I must admit to
feeling an element of 'interesting, but so what?' When I read through the notes
for this exercise. Sensor linear capture refers to the way a digital camera's
sensor records an image - basically in camera processing adjusts the tone curve
of the image, if it did not do this the image would appear too dark. The
exercise requires manipulation of an image's tone curve to simulate this and
then the application of the opposite effect on the manipulated image before
comparing the results.
Before beginning I
decided to do some research in the hope that this might shed some light on why
this exercise is important. Martin Evening in "The
Adobe Photoshop Lightroom 3 Book" (2010 Adobe Press) provides a
good explanation. He asserts that all digital images contain data that is a
linear representation of light hitting the sensor:
"As the
light intensity doubles, a sensor records a brightness level that is two times
higher...human vision perceives things quite differently from the way a sensor
sees and records light...our eyes compensate for increasing levels of
brightness in a non linear fashion...Our human vision system is able to adapt
to widely changing light levels by constantly compensating for such
extremes."1
The way a sensor
records light and represents image data looks very dark - even though it may be
perfectly exposed. Therefore, in order for a digital capture to look right to
our eyes the linear data must at some point be gamma corrected, that is effectively
lightened at the mid point.
The first paragraph
provides an indication of why linear capture is important, Fraser states that
by ignoring the way a digital camera captures an image you run the danger of
"failing to exploit the camera's dynamic range, and creating exposures whose
shadows are noisier than they need to be." He goes on to explain how
levels are distributed in an image using the example of a 12 bit image with
4096 levels and 6 stops of dynamic range:
"If a camera captures six stops of dynamic
range, half of the 4,096 levels are devoted to the brightest stop, half of the
remainder (1,024 levels) are devoted to the next stop, half of the remainder
(512 levels) are devoted to the next stop, and so on. The darkest stop, the
extreme shadows, is represented by only 64 levels."
When the cameras
processing is applied these levels are redistributed evenly across the image,
hence if a photograph is underexposed to maintain the highlight detail the
resulting raw conversion will have to open up the shadows and spread the
darkest 64 levels over a wider tonal range which runs the risk of exaggerated
noise and posterization. He suggests that the best exposure to achieve is one
where the highlights are as close as possible to blowing out without actually
doing so.
For the exercise I
chose an close up image of a lego figure that had a full range of evenly
distributed tones in the histogram:
No adjustments
Linear image - curve adjusted
For this image I
opened the photograph in Photoshop, converted to 16bit, made a curves
adjustment with a steep but smooth downward curve which resulted in an under
exposed image which simulates sensor linear capture.
'Restored' image - curve adjusted
For this image, I
opened the saved version of the simulated linear capture image again converted
to 16bit and made a curve adjustment opposite to that applied in the previous
image, that is pushed up to increase brightness in a smooth curve.
I compared this
image with the original until I achieved an equivalent result with a similar
histogram.
No adjustment detail
Restored curve detail
Finally I examined
the original and restored images at high magnification on screen. I found that
there was evidence of increased noise and posterization in the shadow areas of
the restored image. (The detail shots above show this a little although the effect
is not pronounced.) I concluded that by performing these extreme adjustments on
this image I was simulating trying to increase exposure on an underexposed
image. I have always held the view, picked up from where I do not know, that it
is important in digital photography to preserve highlight detail above all else
as that cannot be recovered in post processing. I always believed that an
underexposed image was preferable to an overexposed picture as underexposure is
easier to compensate for in software. I guess this remains true, however, I am
surprised at how few tones in an image are allocated to the dark and midtones.
Correct exposure it seems is more of a minefield than I first thought the key
to which I believe is understanding the image you want to create at the time of
capture, understanding which tonal values are most important to the pictures
success and using knowledge and experience to achieve this. In truth I rarely
worry about exposure, my camera usually does a pretty good job and I always
shoot raw so can alter the exposure in post processing if need be. This
exercise is beginning to make me understand how little I actually consider
exposure at the time of pressing the shutter and that I need to learn more
about how my camera behaves if I want to produce optimum results.
At the end of this
exercise I feel I understand more of how a digital camera's sensor captures an
image. The true importance of this however is something I am guessing will
become more significant as I explore the next few exercises which are concerned
with highlight clipping, noise and dynamic range.
1 p.629 The Adobe Photoshop Lightroom 3
Book: The Complete Guide for Photographers by Martin Evening (2010 Adobe Press)
+EV.jpg)
EVclipping.jpg)
