Colour to grey scale and related transforms
Lead Research Organisation:
University of Bradford
Department Name: Faculty of Life Sciences
Abstract
Every year, millions of poor grey scale reproductions of colour images are made. Through our research we aim to make millions more good grey scale prints.It is now increasingly common to capture images using colour digital cameras and display them on colour monitors or using colour inkjet printers. However, there are still many occasions when colour images are reproduced in grey scale. The use of black and white printers, photocopiers and fax machines is still an every day occurrence. Unfortunately, the conversion of colour images to their grey scale equivalent, either by these devices, or through other means, often results in a poor reproduction of the images. The aim of our research is to develop a method to derive the best possible grey scale reproduction of a colour image, by a careful consideration of the limitations of our own visual system, and by exploiting the underlying physics of colour image formation. Usually, the colour at a given image point is coded by three numbers, and in the grey scale transformation these three numbers are reduced to just one grey value. More generally, colour information might be coded using N (where N>3) numbers, and in this case it is useful to be able to derive methods to reduce these N numbers to 3, or fewer, so that the N-dimensional information recorded can be displayed on conventional imaging technology. We will extend our research to also consider such cases. Our research will lead to the improved reproduction of images on grey scale devices (e.g. improved photocopying and faxing) as well as providing us with the ability to better visualise the information contained in, for example, satellite images. We also expect that it will be possible to exploit the technology we develop to make colour images that can be viewed without error or confusion, by colour-blind observers. In addition, the work will lead to improvements in existing image-processing algorithms, and to a better understanding of how our own visual system perceives colour and brightness information.
Publications

Bloj M
(2016)
Handbook of Visual Display Technology

Bloj M
(2010)
What do we know about how humans choose grey levels for images?
in Journal of Vision

Bloj M
(2010)
Preferred greyscale versions of coloured images: Human vs machine
in Journal of Vision



Connah D.
(2012)
Human Assignment of Grey Levels Depends on Scene Complexity

Connah D.
(2008)
An investigation into perceptual hue-ordering

Connah D.
(2008)
A novel approach to hue ordering
Description | SpectralEdge Image Visualisation |
Amount | £63,742 (GBP) |
Funding ID | EP/I028455/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2010 |
End | 08/2011 |
Description | Xerox Corporation |
Organisation | Xerox Corporation |
Department | Xerox Research Center Webster |
Country | United States |
Sector | Private |
PI Contribution | Regular phone meetings to inform the partner of progress and new developments. We visited the research partner for 1 week, giving a talk and performing a psychophysical experiment at their facilities. |
Collaborator Contribution | Guidance and advice throughout the project through regular phone meetings. Facilities to perform a psychophysical experiment. |
Impact | No specific outcomes are related to this collaboration. The collaboration was not multidisciplinary, but the partners offered a commercial perspective on our research, and applicability in real-life situations. |
Start Year | 2006 |
Title | Image reconstruction method |
Description | The technology encompasses a method and system for producing a scalar image from a derivative field. A function class c is selected, where all members of the class c are functions which map each vector of the vector image to a unique scalar value. A function f is selected from the class c which maps the vector image to a scalar image, the derivative of which is closest to the derivative field. The scalar image is generated from the vector image by using f to calculate each scalar value in the scalar image from a corresponding vector in the vector image. |
IP Reference | GB0914603 |
Protection | Patent application published |
Year Protection Granted | |
Licensed | Commercial In Confidence |
Impact | N/A |
Title | METHOD AND SYSTEM FOR GENERATING ACCENTED IMAGE DATA |
Description | A method and system for producing accented image data for an accented image is disclosed. The method includes decomposing each of a first and a second image into a gradient representation which comprises spectral and edge components. The first image comprises more spectral dimensions than the second image. The edge component from the first image is combined with the spectral component from the second image to form a combined gradient representation. Accented image data for the accented image is then generated from data including the combined gradient representation. |
IP Reference | US2011052029 |
Protection | Patent granted |
Year Protection Granted | 2011 |
Licensed | Commercial In Confidence |
Impact | N/A |
Company Name | Spectral Edge |
Description | Spectral Edge has developed image processing technology that focuses on colour clarity. |
Year Established | 2011 |
Impact | July 18th 2014, Visual Clarity for All : Spectral Edge Announces Seed Investment Round Led by the Rainbow Seed Fund and ICENI. |
Website | http://www.spectraledge.co.uk |