Objective

2

2D to 3D technology can quickly and effectively transfer the existing rich resource of 2D images into 3D images. However

existing methods only consider depth estimation on the entire object of a tree in the process of depth map generation. In this way

the tree in the final 3D images generated would normally lack a sense of depth and look like a piece of paper stuck on the background. The depth map generated by these methods cannot show the natural three-dimensional structural features of trees and has no sufficient rich stereoscopic levels to show the layering on the trees. To this end

this paper presents a 3D tree image construction method on the basis of depth template.

Method

2

In our proposed method

we first utilize the color difference of pixels under the laboratory color model to divide the 2D tree image into trunk and canopy areas and then divide the canopy area again into several small areas by using multiscale spectral-based image segmentation method. Then

considering the assumption of depth gradient hypothesis

we create various types of basic depth templates. In addition to the six commonly used basic depth templates

two new basic depth templates are added on the basis of the structural features of the trees. In accordance with the complexity of the morphology of trees

this paper divides the tree objects into two major categories:typical and atypical trees. The typical trees are those with regular shapes and can basically belong to the four typical tree models of spherical

conical

cylindrical

and wide spread shapes. The atypical trees are inconsistent with the basic characteristics of the existing four tree models. The initial depth maps of typical tree objects are constructed by combining the basic depth template and the area information of canopy. For the atypical tree object

we first select some basic depth templates to generate a personal depth temple

and then a personalized initial depth map is constructed through the combination of the personal depth temple and the tree's canopy area information. Finally

the tree depth information is adjusted and optimized adaptively in accordance with the application scene. 3D images of trees are adaptively adjusted in accordance with the depth information of the corresponding position of the background to obtain a depth map consistent with the background depth information. In addition

different objects in the scene are located at different depths

so when the tree images are synthesized into the background image

the occlusion between the objects in the scene needs to be adjusted. After the abovementioned process

the tree image is synthesized into the background image and the 3D image is constructed.

Result

2

To verify the effectiveness and practicability of our method

we used different background and tree image materials to create 3D image pairs. We show the five generated 3D images from the experiment in this paper. The experimental results show that all the tree images of different sizes

namely

typical and atypical

can produce layered depth images and can be adaptively synthesized into different 3D background images. The operating efficiency of the system is stable

and the time required to construct the stereoscopic image is linearly related to the size of the original tree image

which means that the run-time growth would not be explosively increased due to the increase in tree image size. In the subjective evaluation test on the stereoscopic image quality

we conducted tests and statistics on three aspects:3D image pair quality

depth map quality

and 3D comfort situation. Five different ratings are available for each aspect

covering all aspects related to the quality of the 3D image. In accordance with the statistics of each item

we obtain the total score under the percentile and then divide the total score into five grades:excellent

good

medium

normal

and poor. In the test

the ratings for these images all reach good levels

and some of them even achieve excellent levels.

Conclusion

2

To naturally blend 3D trees and 3D background images and enhance the 3D display of trees

by using the morphological characteristics of trees

this paper presents a 3D tree image construction method on the basis of depth template. The method takes full advantage of the morphological characteristics of trees and can be applied to both typical and atypical trees. The constructed 3D trees have a high image quality and comfortable stereoscopic effect. The depth template used in this paper presents a greater improvement in the depth sense of trees in 3D images than the existing methods.