Image reconstruction and enhanced resolution imaging from irregular samples
Image reconstruction and enhanced resolution imaging from irregular samples
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DOI：
10.1109/36.905237
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发表时间：
2001-02
期刊：
影响因子：
--
通讯作者：
D. Early;D. Long
中科院分区：
文献类型：
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作者：
D. Early;D. Long
虽然高分辨率、规则网格的观测通常是遥感中的首选，但实际观测往往采样不均匀，分辨率低于预期。因此，分辨率增强和图像重建引起了人们的兴趣。本文讨论了从不规则采样数据重建图像和生成增强分辨率图像的一般理论和技术。利用非规则采样理论，我们考虑了如何利用非理想孔径滤光片测量的高频成分，通过重构技术从过采样数据中恢复孔径函数衰减的旁瓣中的频率成分。我们证明，只要稍加修改，代数重建技术(ART)与Grochenig(1992)的不规则抽样重建算法在功能上是等价的。使用简单的蒙特卡罗模拟，我们比较和对比了加法ART、乘法ART和散射计图像重建(SIR)(乘法ART的导数)算法在有无噪声的情况下的性能。重建理论和技术可以应用于各种传感器，并可以从许多非成像传感器产生更高分辨率的图像。以ERS-2和SeaWinds散射计数据为例说明了这一技术。
While high resolution, regularly gridded observations are generally preferred in remote sensing, actual observations are often not evenly sampled and have lower-than-desired resolution. Hence, there is an interest in resolution enhancement and image reconstruction. This paper discusses a general theory and techniques for image reconstruction and creating enhanced resolution images from irregularly sampled data. Using irregular sampling theory, we consider how the frequency content in aperture function-attenuated sidelobes can be recovered from oversampled data using reconstruction techniques, thus taking advantage of the high frequency content of measurements made with nonideal aperture filters. We show that with minor modification, the algebraic reconstruction technique (ART) is functionally equivalent to Grochenig's (1992) irregular sampling reconstruction algorithm. Using simple Monte Carlo simulations, we compare and contrast the performance of additive ART, multiplicative ART, and the scatterometer image reconstruction (SIR) (a derivative of multiplicative ART) algorithms with and without noise. The reconstruction theory and techniques have applications with a variety of sensors and can enable enhanced resolution image production from many nonimaging sensors. The technique is illustrated with ERS-2 and SeaWinds scatterometer data.