计算机科学
像素
算法
还原(数学)
信号(编程语言)
傅里叶变换
图像质量
均方误差
降噪
光学
图像(数学)
计算机视觉
数学
物理
统计
数学分析
程序设计语言
几何学
作者
Wei‐Feng Hsu,Shyh-Tsong Lin,Jeng‐Feng Lin
标识
DOI:10.1016/j.optlaseng.2019.05.023
摘要
Spatial light modulators (SLMs) comprising millions of micro-pixels have been applied for advanced applications requiring diffractive images of high quality (i.e., low root-mean-squared error, high signal-to-noise ratio, and low signal variation). Diffractive optical elements (DOEs) to be displayed in high-resolution SLMs are calculated using optimization algorithms to produce specific images. Current DOE optimization algorithms are incapable of providing high-quality images or else they consume too much time doing so. This paper presents two algorithms: the large error reduction algorithm (LERA) and the progressive error reduction algorithm (PERA). LERA selects image pixels (px) with the largest error for replacement with a target amplitude to improve image quality beyond what could be achieved using the iterative Fourier transform algorithm (IFTA). LERA tends to be time-consuming; however, it is able to reduce variations in signal intensity to 1.73e-8. PERA accelerates the optimization process by cascading an IFTA and several modified LERAs. Experiments were conducted on six DOEs of 1920×1080 px using a three-stage PERA equipped with three scaling factors.
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