Lower photosynthetic capacity under higher spectral reflectance? The case of Actinidia polygama

Changes in growth and photosynthetic capacity of rice with increased UV-B radiation

Physiologia Plantarum ◽

10.1034/j.1399-3054.1991.830307.x ◽

1991 ◽

Vol 83 (3) ◽

pp. 373-380 ◽

Cited By ~ 13

Author(s):

Alan H. Teramura ◽

Lewis H. Ziska ◽

A. Ester Sztein

Keyword(s):

Photosynthetic Capacity

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The effects of development at sub-optimal growth temperatures on photosynthetic capacity and susceptibility to chilling-dependent photoinhibition in Zea mays

Physiologia Plantarum ◽

10.1034/j.1399-3054.1992.850322.x ◽

1992 ◽

Vol 85 (3) ◽

pp. 554-560 ◽

Cited By ~ 2

Author(s):

Gui-Ying Nie ◽

Steve P. Long ◽

Neil R. Baker

Keyword(s):

Zea Mays ◽

Photosynthetic Capacity ◽

Optimal Growth

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SAFARI 2000 SURFACE SPECTRAL REFLECTANCE AT SUA PAN, BOTSWANA, DRY SEASON 2000

ORNL Distributed Active Archive Center Datasets ◽

10.3334/ornldaac/780 ◽

2005 ◽

Author(s):

W. BUERMANN ◽

F. ECKARDT ◽

M. HELMLINGER

Keyword(s):

Spectral Reflectance ◽

Dry Season

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Skin Chromophore Estimation from Mobile Selfie Images using Constrained Independent Component Analysis

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.14.coimg-357 ◽

2020 ◽

Vol 2020 (14) ◽

pp. 357-1-357-6

Author(s):

Luisa F. Polanía ◽

Raja Bala ◽

Ankur Purwar ◽

Paul Matts ◽

Martin Maltz

Keyword(s):

Independent Component Analysis ◽

Spectral Reflectance ◽

Source Separation ◽

Principal Component ◽

Component Analysis ◽

Previous Method ◽

Independent Component ◽

Light Transport ◽

Camera Model ◽

Constrained Independent Component Analysis

Human skin is made up of two primary chromophores: melanin, the pigment in the epidermis giving skin its color; and hemoglobin, the pigment in the red blood cells of the vascular network within the dermis. The relative concentrations of these chromophores provide a vital indicator for skin health and appearance. We present a technique to automatically estimate chromophore maps from RGB images of human faces captured with mobile devices such as smartphones. The ultimate goal is to provide a diagnostic aid for individuals to monitor and improve the quality of their facial skin. A previous method approaches the problem as one of blind source separation, and applies Independent Component Analysis (ICA) in camera RGB space to estimate the chromophores. We extend this technique in two important ways. First we observe that models for light transport in skin call for source separation to be performed in log spectral reflectance coordinates rather than in RGB. Thus we transform camera RGB to a spectral reflectance space prior to applying ICA. This process involves the use of a linear camera model and Principal Component Analysis to represent skin spectral reflectance as a lowdimensional manifold. The camera model requires knowledge of the incident illuminant, which we obtain via a novel technique that uses the human lip as a calibration object. Second, we address an inherent limitation with ICA that the ordering of the separated signals is random and ambiguous. We incorporate a domain-specific prior model for human chromophore spectra as a constraint in solving ICA. Results on a dataset of mobile camera images show high quality and unambiguous recovery of chromophores.

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A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2020.64.5.050411 ◽

2020 ◽

Vol 64 (5) ◽

pp. 50411-1-50411-8

Author(s):

Hoda Aghaei ◽

Brian Funt

Keyword(s):

Machine Vision ◽

Spectral Reflectance ◽

Color Constancy ◽

Ground Truth ◽

Practical Approach ◽

Post Processing ◽

Illumination Estimation ◽

Processing Step ◽

Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

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