Compression comparisons for multiview stereo

D.K. Jones, M.W. Maier
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Abstract

Summary form only given. Multiview stereo imaging uses arrays of cameras to capture scenes from multiple perspectives. This form of imagery is used in systems that allow the user to survey the scene, for example by head motion. Very little work has been reported on compression schemes for multiview images. Multiview image sets tend to be very large because they may contain several hundred views, but there is considerable redundancy among the views which makes them highly compressible. This paper compares methods for compressing large multiview stereo image sets. There is an obvious similarity between multiview image sets and video sequences. As a baseline we compressed a set of multiview stereo images with JPEG on each image individually and MPEG-1 applied to the whole set. The average bits per pixel were reduced by roughly a factor of two over individual frame compression, at constant mean square error (MSE). Stereo specific perceptual distortions can be viewed in anaglyph representations of the data set. Another method, unique to this data type, is based on residual coding with respect to a synthetic "panoramic still" containing information from all of the images in the set. In this method we synthesize a single panoramic image from all of the members of a registered set, code the panoramic image, and then code the residual images formed by subtracting the individual images from the corresponding position on the panorama. Initial results with this method appear to give a similar MSE rate distortion curve as the MPEG based techniques. However, the panoramic still method is inherently random access.
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多视点立体的压缩比较
只提供摘要形式。多视角立体成像使用相机阵列从多个角度捕捉场景。这种形式的图像用于允许用户调查场景的系统中,例如通过头部运动。关于多视图图像压缩方案的研究很少。多视图图像集往往非常大,因为它们可能包含数百个视图,但视图之间存在相当大的冗余,这使得它们具有高度可压缩性。本文比较了压缩大型多视点立体图像集的几种方法。多视图图像集和视频序列之间有明显的相似性。作为基线,我们压缩了一组多视图立体图像,每个图像单独使用JPEG,并将MPEG-1应用于整个图像集。在均方误差(MSE)不变的情况下,每个像素的平均比特数在单个帧压缩中大约减少了两倍。立体特定的感知扭曲可以在数据集的象形表示中查看。这种数据类型特有的另一种方法是基于对包含集合中所有图像信息的合成“全景静止图像”的残差编码。在该方法中,我们将注册集的所有成员合成为单个全景图像,对全景图像进行编码,然后对全景图像上相应位置的单个图像进行减去形成的残差图像进行编码。该方法的初步结果与基于MPEG的技术的MSE率失真曲线相似。然而,全景静止方法本身就是随机存取。
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