Objective: To simulate a linear image by applying curves, replicating an image before in-camera processing.
A linear image represents an image before the camera has applied it’s in camera processing. Almost all digital cameras apply some processing. Film however, does not. The linear image appears much darker. A camera sensor’s response is called ‘linear’. The more light that falls on the sensor the stronger the response but at exactly the same rate from dark to very bright. This is different to how our eyes respond and how film responds. Our eyes cope with a wide range of brightness by compressing the light so that really bright seems less than it is. Film responds in a similar way but to a lesser extent.
Gamma correction is performed in the camera to produce the kind of image we expect to see. If this processing didn’t happen the image would look very dark and the histogram would show most of the tonal values to the left side. A typical gamma correction curve makes an image brighter.
Original image, converted to 16 bits per channel, curve applied:
As you can see, applying the curve has resulted in a much darker image.
As you can see from the above histogram – the levels are roughly based in the middle.
The liner’s histogram is grouped to the far left, something that we expect to see with a darkened image.
Liner image with curve applied (to re-create original image):
There is some noise already, but if you compare it to the below image (linear image with curve applied) you can see that the noise distortion is slightly greater in the corrected image.
This exercise has shown me that lightening an image to simulate in-camera processing exaggerates the noise levels, especially the noise in the shadowed areas. It has high lightened the importance of making sure my exposure is correct through camera settings rather than relying heavily on post processing software.