All Things Color for Film and Digital Cinema
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Posts Tagged ‘color reference’

Happy Feet Two – 3D

Happy Feet Two

2011

Director: George Miller

Studio: Warner Brothers

Senior Digital Intermediate Colorist : Adrian Hauser

Graded Stills from the Teaser Trailer


Protected: DCI – Digital Cinema Projection Reference

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Video Waveform Visualization and Creation

As an addition to the prior post on waveforms here we examine a more visually descriptive way of showing how a video waveform is created and therefor how it can be interpreted.

Fig:1 Waveform and Live Image

Above we can see a standard Live Video Feed and its represented waveform.

Below I have created a 3Dimentional Luminance map of the same live feed. In this representation every pixel on the image is represented on the z-axis as a luminance value bw 0 and 1023 video code values. The ‘lighter’ or more intense the pixel value the higher it appears on the z-axis.

Fig: 2 Luminance Relief Map  Face On

As I rotate this image in 3D space, around the y-axis, you can see the luminance values more clearly represented as a Height map in the 3 Dimensional space.

Fig: 3 Luminance Relief Map Rotated 45 Degrees

When finally rotated a full 90 Degrees we end up with the Waveform interpretation.

Fig: 4 Luminance Relief Map Rotated 90 Degrees

Adrian Hauser


Waveform Vs Histogram interpretation in Digital Cinema Cameras

Understanding how to read Histograms present on many new digital cinema cameras can be tricky and are easily misenterpreted.

For analysis, I will use the below still from the film Daybreakers as reference.

Ethan Hawke in "Daybreakers" (2010)

The following snapshots have been taken using DpxRead available on the Panavision website.

Immediately we can see that there is a massive difference in the way these two images are represented in each of the graphical/statistical graphs.

Histograms represent the volume/percentage of light levels exposed within a particular image. The resulting graph shows the distribution/intensity plot of those levels.

Histogram Exposure

The above image reference image  is quite ‘moody’. The histogram shows us this quite literally but surprisingly shows nothing of where the midtones sit. This is because Histograms work with percentages and Ratios of light. If for the most part an image is dark, say 60% of the overall area , then the rest of the histogram has to be interpreted with the remaining 40 percent of image area. For that reason the intensity represented by the histogram for the remaining light values is visually a lot lower than the Dark spike shown in our reference.

To better show the way a histogram graphs an images lightness values I have put the below gradient into the scopes.

Linear Grayscale Ramp

We can see that because there is an even amount of each light level within the gradient image the Histogram shows an even intensity/distribution of each ‘level’.

Video Waveforms on the other hand give us a lot more visual information with which to evaluate your exposure and contrast ratio. As well as showing us the distribution of light values the graph is also plotted across the horizontal plane of the image. With this additional ‘axis’ one can easily determine where within the frame a particular item sits in its digital exposure value. This makes it easy to find for example the exposure of someones skin tone in relation to the background subject matter.

Histograms are Cheap and Easy to display from a programmers POV but in my opinion are quite useless in representing photographic content and should not be used for indepth exposure analysis.

Adrian


18 Percent Grey …. “Middle Grey” and Magic Numbers

 

    For a while I have been pondering the function of the 18 percent grey card. Why 18%, what is its historical reference…ect.

    After a lot of reference reading I came up with the following ….

    Traditionally 18 % refers to the statistical average reflectance of a photographed scene. ‘Normally’ exposed skin tones also generate an average incident light reading of about 18%.

    Photographically, if you were to make a set of 11 patches starting with 100% reflectivity and each subsequent patch was halved in reflectance, you would end up with a logarithmic scale where the light intensity is being halved each patch. The seventh step, middle grey, would yield a photographic Status M Neg density value of 0.7

    Using our Density math described in previous posts we know Transmission = 1/10^Density   

    Therefor    T=1/10^0.7= 0.18      AND       Transmission is directly proportionate to Luminance L*. Not boring you with the math the result is 49.496.

   So    0.7 Density = 0.18 Transmission = 50% Luminance(L*).

 

 

Fig.A - Status M against Status A Density

Fig.A - Status M against Status A Density

 

 

  Interestingly If we map our 21 step sensitometry readings of a 21 strip grey scale test wedge over Neg and Print densities we see that 0.7D is the cross over point !   See Fig.A

 

 

Fig.C

Fig.B

 

 

 

 

Looking at the image below, Fig.C, you will notice that this point of around 18 % grey is the mid point at which the cineon Log file is expanded when overlayed with a Print emulation 3DLookUp table. Both Mid Grey LAD Patch’s are almost identical as seen on the corresponding waveform Representations. 

 

 

18percent

Fig.C

 

Looking at the graph in Fig.C one can also see the reference point of 18 % on each of the mapped targets averaging around 50% luminance. Interestingly with this chart I have mapped Cineon Log levels against the 2.2 and 2.5 video gamma transfer functions and CIE Luminace L* values. They are all relatively close to each other in their Logarithmic encoding. I can see im going to have to rewrite this as its going to get messy from about here on in, although quite fascinating. 2.5 gamma looks like its the best match for CIE L* but somehow we got stuck with 2.2. Near enough is good enough I guess. It was decided back in the 8Bit video days that to help save on visual data that video/TV could also have a perceptual gamma encoding, once again mimicking the eyes response to nature. A gamma of 2.2 was decided apon.  

 

 

Adrian


China Girls .

 

China_girl7

China_girl7

For a bit of fun and curiosity I will update this post over time with images of China girls. China Girls are used to adjust and check printer density.

They provide subjective and objective colour and gray scale patches.

These patches can be read on Densitometers to confirm the process. They are a standard laboratory test film usually incoporating a face and a greyscale; used for printer line-up.

 

 

 

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Color Blindness….. and color fatigue

 

An image from the ishihara test for color blindness

An image from the ishihara test for color blindness

Color Blindness and color fatigue has been the cause of quite a few conundrums in the grading suite.

We have all debated with friends, at some point in our lives, the perception of color between each other. “Do you see the blue of the sky the same way I do?” Someone who has been color blind all their lives takes their perception of color as gospel. 

What’s interesting is when grading a project over a few hours without a break or watching a feature film your internal reference point of what is a correct Balanced Image easily shifts. Technically it only takes 40 minutes for ones Color reference to become ‘reset’, taking on what is presented to you as the new correct reference. In a dark theatre without any external color reference point this is very easy. In this way I find TV grading and feature film grading two quite different beasts. In a darkened theatre our perception of subtle  changes in dark tones is much more than that of a typical television viewing environment where traditionally images are ‘pumped’ to jump off the screen.  

With this in mind can one be trained to be temporarily color blind in 40 mins?

I am currently making up some look up tables that emulate different color vision deficiencies. I’d love to use them some day in a film where perhaps one of the characters is color blind.

An interesting site is this one where you can type in a web address and it will show you how that page or image is percieved by someone deficient in say, Red/Green color.

Here is the site to go to to check your color vision.

Ishihara Test

Adrian