colour physics 101

kindle_colourphysicsfaq

Download my colour physics FAQ e-book for the Kindle here.

Also available as a physical book from Amazon.

  • What is colour?
  • How does colour vision work?
  • Why is the sky blue?
  • What is the colour spectrum?

The answers to these and many other related questions about colour physics are each provided in a short and easy-to-understand form. Will delight and entertain colour professionals and curious members of the public.

Welcome to my blog

I am passionate about sharing my knowledge about colour to anyone who is prepared to listen. I work as a professor of colour science at the University of Leeds, in the School of Design, but I have held academic posts in departments of Chemistry, Physics, Neuroscience, and Engineering. Sounds like a mixed bag, but my interest was colour chemistry, colour physics, colour neuroscience, colour engineering and colour design. You see I have come to believe that colour is the perfect meta-discipline and that to understand colour you need to be able to understand (but not necessarily be an expert in) different fields of knowledge.

One way to use this blog is to just browse through it and dip in here or there. However, another way is to click on one of the categories (that interest you) such as culture, design, fun, and technology and see posts in that area. You can find the categories on the right-hand side of the page if you scroll down.

You can also comment on the blogs. I really like this, even if you disagree with me. Someone once said to me if you put ten colour physicists in a room and ask them a question (presumably about colour physics) you’ll get 10 different answers. Well, I guess not all of you reading this are colour physicists. Given our different interests and backgrounds, and given the complexity of colour, it’s not surprising that we will disagree from time to time. And that is rather the fun part.

If you have a technical question you’d love me to answer you can click on Ask Me and post it there. You can also email me at s.westland@leeds.ac.uk

The Wizard of Oz

This week I had to mark about 50 essays that had been submitted for the Colour: Art and Science module I teach at the University of Leeds. One essay looks rather like another after the first 10 or so. So it was a delight to discover that one student had decided to focus on a movie – The Wizard of Oz – and demonstrate her understanding of colour by analysing this classic movie.

It reminded me of a story my mother told me. When she went to see the Wizard of Oz in the cinema (she would have been about 8 at the time) she had never seen a colour movie before. She was so much looking forward to this new-fangled and exciting technology. It’s hard to imagine how exciting that would have been – if every movie you had ever seen had been in black and white!!

Well, imagine her disappointment when the movie started and the movie was black and white after all. For those who don’t know, the movie starts off in black and white (in the Kansas scenes) and only turns coloured when Dorothy is whisked off by the tornado and dropped off in the land of Oz. It must have been a wonderful moment when the screen just turned full colour!!

Indigo – a colour of the rainbow?

From time to time I come across web pages and groups of people who get irrate about indigo being in the rainbow. There is even a facebook group called “Get Indigo out of the rainbow”. It was Newton who suggested that the rainbow contains seven colours: red, orange, yellow, green, blue, indigo and violet. It has been suggested that, at the time, Newton was trying make some anology with the musical scale and the octave (with its seven intervals) and hence was keen to identify seven colours in the rainbow or visible spectrum. Many modern commentators claim that only six distinct colours can be observed in the rainbow.

Interestingly, the facebook group referred to above would like to eject indigo from the spectrum on the basis that it is not a primary or secondary colour but rather a tertiary colour. The group shows the following colour wheel:

colour wheel

In this so-called painters’ wheel the primary colours are red, yellow and blue and the secondary colours are orange, green and violet. It is argued that since six of the colours in the rainbow are primary or secondary colours in the colour wheel and indigo is not, then indigo has no right to be there. This is wrong on so many levels it is hard to know where to start.

The first thing I would have to say is that this argument seems to ignore the difference between additive and subtractive mixing. Additive mixing – http://colourware.wordpress.com/2009/07/13/additive-colour-mixing/ – describes how light is mixed and the additive primaries are red, green and blue. The additive secondaries are cyan, magenta and yellow. Orange is not in sight – and yet surely if we are to make an argument for inclusion in the spectrum based on primaries (and/or secondaries) then it is the additive system that we should be using since the spectrum is emitted light.  

The optimal subtractive system primaries are cyan, magenta and yellow (with the secondaries being red, green and blue) though the artists’ colour wheel (which is like the painters’ wheel above) has red, blue and yellow as the primaries. 

In my opinion there is nothing special about the colours that we see in the spectrum. Indeed, orange is clearly a mixture of red and yellow and does not seem to me to be a particularly pure colour. I just do not think that arguments to exclude indigo from the spectrum based upon colour wheels or primary colours is valid. That said, I have already mentioned that many people believe that indigo cannot be seen in the spectrum as a separate colour; but this is a phenomenological observation not dogma. I am one of those who believe that indigo and violet cannot be distinguished in the spectrum and therefore I agree with the aims of the facebook group even if I do not agree with their arguments.

The really interesting question is why we see six (or even seven) distinct colour bands in the spectrum when the wavelengths of the spectrum vary smoothly and continuously? I have postulated some possible reasons for this in an earlier post – http://colourware.wordpress.com/2009/07/20/colour-names-affect-consumer-buying/ – but it is far from a complete and convincing explanation. It may explain why we see distinct colours in the rainbow, but why six and why those six in particular. Comments on this would be very very welcome.

colour helps you sleep

cat-686827_640

Light in our natural environment tends to be bluer first thing in the morning and redder at dusk.

Researchers from the University of Manchester looked at the change in light around dawn and dusk to analyse whether colour could be used to determine time of day. They constructed an artificial sky beneath which they placed mice and they then measured the body temperature of the mice for several days and their body temperature was recorded. The highest body temperatures occurred just after night fell when the sky turned a darker blue – indicating that their body clock was working optimally. When just the brightness of the sky was changed, with no change in the colour, the mice became more active before dusk, demonstrating that their body clock wasn’t properly aligned to the day night cycle.

According to Dr Timothy Brown: “This is the first time that we’ve been able to test the theory that colour affects the body clock in mammals. It has always been very hard to separate the change in colour to the change in brightness but using new experimental tools and a psychophysics approach we were successful. What’s exciting about our research is that the same findings can be applied to humans. So in theory colour could be used to manipulate our clock, which could be useful for shift workers or travellers wanting to minimise jet lag.”

why people have started to buy brown cars again

3-Beige-Golf-Rex

Interesting article by Ian Johnston in The Independent today about consumer colour choices for second-hand cars in the UK. Bucking the recent preference for silver, black and whit, the top 10 list of colour schemes includes green, beige, yellow and gold – colours that we associate with the 70s.

Please see the original article for further information.

I like pink

i_like_pink_tshirt-rbf59cb63cffb443d83ecd808c2486cf1_804gs_324

Pink is one of my favourite colours. Generally, however, if you ask people what their favourite colour is, the most frequent response is blue irrespective of gender, age or culture. Adults, that is. Because most young girls prefer pink. There is a huge commercial machine that pushes girls towards pink and boys towards blue. I support the Pink Stinks campaign which I blogged about in 2009, but I fear its chances of success are slender.

In my 2009 I linked to a BBC article that noted that pink for girls and blue for boys was not always the case. People cite the Ladies’ Home Journal from 1918 saying:

There has been a great diversity of opinion on the subject, but the generally accepted rule is pink for the boy and blue for the girl. The reason is that pink being a more decided and stronger colour is more suitable for the boy, while blue, which is more delicate and dainty, is prettier for the girl.

For some reason I always thought that it was the association of blue with the British Navy in the first world war that started the association of blue with boys. But today I read an article that suggests that the association did not start until the 1950s!! Apparently in 1927, Time magazine surveyed 10 major departments stores across the country about how each store associated pink and blue with boys and girls. The results showed that most children dressed in gender-neutral clothing and typically wore white because it was easy to bleach and keep clean. It wasn’t until the 1950s that pink became a female colour according to Estelle Caswell. Read all of what Estelle had to say here.

Egyptian Blue – the first synthetic pigment

1.78x1.17, 600 dpi scan

The first synthetic pigment – Egyptian Blue – was made by the Egyptians around 4500 years ago. A technique developed by scientists at the British Museum has allowed them to discover traces of Egyptian blue on ancient objects that no longer have their original paint finishes intact. Before the Egyptians learned how to make a synthetic blue pigment from sand and copper the main blue pigment was obtained from the mineral lapis lazuli, first found in Afghanistan about 4500 BC. Extracting blue from lapis lazuli was extremely expensive.

Blue remained an expensive pigment however and came to symbolise truth, peace, virtue and authority in fine art. Images of Mary usually showed her wearing a blue robe. Blue was used for symbolic reasons. Cheaper blue pigments became widely available in the modern era of synthetic pigments.

Further details can be found here.

measure colour with your smartphone

node

This looks interesting. Node is a way to add sensors to your iOS device. It allows you to measure all sorts of things, including colour if you have the node+chroma combination. The node costs about £100 and the additional sensors cost about £50 each. I am not sure how much the chroma sensor costs.

You can find further details here – http://variableinc.com/chroma-contact/

accurate colour on a smartphone or tablet

Electronic displays can vary in their characteristics. Although almost all are based on RGB, in fact the RGB primaries in the display can vary greatly from one manufacturer to another. Colour management is the process of making adjustments to an image so that colour fidelity will be preserved. In conventional displays – desktops and laptops – the way this is achieved is through ICC colour profiles. Colour profiles store information about the colours on a particular device that are produced by RGB values on that device. So to make a display profile you normally need to display some colours on the screen and measure the CIE XYZ values of those colours; you then have the RGB values you used and the XYZ values that resulted. The profiling software can use these corresponding RGB and XYZ values to build a colour profile so that the colour management engine knows how to adjust the RGB values of an image so that the colours are displayed properly. Building a profile often requires specialist colour measurement equipment – though this can often be quite inexpensive now. If you are using your desktop or laptop display and you have never built a profile then you are probably using the default profile that was provided when your display was shipped. The default profile will ensure some level of colour fidelity but particular settings (such as the colour temperature or the gamma) may not be adequately accounted for. If you want accurate colour then you should learn about colour profiling.

It all sounds simple except for the fact that ICC colour profiles are not supported by iOS or Android operating systems on mobile devices. I find this really surprising but that’s how it is for now. Maybe it will be different in the future.

This means that ensuring colour fidelity on a smartphone or tablet is not so straight forward. So what can you do?

Well, there are two commercial solutions to this problem that I am aware of. They are X-rite’s ColorTrue and Datacolor’s SpyderGallery. ColorTrue and SpyderGallery are apps that will use a colour profile and provide good colour fidelity. These are great solutions. Perhaps the only drawback is that the colour correction only applies to images that are viewed from within the app. Having said that, they allow your standard photo album photos to be accessed – but the correction would not apply, for example, to images viewed using your web browser. This is why a proper system implemented at the level of the operating system would be better, in my opinion.

There are two alternatives. The first would be to implement your own colour correction and modify the images offline before sending them to the device. This would not suit everyone – the average consumer who just wanted to look at their photos for example. But it is what I typically do here in the lab if I want to display some accurate colour images on a tablet. But if you were a company and you wanted to display images of some products for example – it might be a reasonable approach. It has the advantage that the colour correction will work when viewed in any app on the device because the colour correction has been applied at the image level rather than the app level. But it does mean you need to do this separately for each device and keep track of which images are paired to each device. This is ok if you have one or a small number of devices but maybe not so good if you have hundreds of devices.

The second alternative would be to build your own app. If you want to do things with your images that you cannot do in ColorTrue or SpyderGallery or if you have lots of devices and you can’t be bothered to manually convert the images for each device, then you could install your own app that implements a colour profile and then does whatever else you want it to do.

curved displays are the future

samsungevent

Yesterday I spoke an an event to launch Samsung’s latest curved screen displays. The technology is really gorgeous and everyone who attended was wanting one of the new displays after seeing them.

I am convinced that curved screens will become ever more popular in the future because not only do they look good but they offer serious advantages for users who undertake intensive tasks – the sort of tasks that need a large desktop display rather than a mobile device. When it comes to desktop displays it is really quite simple – bigger is better.

Many people – and I am one of them – are what is known as ‘double screeners’. I have two screens attached to my desktop and my operating system is spread seamlessly across them because I wanted more screen space to work in. I recently carried out a survey – you can find more details here – which showed that 38% of British office workers are already using two or more screens attached to their desktop computers.

Of course, in an ideal world one very large screen would be better than two smaller screens. But there is a problem with most flat-screen technology which is that the LED/LCD pixels emit light straight out but emit a lot less light at an angle to the screen. This means that you look at a large flat screen the light reaching your eye from the edges of the screen is a lot less. Not only that but, because you are looking at the screen at an angle, text and other fine details can be distorted at the edge. Curved displays get around this problem and I am hoping to replace my two flat screens soon with a single Samsung curved display.

With a curved display the distance from the eye to the screen is the same across the whole display and the angle of view is also constant. Not only does this solve the colour and acuity problems I just mentioned but it means that users need to need fewer eye and neck movements. Given that many of us spending longer using a display than we do actually sleeping this could have a big effect on user well-being.

Our survey also showed that about 60% of office workers think it is important that the office technology they use looks good. This can help to motivate them and help them to feel good about themselves. The new Samsung curved displays certainly will satisfy these people.

Incomplete pair comparison

One of my big academic interests is scaling perceptual phenomena. That is, we take some physical stimuli (for example, a set of sounds of varying intensity/volume) and then we want to know how loud they are perceived to be by people. This allows us to build a relationship between the physical stimulus (in this case intensity) and the perceptual stimulus (in this case loudness). The same idea could be used to scale largeness, smallness, colourfulness, whiteness, lightness, heaviness, sweetness etc. It’s not always a -ness. But it usually is.

There are a great many techniques to scale perception. You can just ask people, for example, to assign a number. For example, you play a sound and ask them to rate how loud it is on a scale, say, from 0 to 100. This is called Magnitude Estimation (ME). It’s a perfectly good technique but it has limitations and one of these is that it can be quite difficult for the participant. And, say, the first stimulus seems really loud and they assign it a loudness of 90; then it turns out that all the subsequent stimuli are louder – then all their estimations will be squeezed in the 90-100 range, which is not ideal. Consequently, in the ME technique we often have so-called anchors – that is, example stimuli at each end of the scale.

An alternative technique is called paired comparison (PC). In this we might have, for example, five stimuli A, B, C, D and E and we present them in pairs and ask the participants which one is louder (or whiter or yellower etc.). The total number of paired comparisons is 10 in this case which is quite manageable. From the results of these paired comparisons it is possible to estimate a scale value for each of the stimuli where the scale value will be an interval scale of loudness (or whiteness or yellowness, etc.). This is a really nice technique and there are quite a few papers that claim that PC is more reliable than ME, for example. However, when the number of stimuli is large the number of pair comparisons becomes huge and the the task is not practicable. When this happens it is possible to undertake so-called incomplete pair comparison where we only present some of the possible pairs to the participants. The question is, however, what proportion of the pairs should be present for the PC experiment to be reliable?

This was the question that Yuan Li and I asked each other during her doctoral research. We undertook a large-scale simulation of a PC experiment. I won’t go into the details here. The method and results have just been published in the Journal of Imaging Science and Technology (JIST). You can see the paper here.

However, I show below the key table from the research which I think might be of interest to other people who are undertaking, or planning to undertake, an incomplete PC experiment.

table

This table shows the number of stimuli that are being compared along the top. Down the left-hand side are the number of observers taking part. The figure in the corresponding row and column shows the per cent of pair comparisons that need to be carried out to get robust results that would be similar to those you would get if you did the full PC experiment. So, for example, if you 20 samples and 15 participants then you need to half of the possible comparisons. For 20 samples there are 190 comparisons so you would need to 95 of them (which could be selected randomly).

I should point out that there is a caveat that needs to be considered. This work is only valid if the observers can be considered to be stochastically identical. If we ask people to rate samples for loudness, or whiteness, or heaviness, for example, I think this assumption is justified. However, if we were asking people to scale how beautiful people’s face were, for example, – an experiment reminiscent of the early facebook experiment by Mark Zuckerberg – then observers could differ wildly in their judgements. One participant may rate as most beautiful a face that another participant rates as the least beautiful. Because of the assumptions that we made in our modelling we cannot predict the proportion of pair comparisons that would be needed in a case like this. We are thinking about it though.