This paper introduces a novel approach for post-processing of depth map which enhances the depth map resolution in
order to achieve visually pleasing 3D models from a new monocular 2D/3D imaging system consists of a Photonic mixer
device (PMD) range camera and a standard color camera. The proposed method adopts the revolutionary inversion
theory framework called Compressive Sensing (CS). The depth map of low resolution is considered as the result of
applying blurring and down-sampling techniques to that of high-resolution. Based on the underlying assumption that the
high-resolution depth map is compressible in frequency domain and recent theoretical work on CS, the high-resolution
version can be estimated and furthermore reconstructed via solving non-linear optimization problem. And therefore the
improved depth map reconstruction provides a useful help to build an improved 3D model of a scene. The experimental
results on the real data are presented. In the meanwhile the proposed scheme opens new possibilities to apply CS to a
multitude of potential applications on various multimodal data analysis and processing.
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