Method and apparatus for estimating depth by using focus stack based on density of feature points

Abstract

The present invention discloses a method and apparatus for estimating depth by using a focus stack based on the density of feature points. The method includes the following steps that: the feature points of each image in a focus stack are extracted, a feature point density-based focus measure is established; a depth estimation model based on a feature point density-introduced weighted focus measure is established; and with an SML focus measure adopted as an instance, an SML and feature point density-based weighted linear mixed focus measure is adopted as the objective function of depth estimation, so that the estimation of the depth and full-focus image of a scene can be realized. According to the method of the invention, the focus measure about the density of the feature points and the linear weighted focus measure are established, and the focus measure-based depth estimation model is constructed, and the depth information of the scene is obtained, and therefore, the full-focus and three-dimensional reconstruction of the scene can be realized. With the method adopted, precise depth information can be provided for the realization of three-dimensional reconstruction, and the full-focus image can be obtained.

Description

technical field [0001] The invention relates to the fields of computer vision and digital image processing, in particular to a method and device for estimating depth from a focus stack based on feature point density. Background technique [0002] The digitization of 3D scene information has expanded human cognition and expression of 3D space. Image-based 3D reconstruction has always been a research hotspot in computational vision. Scene depth information reconstruction can provide 3D information for virtual reality, augmented reality, and photogrammetry, and is the key to reconstructing 3D scenes. [0003] At present, image-based scene depth estimation methods are mainly divided into stereo vision methods and monocular vision methods. For the stereo vision method, the parallax method is more common in the depth estimation method. The parallax method uses the parallax generated between images from different viewpoints as the basis for depth estimation. The core problem of th...

AI Technical Summary

Problems solved by technology

However, the accuracy of the focus measurement method in the prior art is not high in the detection of image texture regions

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