A new depth estimation method for 3D reconstruction in a synthetic aperture integral imaging framework is presented. This method removes the edges of the objects in the elemental images when the objects are in focus. This strategy aims to compensate for the noise that objects focused close to the cameras can introduce into the photo-consistency measure of objects at higher depths. Furthermore, a photo-consistency criterion is applied combining a defocus and a correspondence measure, and a depth regularization method which smooths noisy depth results for the case of object surfaces. The proposed method obtains consistent results for any type of object surfaces as well as very sharp boundaries. Experimental results show that our method reduces the noise in the object edges and gives rise to an improvement in the depth map results in relation to the other methods shown in the comparative analysis.
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Depth estimation improvement in 3D integral imaging using an edge removal approach
Semantic Scholar · Computer Science · 2018
Abstract
A new depth estimation method for 3D reconstruction in a synthetic aperture integral imaging framework is presented. This method removes the edges of the objects in the elemental images when the objects are in focus. This strategy aims to compensate for the noise that objects focused close to the cameras can introduce into the photo-consistency measure of objects at higher depths. Furthermore, a photo-consistency criterion is applied combining a defocus and a correspondence measure, and a depth regularization method which smooths noisy depth results for the case of object surfaces. The proposed method obtains consistent results for any type of object surfaces as well as very sharp boundaries. Experimental results show that our method reduces the noise in the object edges and gives rise to an improvement in the depth map results in relation to the other methods shown in the comparative analysis.