基于渐隐异常值的FTV系统深度改进

H. Hosseinpour, Seyed A. Moosavie nia, M. Pourmina
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引用次数: 0

摘要

虚拟视图合成是计算机视觉和三维应用的重要组成部分。高质量的深度图是虚拟视图合成的主要问题。因为与彩色图像相比,相应深度图像的分辨率较低。本文提出了一种基于逐渐省略离群点的高效、可信的深度值计算方法。在该方法中,远离深度值均值的深度值被逐步省略。仿真结果表明,该方法的平均PSNR提高了2.5dB (8.1%), SSIM提高了0.028 (3%),UNIQUE提高了0.021(2.4%),运行时间减少了8.6s(6.1%),错误像元减少了1.97(24.8%)。
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Depth Improvement for FTV Systems Based on the Gradual Omission of Outliers
Virtual view synthesis is an essential part of computer vision and 3D applications. A high-quality depth map is the main problem with virtual view synthesis. Because as compared to the color image the resolution of the corresponding depth image is low. In this paper, an efficient and confided method based on the gradual omission of outliers is proposed to compute reliable depth values. In the proposed method depth values that are far from the mean of depth values are omitted gradually. By comparison with other state of the art methods, simulation results show that on average, PSNR is 2.5dB (8.1 %) higher, SSIM is 0.028 (3%) more, UNIQUE is 0.021 (2.4%) more, the running time is 8.6s (6.1%) less and wrong pixels are 1.97(24.8%) less.
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