梯度下降
全息术
计算机科学
计算机视觉
计算
人工智能
算法
坐标下降
计算全息
约束(计算机辅助设计)
相(物质)
图像复原
图像(数学)
光学
图像处理
数学
人工神经网络
物理
几何学
量子力学
作者
Koray Kavaklı,Yuta Itoh,Hakan Ürey,Kaan Akşit
标识
DOI:10.1109/vr55154.2023.00057
摘要
This paper introduces a new multiplane CGH computation method to reconstruct artifact-free high-quality holograms with natural-looking defocus blur. Our method introduces a new targeting scheme and a new loss function. While the targeting scheme accounts for defocused parts of the scene at each depth plane, the new loss function analyzes focused and defocused parts separately in reconstructed images. Our method support phase-only CGH calculations using various iterative (e.g., Gerchberg-Saxton, Gradient Descent) and non-iterative (e.g., Double Phase) CGH techniques. We achieve our best image quality using a modified gradient descent-based optimization recipe where we introduce a constraint inspired by the double phase method. We validate our method experimentally using our proof-of-concept holographic display, comparing various algorithms, including multi-depth scenes with sparse and dense contents.
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