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Analysis of displacement errors in high-resolution imagereconstruction with multisensors

机译:多传感器高分辨率图像重建中的位移误差分析

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摘要

An image-acquisition system composed of an array of sensors, where each sensor has a subarray of sensing elements of suitable size, has recently been popular for increasing the spatial resolution with high signal-to-noise ratio beyond the performance bound of technologies that constrain the manufacture of imaging devices. Small perturbations around the ideal subpixel locations of the sensing elements (responsible for capturing the sequence of undersampled degraded frames), because of imperfections in fabrication, limit the performance of the signal-processing algorithms for processing and integrating the acquired images for the desired enhanced resolution and quality. The contributions of this paper include an analysis of the displacement errors on the convergence rate of the iterative approach for solving the transform based preconditioned system of equations. Subsequently, it is established that the use of the MAP, L2 norm or H1 norm regularization functional leads to a proof of linear convergence of the conjugate gradient method in terms of the displacement errors caused by the imperfect subpixel locations. Results of simulation support the analytical results
机译:由传感器阵列组成的图像采集系统(其中每个传感器具有适当大小的传感元件的子阵列)最近在提高空间分辨率和高信噪比方面已广受欢迎,超出了约束技术的性能范围。成像设备的制造。由于制造上的缺陷,在传感元件的理想子像素位置(负责捕获欠采样的降级帧的序列)周围的微小扰动限制了信号处理算法的性能,该算法用于处理和积分所获取图像以获得所需的增强分辨率和质量。本文的贡献包括对求解基于变换的方程式预处理系统的迭代方法的收敛速度的位移误差的分析。随后,建立了MAP,L2范数或H1范数正则化函数的使用导致共轭梯度法线性收敛的证据,该共轭梯度法是由不完美的子像素位置引起的位移误差。模拟结果支持分析结果

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