The Experts below are selected from a list of 105222 Experts worldwide ranked by ideXlab platform
Ning Zhang - One of the best experts on this subject based on the ideXlab platform.
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primary consistent soft decision color demosaicking for Digital Cameras patent pending
IEEE Transactions on Image Processing, 2004Co-Authors: Xiaolin Wu, Ning ZhangAbstract:Color mosaic sampling schemes are widely used in Digital Cameras. Given the resolution of CCD sensor arrays, the image quality of Digital Cameras using mosaic sampling largely depends on the performance of the color demosaicking process. A common problem with existing color demosaicking algorithms is an inconsistency of sample interpolations in different primary color channels, which is the cause of the most objectionable color artifacts. To cure the problem, we propose a new primary-consistent soft-decision framework (PCSD) of color demosaicking. In the PCSD framework, we make multiple estimates of a missing color sample under different hypotheses on edge or texture directions. The estimates are made via a primary consistent interpolation, meaning that all three primary components of a color are interpolated in the same direction. The final estimate of a color sample is obtained by testing different interpolation hypotheses in the reconstructed full-resolution color image and selecting the best via an optimal statistical decision or inference process. A concrete color demosaicking method of the PCSD framework is presented. This new method eliminates certain types of color artifacts of existing color demosaicking methods. Extensive experimental results demonstrate that the PCSD approach can significantly improve the image quality of Digital Cameras in both subjective and objective measures. In some instances, our gain over the competing methods can be as much as 7dB.
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primary consistent soft decision color demosaic for Digital Cameras
International Conference on Image Processing, 2003Co-Authors: Ning ZhangAbstract:Bayer color mosaic sampling scheme is widely used in Digital Cameras. Given the resolution of CCD sensor arrays, the image quality of Digital Cameras using Bayer sampling mosaic largely depends on the performance of the color demosaic process. A common and serious weakness shared by all existing color demosaic algorithms is an inconsistency of sample interpolations in different primary color components, which is the culprit for the most objectionable color artifacts. To cure the problem we propose a primary-consistent color demosaic algorithm. The performance of this algorithm is further enhanced by a soft-decision sample interpolation scheme. Experiments demonstrate that the proposed framework of primary-consistent soft-decision color demosaic can significantly improve the image quality of Digital Cameras.
Xiaolin Wu - One of the best experts on this subject based on the ideXlab platform.
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primary consistent soft decision color demosaicking for Digital Cameras patent pending
IEEE Transactions on Image Processing, 2004Co-Authors: Xiaolin Wu, Ning ZhangAbstract:Color mosaic sampling schemes are widely used in Digital Cameras. Given the resolution of CCD sensor arrays, the image quality of Digital Cameras using mosaic sampling largely depends on the performance of the color demosaicking process. A common problem with existing color demosaicking algorithms is an inconsistency of sample interpolations in different primary color channels, which is the cause of the most objectionable color artifacts. To cure the problem, we propose a new primary-consistent soft-decision framework (PCSD) of color demosaicking. In the PCSD framework, we make multiple estimates of a missing color sample under different hypotheses on edge or texture directions. The estimates are made via a primary consistent interpolation, meaning that all three primary components of a color are interpolated in the same direction. The final estimate of a color sample is obtained by testing different interpolation hypotheses in the reconstructed full-resolution color image and selecting the best via an optimal statistical decision or inference process. A concrete color demosaicking method of the PCSD framework is presented. This new method eliminates certain types of color artifacts of existing color demosaicking methods. Extensive experimental results demonstrate that the PCSD approach can significantly improve the image quality of Digital Cameras in both subjective and objective measures. In some instances, our gain over the competing methods can be as much as 7dB.
Joaquin Alonsomontesinos - One of the best experts on this subject based on the ideXlab platform.
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solar extinction measurement system based on Digital Cameras application to solar tower plants
Renewable Energy, 2018Co-Authors: J Ballestrin, R Monterreal, M E Carra, Jesus Fernandezreche, Jesus Polo, R Enrique, Jorge Rodriguez, M Casanova, F J Barbero, Joaquin AlonsomontesinosAbstract:Abstract In Concentrating Solar Power (CSP) technologies, direct solar radiation is reflected from a concentrating system to a receiver, where it is transformed into process heat. In particular, in solar tower plants, the phenomenon of atmospheric extinction between both systems must be studied since the radiative losses can be important due to the increasingly large distances in the gradually larger plants. Large distances are necessary in order to measure the extinction since, in reduced distances, it can be undetectable. However, the great uncertainty of some available instruments and/or the monochromaticity of others, make it possible to affirm that, at present, there is no experimental device that allows a credible measure of solar extinction to be carried out. Nowadays, Digital Cameras are used in many scientific applications due to their ability to convert available light into Digital images. Their broad spectral range, high resolution and high signal to noise ratio, make them an interesting device for extinction measurement. The aim of this work is to present the description of a novel measurement system for solar extinction at ground level based on two Digital Cameras and a Lambertian target. The first experimental results show that the system can measure solar extinction in the bandwidth 400–1000 nm with an accuracy of less than an absolute ±2%. This measurement system is currently running on a daily basis at Plataforma Solar de Almeria.
Elisabeth J Cooper - One of the best experts on this subject based on the ideXlab platform.
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using ordinary Digital Cameras in place of near infrared sensors to derive vegetation indices for phenology studies of high arctic vegetation
Remote Sensing, 2016Co-Authors: Helen B Anderson, Lennart Nilsen, Hans Tommervik, Stein Rune Karlsen, Shin Nagai, Elisabeth J CooperAbstract:To remotely monitor vegetation at temporal and spatial resolutions unobtainable with satellite-based systems, near remote sensing systems must be employed. To this extent we used Normalized Difference Vegetation Index NDVI sensors and normal Digital Cameras to monitor the greenness of six different but common and widespread High Arctic plant species/groups (graminoid/Salix polaris; Cassiope tetragona; Luzula spp.; Dryas octopetala/S. polaris; C. tetragona/D. octopetala; graminoid/bryophyte) during an entire growing season in central Svalbard. Of the three greenness indices (2G_RBi, Channel G% and GRVI) derived from Digital camera images, only GRVI showed significant correlations with NDVI in all vegetation types. The GRVI (Green-Red Vegetation Index) is calculated as (GDN − RDN)/(GDN + RDN) where GDN is Green Digital number and RDN is Red Digital number. Both NDVI and GRVI successfully recorded timings of the green-up and plant growth periods and senescence in all six plant species/groups. Some differences in phenology between plant species/groups occurred: the mid-season growing period reached a sharp peak in NDVI and GRVI values where graminoids were present, but a prolonged period of higher values occurred with the other plant species/groups. In particular, plots containing C. tetragona experienced increased NDVI and GRVI values towards the end of the season. NDVI measured with active and passive sensors were strongly correlated (r > 0.70) for the same plant species/groups. Although NDVI recorded by the active sensor was consistently lower than that of the passive sensor for the same plant species/groups, differences were small and likely due to the differing light sources used. Thus, it is evident that GRVI and NDVI measured with active and passive sensors captured similar vegetation attributes of High Arctic plants. Hence, inexpensive Digital Cameras can be used with passive and active NDVI devices to establish a near remote sensing network for monitoring changing vegetation dynamics in the High Arctic.
Thomas W. Pike - One of the best experts on this subject based on the ideXlab platform.
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Using Digital Cameras to investigate animal colouration: Estimating sensor sensitivity functions
Behavioral Ecology and Sociobiology, 2011Co-Authors: Thomas W. PikeAbstract:Spectrophotometers allow the objective measurement of colour and as a result are rapidly becoming a key piece of equipment in the study of animal colouration; however, they also have some major limitations. For example, they can only record point samples, making it difficult to reconstruct topographical information, and they generally require subjects to be inanimate during measurement. Recently, the use of Digital Cameras has been explored as an alternative to spectrophotometry. In particular, this allows whole scenes to be captured and objectively converted to animal colour space, providing spatial (and potentially temporal) data that would be unobtainable using spectrophotometry; however, mapping between camera and animal colour spaces requires knowledge of the spectral sensitivity functions of the camera’s sensors. This information is rarely available, and making direct measures of sensor sensitivity can be prohibitively expensive, technically demanding and time-consuming. As a result, various methods have been developed in the engineering and computing sciences that allow sensor sensitivity functions to be estimated using only readily collected data on the camera’s response to a limited number of colour patches of known surface reflectance. Here, I describe the practical application of one such method and demonstrate how it allows the recovery of sensor sensitivities (including in the ultraviolet) with a high enough degree of accuracy to reconstruct whole images in terms of the quantal catches of an animal’s photoreceptors, with calculated values that closely match those determined from spectrophotometric measurements. I discuss the potential for this method to advance our understanding of animal colouration.