基于傅里叶变换和灰度共生矩阵的Hadamard矩阵重排序压缩单像素成像
Re-ordering of Hadamard matrix using Fourier transform and gray-level co-occurrence matrix for compressive single-pixel imaging
摘要：
单像素成像中最活跃的研究领域之一是采样基及其顺序对重建图像质量的影响。本文提出了两个新的顺序，上升尺度（AS）和上升惯性（AI），阿达玛基和测试其性能，使用模拟和实验方法，低采样率（0.5至0.01）。这些订单进行了比较，两个国家的最先进的订单，蛋糕切割（CC）和总梯度（TG），使用TVAL 3作为重建算法和三个噪声水平。这些新提出的顺序有更好的重建图像质量的模拟数据集（110张图像），并实现了结构相似性指数值高于CC顺序。实验数据集（2幅图像）表明，AS和AI命令在采样率为0.5时表现更好，而对于较低的采样率，AS，AI和CC的性能相似。TG订单在大多数情况下表现最差。最后，仿真结果提出了明确的证据，峰值信噪比（PSNR）是不是一个可靠的图像质量评估（IQA）的度量来评估图像重建质量的背景下，单像素成像。
英文摘要：
One of the most active research fields in single-pixel imaging is the influence of the sampling basis and its order in the quality of the reconstructed images. This paper presents two new orders, ascending scale (AS) and ascending inertia (AI), of the Hadamard basis and test their performance, using simulation and experimental methods, for low sampling ratios (0.5 to 0.01). These orders were compared with two state-of-the-art orders, cake-cutting (CC) and total gradient (TG), using TVAL3 as the reconstruction algorithm and three noise levels. These newly proposed orders have better reconstructed image quality on the simulation data set (110 images) and achieved structure similarity index values higher than CC order. The experimental data set (2 images) showed that the AS and AI orders performed better with a sampling ratio of 0.5, while for lower sampling ratio the performance of AS, AI and CC was similar. The TG order performed worst in the majority of the cases. Finally, the simulation results present clear evidence that peak signal-to-noise ratio (PSNR) is not a reliable image quality assessment (IQA) metric to assess image reconstruction quality in the context of single pixel imaging.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
