K-correlation power spectral density and surface scatter model

Dittman, Michael G.

doi:10.1117/12.678320

Cited by 28 publications

(35 citation statements)

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“…The results are illustrated on figure 1, where the exact straylight kernel is computed with ASAP for a point source at infinity at the center of the field, and compared with the corresponding Peterson kernel computed with (12) and (15). The agreement is excellent.…”

Section: Icso 2016 Biarritz France International Conference On Spacementioning

confidence: 62%

“…As can be checked numerically, this model is inherently normalized to the correct TIS. Dittman proposed to extend the K-correlation model to PSD functions with a slope s2 [15]. Such PSD laws are fitting well the experimental BSDFs, and indeed for s=2 one recovers the Wein equation [3].…”

Section: Roughness Of Optical Surfaces: Overview Of Existing Bsdf mentioning

confidence: 99%

“…It can be easily checked that in the BSDF from reference [3], proper normalization is not automatically achieved. Finally, the K-correlation model [15,16] is a physically-based BSDF obtained by inserting an analytical parametrization of the power spectral density (PSD) into the Rayleigh-Rice equation [10,16]. As can be checked numerically, this model is inherently normalized to the correct TIS.…”

Section: Roughness Of Optical Surfaces: Overview Of Existing Bsdf mentioning

confidence: 99%

“…Further, the obtained BSDFs are not normalized, and if proper normalization factors are added the final BSDF expression does not follow anymore the RayleighRice theory. To resolve the issue, Dittman [15] makes the following reasoning: the TIS, given by the BSDF integral over one hemisphere, is also given by the PSD integral over a limited range of frequencies (limited by the hemisphere boundaries), and finally given by the traditional equation (3) with a band-limited roughness. This band-limited roughness is wavelength-dependent, with the consequences that it is no longer possible to associate a single roughness value to a surface, and the TIS is now determined by the surface PSD.…”

Section: Roughness Of Optical Surfaces: Overview Of Existing Bsdf mentioning

confidence: 99%

See 3 more Smart Citations

Towards a standardized method to assess straylight in earth observing optical instruments

Caron

Taccola

Bézy

2017

International Conference on Space Optics — ICSO 2016

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Section: Icso 2016 Biarritz France International Conference On Spacementioning

confidence: 62%

Section: Roughness Of Optical Surfaces: Overview Of Existing Bsdf mentioning

confidence: 99%

Section: Roughness Of Optical Surfaces: Overview Of Existing Bsdf mentioning

confidence: 99%

Section: Roughness Of Optical Surfaces: Overview Of Existing Bsdf mentioning

confidence: 99%

See 2 more Smart Citations

Towards a standardized method to assess straylight in earth observing optical instruments

Caron

Taccola

Bézy

2017

International Conference on Space Optics — ICSO 2016

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“…Dittman provides the derivation, normalization and use of the K-Correlation Power Spectral Density (PSD) and BRDF models we use 8 . A summary of some of the critical terms is provided here:…”

Section: Definitionsmentioning

confidence: 99%

No such thing as σ: flowdown and measurement of surface roughness requirements

Dittman¹,

Grochocki²,

Youngworth³

2006

Optical Systems Degradation, Contamination, and Stray Light: Effects, Measurements, and Control II

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The standard use of the parameter σ for the rms surface roughness of optics has obscured the fact that the effective surface roughness is a function of both the measurement wavelength and bandwidth. A more appropriate method for the flowdown of surface specifications from stray light requirements is presented. Acceptance test methods for validating surface properties of optics using a Zygo NewView Profilometer are also discussed.

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In Situ AFM Imaging of Adsorption Kinetics of DPPG Liposomes: A Quantitative Analysis of Surface Roughness

et al. 2019

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The adsorption of intact liposomes on surfaces is of great importance for the development of sensors and drug delivery systems and, also, strongly dependent on the surface roughness where the liposomes are adsorbed. In this paper, we analyzed, by using atomic force microscopy in liquid, the evolution of the morphology of gold surfaces and of poly(allylamine hydrochloride) (PAH) surfaces with different roughness during the adsorption of liposomes prepared with the synthetic phospholipid 1,2-dipalmitoyl-sn-glycero-3-[phospho-rac-(1-glycerol)]. Our results reveal the following. On smooth surfaces of Au only and Au with PAH, the liposomes open and deploy on the substrate, creating a supported-lipid bilayer, with the opening process being faster on the Au/PAH surface. On rough substrates of Au coated with polyelectrolyte multilayers, the liposomes were adsorbed intact on the surface. This was corroborated by power spectral density analysis that demonstrates the presence of superstructures with an average lateral size of 43 and 87 nm, in accordance with two and four times the mean liposome hydrodynamic diameter of about 21 nm. In addition, this work presents an adequate and effective methodology for analysis of adsorption phenomena of liposomes on rough surfaces.

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K-correlation power spectral density and surface scatter model

Cited by 28 publications

References 0 publications

Towards a standardized method to assess straylight in earth observing optical instruments

Towards a standardized method to assess straylight in earth observing optical instruments

No such thing as σ: flowdown and measurement of surface roughness requirements

In Situ AFM Imaging of Adsorption Kinetics of DPPG Liposomes: A Quantitative Analysis of Surface Roughness

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