Distortionless integrated imaging three-dimension display method adaptive to complex scene

Abstract

The invention provides a distortionless integrated imaging three-dimension display method adaptive to a complex scene. According to the method, the color image and depth image of a three-dimensional scene are obtained through using the Kinect; interference elimination is performed based on edge information according to the problem of the inconsistency of the boundaries of the color image and the depth image; as for the black hole region of the depth image, a joint trilateral filterer is adopted to fill the black hole region; a value domain filter in the joint trilateral filterer is adaptively processed, so that the artifact effect of the depth image is eliminated; and an optical field mathematical model is utilized to obtain the primitive element image array of the complex scene, so that distortionless three-dimension integrated imaging display is realized. With the distortionless integrated imaging three-dimension display method adaptive to the complex scene of the invention adopted, the physical limitations of a microlens array under the complex scene can be effectively eliminated, and the distortionless integrated imaging three-dimension display of the complex scene can be realized.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and relates to a distortion-free integrated imaging three-dimensional display method that can adapt to complex scenes. Background technique [0002] As a research hotspot in the next generation of true three-dimensional display technology, integrated imaging technology has the advantages of continuous viewing angle, full parallax, no visual fatigue and simple imaging structure. The 3D integrated imaging display mainly includes two processes of acquisition and reconstruction. The acquisition process uses a set of microlens arrays to record the three-dimensional scene, and each microlens in the microlens array captures the parallax information in the three-dimensional scene from different perspectives, and generates a primitive image array with multiple parallax information. The reconstruction process uses the microlens array with the same parameters as the acquisition time, and according ...

AI Technical Summary

Problems solved by technology

However, there are black hole areas on the depth image obtained based on Kinect. These areas are mainly caused by the inability of the infrared camera to acquire the speckle pattern due to foreground objects blocking the light path or objects with smooth surfaces or light-absorbing materials.

In addition, it is necessary to overcome the inconsistency of the boundary between the depth image and the color image and the continuous depth value

[0004] Since the advent of Kinect, many scholars have studied the restoration technology of Kinect depth image. In 2011, Matyunin et al. used inter-frame motion compensation and median filtering to fill the depth image with black holes, but did not consider boundary alignment and when encountering large In 2012, in order to correct the boundary alignment problem of the depth image, Loghman et al. combined the image filtering with the anisotropic diffusion upsampling process. However, in the upsampling process In the same year, Junyi Liu improved Telea's fast marching algorithm, using color images as guiding information to fill in black holes, that is, inserting effective depth values ​​around black hole points into black hole points, but this method also cannot eliminate The interference depth value around the boundary, and there is an artifact effect on the edge of the object after repair; Camplan used Gaussian mixture modeling to generate a depth image model in 2012, and then used a joint bilateral filter with adaptive weights to iteratively repair the depth map and update the depth The image model is used to obtain the denoised depth image, but it cannot be completely repaired for large areas of black hole regions.

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