray-Space, an image-based rendering technique to generate arbitrary views from multiple cameras, describes three- dimensional space based on only ray information from a large number of cameras. Therefore, data compression is needed. We leverage the correlation of time and space aiming for high compression. H.264/AVC is employed for dynamic image coding, and studies have been conducted on using the AVC in time domain. Here we propose a novel algorithm that uses view-interpolation for coding in space domain. Interpolation is a method to generate the middle view in a stereoscopic setup. By generating interpolated images from coded images as reference ones, coding performance should give better results. Therefore, interpolation accuracy is important for coding performance. In this paper, we propose an interpolation technique using geometric information in a linear camera arrangement. By calculating the trace of each point considering camera arrangement, and obtaining its corresponding point, the middle image is generated. In so doing, the interpolation method is an intensity-based scheme, constrained by smoothness in disparity domain. Experiment of coding using interpolation outperforms the standard AVC by 1~2 dB in all bitrates. Moreover, we deal with occlusion regions by means of extrapolation using four images. To detect occlusion regions, we use two criteria, one is minimum error, second is ratio of minimum error between four images. In occlusion region, the intensity of middle image is generated using extrapolated images. This method gives up to 1~3 dB improvement compared to occlusion-ignored algorithm.
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