Exercise 13 - managing colour

There are a number of ways to 'manage colour' in Photoshop: -

1. Using Auto Colour via the menu bar: Image > Auto colour. This is the most radical option because its automatic and it discards image information - one click and its done.
2. Using Auto Colour via a Levels or Curves adjustment layer.
3. Using the 'eyedroppers' via a Levels or Curves adjustment layer.

All three options give similar results. My personal preference is option 3 because you can hope around the image selecting different coloured areas until you find one that give the desired result.

The three images selected were shot in JPEG. They have been colour corrected only and would all require further post processing prior to use.

Image 1 - blue colour cast

Image 1 - colour corrected

Image 2 - mixed lighting, flourescent and daylight

Image 2 - colour corrected

Image 3 - mixed lighting, soduim and halogen



Image 3 - colour corrected



Exercise 12 - managing tone

Starting point - an abstract image of yacht rigging taken through wet windscreen.

NEF in camera

Alterations made in RAW converter:

Ø         White balance changed to Cloudy

Ø         Exposure reduced by 0.3

Ø         Recovery set to 30

Ø         Blacks set to 31 (just prior to clipping)

Ø         Contrast set to 40 (increase of 15)

Alterations made in Photopshop:

Ø         Further adjustment made to black/white points using Red/Green/Blue sliders

Ø         Brightness unaltered

Ø         Contrast very slightly increased

Final version

Auto-corrected version

The auto correction function in Photoshop gives a darker and bluer image that one I created. In reality, this is probably a more accurate representation of the day/scene - it is certainly closer to the in camera version.

Exercise 11 - RAW versus JPEG

Reviewing both images 'as shot' the JPEG has a better overall colour and there is more definition in the shadows - the RHS wall inside the tunnel. By comparison, the RAW images feels a little bit washed out; the colours are not quite there - the green and the reds not quite so vibrant. Plus the RAW images has a reddish colour cast.



As shot JPEG

 

As shot RAW



Processing the images

Activity on JPEG: -

Ø         Levels adjustment

Ø         Curves adjustment - slight contrast

Ø         Cloned out rubbish

Ø         Slight burning of the tunnel walls - not very effective

Ø         Crop.

Activity on RAW: -

Ø         White Balance - increase by 200

Ø         Tint - decreased by 10

Ø         Recovery - increase by 40

Ø         Fill light - increase by 50

Ø         Blacks - decrease by 3

Ø         Brightness - decreased by 50

Ø         Contrast - increase by 5

Ø         Levels adjustment

Ø         Cloned out rubbish

Ø         Crop.

Having completed the processing on both images and listed the activities, it surprising how many elements of the RAW image were tweaked.

Processed JPEG

The JPEG is an acceptable photograph and a good representation of the scene, and the processed version is a significant improvement upon the 'as shot' version.



Processed RAW

However, the RAW image now has a much more autumnal feel; with the reds and browns really 'popping' and the long grasses on the RHS catching the winter sun. The shadows across the walkway are also much better defined.

RAW versus JPEG

It is a significant advantage to be able to alter the white balance of you shot and easily remove any colour cast that might occur.

With regards dynamic range, RAW enables the processing of the same image across a range of exposures. These versions an then be merged together without the any alignment problems. In theory this means that you camera has an infinite dynamic range.  

Exercise 8 - dynamic range

More sun, more exercises...

Location: a still cold, but snow free back garden.

ISO (lowest setting) - 200

Noise reduction - off

Highlight - white paper taped to the garden fence

Shadow - the bamboo bed

This seemed like a simple enough exercise, reading it; it also seemed simple when I took my camera into the garden and took a series of photographs. However, once inside doing the write-up I suffered brain freeze. It didn't make sense and I even re-did the exercise twice! I was still struggling but rather than grab the camera again I went for paper and tabulated all three sets of result. Suddenly it was simple again. I have no idea what happened, but it was very strange.



The bamboo bed

Exposure Values

Aperture	No highlights	Point 1	Point 2	Point 3	Point 4
f/6.3	1/1000	1/13	1/50	1/80	1/80
f/14	1/250	1/2	1/10	1/15	1/15
f/22	1/100	1/1.3	1/4	1/6	1/6

The yellow shaded column gives the exposure values at which there were no highlights showing on the piece of paper. The other columns show the values taken, from the specific areas of the photograph, using the cameras spot meter.

Using RAW to examine shadow detail

The image below shows the darkest area of the photograph lightened (exposure value of +2.85 in Photoshop) to show the fence panelling in the bamboos. It is very difficult to tell the difference between fence, bamboo and leaf.



Fence/bamboo shadow detail

Calculating the dynamic range of my D90

At f/6.3 exposure values from 1/13 through to 1/1000 giving 6.5 stops

At f/14 exposure values from 1/2 through to 1/250 giving 7 stops

At f/22 exposure values from 1/1.3 through to 1/100 giving 6.5 stops

According to the experts...

The forums differ in their opinions regarding the dynamic range of my camera, but it's somewhere between 7 and 9 fstops. Going by all the technical data presented on these websites I would guess that they applied a more rigorous set of test protocols than I did. I also suspect that it took them weeks to arrive at these results rather than a few hours. So all said and done I'm happy to accept that my results probably have a reasonable margin of error and that the dynamic range of my camera is between 7 and 9 fstops.

Exercise 7 - noise

It seems a long time since my last blog contribution - in fact its 4 weeks, a very long time. My principle issue being very grey, flat light and miserable weather; this weekend is the first time I've seen sun in I can't remember how long....

Weather: Nice blue sky and a low winter sun just hovering below the tree tops

Location: the study at my in-laws

It took a few attempts to compose the photograph and get the correct mixture of light and shadow. Plus, I didn't have my tripod with me so I had to create a makeshift platform using a stack of books secured to a stool with my belt.



Noise composition - ISO 200

Looking at the two extreme photographs (ISO 200 to 3200) it is difficult to distinguish much difference at normal print size, however, on closer inspection they are very different. Below are three areas at 200% magnification.  


Door at ISO 200

The door is white gloss, this close-up shows two blemishes:

a. A blue ink smear below the handle on the edge of the door

b. A dark paint chip in the bottom left hand corner.

Door at ISO3200

In this photograph it is still obvious that the door is white, however, the blue ink smear is significantly less defined because the noise has given the image a blue tinge - it almost looks as if the door is being viewed through wet glass. The paint chip is clearly visible as a chip rather than noise.

  

Stairwell at ISO200

The writing on the label in the guitar has clean edges and the strings are clearly defined. Similarly the architrave and the stitching on the quilt is crisp. In the deepest shadows the corner of the wall/ceiling can be easily seen.


Stairwell at ISO3200

The noise in this section of the image is easy to discern: the lettering on the guitar label is fuzzy; only part of the strings is defined; in addition the wood of the guitar is mottled. In the deepest shadows the vertical wall junction can be seen, but there is no definition at the ceiling. Overall the image is blotchy.



Pepper at ISO200

Again the stitching is clear and the rear 'edge' between Pepper and the quilt is easily observed. Whilst it is not possible to make out individual hairs, it is easy to see the ruffs in his fur around his chest.


Pepper at ISO3200

The stitching is obvious, but not crisp and the rear end of Pepper drifts into the quilt. The ruffs around his chest area cannot be seen, nor is it easy to make out his eyebrows (brown spots).


You will find it unsurprising that as the ISO is changed from 200 through to 3200 the noise gradually increases. Using this particular composition I found it very easy to discern the difference between noise and shadow, nonetheless, I do appreciate that on a subject less familiar it would not be at all easy.
I believe 'noise acceptability' would depend upon a number of things:

Ø        The knowledge of the audience in terms of the subject matter - most people have seen a dog, therefore a fuzzy dog is not a major problem. On the other hand, a fuzzy photograph of a rare animal would be unacceptable.

Ø        Professional versus family snaps - whilst everybody wants to shot sharp photographs there is a degree of tolerance when viewing your Uncles pictures of the last holiday. The same leeway would not be afforded to a professional whose services had been bought.

Ø        Available light levels - I believe it's much better to get a noisy image rather than no image.

Ø        Style and/or mood - noise/grain can be very effective when creating an atmosphere especially in portraiture and in certain urban settings.



Exercise 6 - seeing red

The exercise required: a scene which has a wide range of brightness - so I chose a cold and frosty morning with a bright winter sun hiding behind the trees.

Path around the lake

This image was taken facing into the sun and clearly suffers from burn out in and around the trees on the left hand side. But rather than being limited to just the 'disk' of the sun, the burnt out area extends a good way cross the sky. In this image it is possible to determine the area between nearly-white and total white - whether one could draw a line along the exact edge is doubtful.

When looking at a close up section of the image, even with the clipped version along side, it would be difficult to define the edge.

Whole image with clipping warning

The red above is the highlight clipping warning showing approximately half of the sky is burnt out. What cannot be clearly seen in this web-photograph is that there are also numerous little red dots in the grass where information has been lost. 


The sun

Conversely, the image above is a close up of the sun from the under exposed version of the photograph and this red spot is the limit of the burn out. However, to reduce it this far the rest of the image is very dark - to make this scene work as a photograph and number of different exposures would need to be blended together.

Information loss - close up of the trees at the end of the warehouse



Information retained

The two photographs above show the same trees - the first is from the over exposed image (+2), the second form the under exposed image (-2). Not only is branch detail retained, but also the crossing vapour trails.


Purple fringing

This purple fringing, also known as chromatic aberration and is caused because each colour of light has its own refractive index meaning it bends at a different angle. This results in some wavelengths hitting the camera sensor in exactly right and others being slightly off - either in front of, or behind. This fringing is most noticeable across the light/dark transition.

With regards colour saturation - the over exposed images look pale and washed out, whereas the under exposed images are dark (rather than saturated). Ironically, I often find that photographs taken in harsh light can look as though they very taken in hazy conditions.



Final image







Exercise 5 - the root of all noise?

Take any picture and convert it to 16 bits per channel.

Starting Cow

Add an adjustment layer and apply a curve to compensate for the camera's sensor linear processing algorithm.


Linear adjustment curve

Save the new darker image and compare it with the original.


Dark Cow

Application of the adjustment curve has resulted in the histogram being skewed significantly to the left hand side.
Now apply a second adjustment curve to return the image to its original state.


Gamma correction curve

This curve removes the skew applied to the histogram and the image looks normal again.

Final Cow

The histogram of the final image is not exactly the same as the original one, this is because the two curves I applied to the image were not exact opposites. 

Looking at the histograms of the images above: -

Ø         Dark cow - in the original image 'seen' by the sensor, the shadow information takes up approximately one fifth of the histogram area

Ø         Final cow - the same shadow information has been 'stretched and moved' and covers approximately two thirds of the histogram area.

Thus, it is hardly surprising that when this linear processing takes place, any noise in the shadow area is 'magnified' as the algorithm guesses to fill in the blanks and make up the new area under the curve.