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首页> 外文会议>Electro-Optical and Infrared Systems: Technology and Applications IV; Proceedings of SPIE-The International Society for Optical Engineering; vol.6737 >Low-cost Wavefront Coding Using Coma and a Denoising-based Deconvolution
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Low-cost Wavefront Coding Using Coma and a Denoising-based Deconvolution

机译：使用昏迷和基于降噪的反卷积的低成本波前编码

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摘要

Wavefront coding (WFC) is a powerful hybrid optical-numerical technique for increasing the depth of focus of imaging systems. It is based on two components: (1) an optical phase element that codifies the wavefront, and (2) a numerical deconvolution algorithm that reconstructs the image. Traditionally, some sophisticated optical WFC designs have been used to obtain approximate focus-invariant point spread functions (PSFs). Instead, we present a simple and low cost solution, implemented on infrared (IR) cameras, which uses a decentred lens inducing coma as an adjustable and removable phase element. We have used an advanced deconvolution algorithm for the image reconstruction, which is very robust against high noise levels. These features allow its application to low cost imaging systems. We show encouraging preliminary results based on realistic simulations using optical PSFs and noise power spectral density (PSD) laboratory models of two IR imaging systems. Without induced optical phase, the reconstruction algorithm improves the image quality in all cases, but it performs poorly when there are both in and out-of-focus objects in the scene. When using our coding/decoding scheme with low-noise detectors, the proposed solution provides high quality and robust recovery even for severe defocus. As sensor noise increases, the image suffers a graceful degradation, its quality being still acceptable even when using highly noisy sensors, such as microbolometers. We have experienced that the amount of induced coma is a key design parameter: while it only slightly affects the in-focus image quality, it is determinant for the final depth of focus.
机译：波前编码（WFC）是一种功能强大的混合光学数字技术，用于增加成像系统的聚焦深度。它基于两个组件：（1）编码波前的光学相位元素，以及（2）重建图像的数值反卷积算法。传统上，一些复杂的光学WFC设计已用于获得近似焦点不变点扩展函数（PSF）。取而代之的是，我们提出了一种简单且低成本的解决方案，该解决方案在红外（IR）相机上实现，该相机使用偏心镜诱发昏迷作为可调节和可移动的相位元件。我们已经使用了先进的反卷积算法来进行图像重建，对于高噪声水平它非常健壮。这些功能使其可以应用于低成本成像系统。我们展示了令人鼓舞的初步结果，这些结果基于使用光学PSF和两个IR成像系统的噪声功率谱密度（PSD）实验室模型的逼真的模拟。在没有诱导光学相位的情况下，重建算法可以在所有情况下提高图像质量，但是当场景中同时存在焦点对准和焦点对准的对象时，重建算法的效果会很差。当将我们的编码/解码方案与低噪声检测器一起使用时，即使严重的散焦，所提出的解决方案也可以提供高质量和强大的恢复能力。随着传感器噪声的增加，图像会遭受优美的降级，即使使用诸如微辐射热计的高噪声传感器，其质量仍然可以接受。我们已经体验到，诱发昏迷的数量是关键的设计参数：虽然它仅对焦距图像质量有轻微影响，但它是最终焦深的决定因素。

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