Color Fading: Variation of Colorimetric Parameters with Spectral Reflectance

Author(s):  
Deepak Sarvate ◽  
Amit Bhati ◽  
Rahul Srivastava ◽  
VS Choudhary ◽  
RV Raghavan
2020 ◽  
Vol 2020 (14) ◽  
pp. 357-1-357-6
Author(s):  
Luisa F. Polanía ◽  
Raja Bala ◽  
Ankur Purwar ◽  
Paul Matts ◽  
Martin Maltz

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.


2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt

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.


2003 ◽  
Vol 67 (1) ◽  
pp. 289 ◽  
Author(s):  
E. Ben-Dor ◽  
N. Goldlshleger ◽  
Y. Benyamini ◽  
M. Agassi ◽  
D. G. Blumberg

2020 ◽  
Vol 5 (8) ◽  
pp. 145-146
Author(s):  
Dr. F. E. Abu-Agwa ◽  
Dr. M. S. Amira ◽  
Dr. E. A. Abou-Hussien ◽  
Dr. M. I. S. Ahmad
Keyword(s):  

1993 ◽  
Vol 154 (2) ◽  
pp. 298-305 ◽  
Author(s):  
Gregory A. Carter ◽  
Donald R. Young

Author(s):  
Hibiki M. Noda ◽  
Hiroyuki Muraoka ◽  
Kenlo Nishida Nasahara

AbstractThe need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.


Sign in / Sign up

Export Citation Format

Share Document