The main purpose of this article is to compare the practice of five methods used to convert 2D images into 3D images. The 2D to 3D conversion technique plays an important role in 3DTV development and promotion as it supplies high quality 3D writing equipment. This article analyzes five methods and compares their results to the best ways to create high-quality 3D images. The first method to convert 2D images to 3D based on the depth information map with edge information. The second method uses information for a map of depth based on merger. The third method generates 3D images with random action algorithms. The fourth method creates 3D images using a combination of motion, edge detection, and image breakout, depth estimation, and relocation algorithms. Finally, the fifth method generates 3D images based on the deep nanoscale method. Many performance metrics are used to analyze the performance of these approaches. This file uses PSNR, SSIM, MSE and RMSE for operational analysis. Experimental results suggest that random way works better than the other two ways.

2D-to-3D conversion, depth boundaries, depthmap,nonlocal neighbors, nonlocal random walks

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