Theoretical Bases And Measurement Of The MTF Of Integrated Image Sensors

Chazallet, Frédéric; Glasser, Jean; Vaillant, Jacques

doi:10.1117/12.948815

Cited by 14 publications

(1 citation statement)

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“…Chazallet and Glasser compared methods of using a sinusoidal input, a bar chart input, and a knife-edge towards the goal of estimating the PSF with particular attention to spatial sampling and concluded that the knife-edge method, which uses a high contrast edge, or a step function in intensity, to produce an ESF was most favorable overall [5]. PSF estimation from a slanted edge has been refined over the years as the applications and the required detail have evolved.…”

Section: Introductionmentioning

confidence: 99%

<title>PSF estimation by gradient descent fit to the ESF</title>

Smith

2006

SPIE Proceedings

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Calibration of scanners and cameras usually involves measuring the point spread function (PSF). When edge data is used to measure the PSF, the differentiation step amplifies the noise. A parametric fit of the functional form of the edge spread function (ESF) directly to the measured edge data is proposed to eliminate this. Experiments used to test this method show that the Cauchy functional form fits better than the Gaussian or other forms tried. The effect of using a functional form of the PSF that differs from the true PSF is explored by considering bilevel images formed by thresholding. The amount of mismatch seen can be related to the difference between the respective kurtosis factors.

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Section: Introductionmentioning

confidence: 99%

<title>PSF estimation by gradient descent fit to the ESF</title>

Smith

2006

SPIE Proceedings

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Flow Imaging

Clemens

2002

Encyclopedia of Imaging Science and Technology

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Imaging has a long history in fluid mechanics and has proven critical to the investigation of nearly every type of flow of interest in science and engineering. A less than exhaustive list of flows where imaging has been successfully applied would include flows that are creeping, laminar, turbulent, reacting, high‐temperature, cryogenic, rarefied, supersonic, and hypersonic. The wide range of applications for flow imaging is demonstrated by the recent development of techniques for imaging at micro‐ and macroscales. Traditionally, flow imaging has been synonymous with “flow visualization,” which usually connotes that only qualitative information is obtained. Owing to the complex and often unpredictable nature of fluid flows, flow visualization remains one of the most important tools available in fluid mechanics research. Most imaging in fluid mechanics research involves planar imaging, where the flow properties are measured within a two‐dimensional cross section of the flow. This is most often accomplished by illuminating the flow using a thin laser light sheet, and then recording the scattered light using a digital camera. The laser light is scattered from either molecules or particles in the flow. The primary emphasis of this article is on this type of planar laser imaging because it remains the cornerstone of quantitative imaging in fluid mechanics research. Furthermore, planar imaging is often a building block for more complex 3‐D imaging techniques. Quantitative imaging is substantially more challenging than simple visualization because a greater degree of knowledge and effort are required before the researcher can ensure that the spatial distribution of the flow property of interest is faithfully represented in the image. The first part of this article discusses some of the most important issues that need to be addressed in quantitative flow imaging. The article ends with a brief survey of primarily planar imaging techniques that have been developed. This survey will not be able to discuss all, or even most, of the techniques that have been developed, but hopefully readers will gain an appreciation for the wide range of techniques that can be applied to their flow problems.

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Effects of imaging system blur on measurements of flow scalars and scalar gradients

Wang

Clemens

2004

Exp Fluids

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Theoretical Bases And Measurement Of The MTF Of Integrated Image Sensors

Cited by 14 publications

References 0 publications

<title>PSF estimation by gradient descent fit to the ESF</title>

<title>PSF estimation by gradient descent fit to the ESF</title>

Flow Imaging

Effects of imaging system blur on measurements of flow scalars and scalar gradients

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