Demosaicking methods for Bayer color arrays

Ramanath, Rajeev; Snyder, Wesley E.; Bilbro, Griff L.; Sander, W. A.

doi:10.1117/1.1484495

Cited by 261 publications

(159 citation statements)

References 6 publications

(1 reference statement)

Supporting

Mentioning

151

Contrasting

Unclassified

Order By: Relevance

“…For the purpose of this paper, colour will be defined with 2 attributes; hue and saturation. Hue is the property of colours by which they can be perceived as ranging from red through yellow, green, and blue (Ramanath et al, 2002). Saturation (for our purposes) is the amount of white apparently mixed with a pure colour, for example, red can have white added to create pink.…”

Section: Use Of Colour On Mapsmentioning

confidence: 99%

Mapping the climate: guidance on appropriate techniques to map climate variables and their uncertainty

2012

View full text Add to dashboard Cite

Abstract. Maps are a crucial asset in communicating climate science to a diverse audience, and there is a wealth of software available to analyse and visualise climate information. However, this availability makes it easy to create poor maps as users often lack an underlying cartographic knowledge. Unlike traditional cartography, where many known standards allow maps to be interpreted easily, there is no standard mapping approach used to represent uncertainty (in climate or other information). Consequently, a wide range of techniques have been applied for this purpose, and users may spend unnecessary time trying to understand the mapping approach rather than interpreting the information presented. Furthermore, communicating and visualising uncertainties in climate data and climate change projections, using for example ensemble based approaches, presents additional challenges for mapping that require careful consideration. The aim of this paper is to provide background information and guidance on suitable techniques for mapping climate variables, including uncertainty. We assess a range of existing and novel techniques for mapping variables and uncertainties, comparing "intrinsic" approaches that use colour in much the same way as conventional thematic maps with "extrinsic" approaches that incorporate additional geometry such as points or features. Using cartographic knowledge and lessons learned from mapping in different disciplines we propose the following 6 general mapping guidelines to develop a suitable mapping technique that represents both magnitude and uncertainty in climate data:-use a sensible sequential or diverging colour scheme; -use appropriate colour symbolism if it is applicable; -ensure the map is usable by colour blind people; -use a data classification scheme that does not misrepresent the data;-use a map projection that does not distort the data -attempt to be visually intuitive to understand.Using these guidelines, we suggest an approach to map climate variables with associated uncertainty, that can be easily replicated for a wide range of climate mapping applications. It is proposed this technique would provide a consistent approach suitable for mapping information for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5).

show abstract

Section: Use Of Colour On Mapsmentioning

confidence: 99%

Mapping the climate: guidance on appropriate techniques to map climate variables and their uncertainty

2012

View full text Add to dashboard Cite

show abstract

“…For the sake of comparison, we also implemented, in addition to the proposed method, another 5 techniques of multispectral demosaicking including bilinear interpolation [18], channel difference interpolation extended from the color difference method [13], LMMSE method [7] based on constant difference, binary tree based demosaicking [10] and discrete wavelet transformed based approach [15].…”

Section: Resultsmentioning

confidence: 99%

A Linear Interpolation Algorithm for Spectral Filter Array Demosaicking

Wang¹,

Wang²,

Hardeberg³

2014

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Linear interpolation methods have the characteristics of low computational complexity which makes them widely developed in CFA (color filter array) demosaicking. However, the trichromatic nature of colour images enables CFA demosaicking algorithms to take advantage of the luminance-chrominance representation to interpolate the colour planes efficiently and effectively. It seems, however, this does not apply to multispectral images in a straightforward manner. In this paper, we first propose a linear interpolation method for SFA (spectral filter array) demosaicking drawing on the mathematical analysis of mosaicking, demosaicking processes and the idea of residual interpolation. We then compare the performance of the proposed method with that of five other techniques by means of the SSIM index. The result shows that our new algorithm has a good performance with less computing time.

show abstract

“…Since the algorithm employed to detect particle center considers grayscale images as input, Bayer images need to be converted in an intermediate step to RGB color images using a bilinear interpolation. This is performed with a demosaicing algorithm [17]. After that the images are converted to grayscaled ones using equal weights for red, green, and blue components to compute the intensity value.…”

Section: Image Pre-processingmentioning

confidence: 99%

Improved 3-D Particle Tracking Velocimetry with Colored Particles

Bendicks¹,

Tarlet²,

Roloff

et al. 2011

JSIP

View full text Add to dashboard Cite

The present work introduces an extension to three-dimensional Particle Tracking Velocimetry (3-D PTV) in order to investigate small-scale flow patterns. Instead of using monochrome particles the novelty over the prior state of the art is the use of differently dyed tracer particles and the identification of particle color classes directly on Bayer raw images. Especially in the case of a three camera setup it will be shown that the number of ambiguities is dramatically decreased when searching for homologous points in different images. This refers particularly to the determination of spatial particle positions and possibly to the linking of positions into trajectories. The approach allows the handling of tracer particles in high numbers and is therefore perfectly suited for gas flow investigations. Although the idea is simple, difficultties may arise particularly in determining the color class of individual particle when its projection on a

show abstract

Demosaicking methods for Bayer color arrays

Cited by 261 publications

References 6 publications

Mapping the climate: guidance on appropriate techniques to map climate variables and their uncertainty

Mapping the climate: guidance on appropriate techniques to map climate variables and their uncertainty

A Linear Interpolation Algorithm for Spectral Filter Array Demosaicking

Improved 3-D Particle Tracking Velocimetry with Colored Particles

Contact Info

Product

Resources

About