Abstract
Depth information of the image is really necessary information to reconstruct a 3-dimensional object.
The classical methods of depth estimation are generally divided into two categories: active and passive
methods. The active methods requires the additional lighting equipment, passive methods also have a
series of problems .They require a plurality of images obtained by capturing a plurality of viewpoints ,
and determine the locating occlusion boundary , etc., and hence the depth estimation has been a
challenging problem in the research field of computer vision.1 Because of the depth information of the
image has a natural sparse features, this paper uses a passive approach, the signal of sparse priori based
on compressed sensing theory is used to estimate the depth of the image, without capturing multiple
images, using a single input image can obtain a high quality depth map. Experimental results show that
the depth map obtaining by our method, compared to the classical passive method, the contour
sharpness, the depth of detail information and the robustness of noise are more advantages. The method
also can be applied to re-focus the defocused images, and automatic scene segmentation and other
issues, ultimately may have broad application prospects in the reconstruction of true 3-dimensional
objects.
