In order to construct a standard color image we need to have three basic colors available being red, green and blue.
This is achieved in a color CCD/CMOS sensor by applying tiny color filters to each pixel. These pixels are grouped into an array of 4 pixels and are color coded red, green, green and blue (RGGB). This is called a Bayer matrix/filter. As the human eye is most sensitive to green light, 2 green pixels are used in a group of 4. When the exposure is ended, the camera will automatically build up the color image from the info contained in all the separate pixels (this is mentioned for reference only as the technical details are beyond the scope of this article.)
Now lets go back to the histogram.
When looking at the histogram of a color image in Photoshop, it is by default set to show all three channels simultaneously (RGB). In order to process the image correctly we also need to view the data available in each channel separately.
This can be done by changing the channel from “RGB” to the individual Red, Green and Blue channels.
When imaging through a refractor or when filters are being applied, the data in these channels will usually not overlap.
An example of the different color channels not overlapping can be seen in the screen shown at left.
Part of stretching the image correctly is resetting the color balance in such a way that all 3 channels will overlap again.
The correction of the color balance is an almost final step in this process and will be addressed later in this tutorial.
The first step in processing basics is how to stretch the data available.
There are different methods available for doing this.
1) Level adjustments, this is called linear stretching.
With this tool the levels for pixel values can be remapped to a different value increasing the overall brightness of an image.
The drawback of using this method is that it will reset all pixel values in a linear way increasing the brightness level of each pixel in the image with an equal amount.
This will very likely cause the stars in the image to become oversaturated and appear as colorless hard white dots. This is not a very desirable effect and should be avoided if possible.
As level adjustments is not the best way of getting the data out of the image we will not be using in in this step of the processing (more on this later). Let’s have a look at the next method
2) Curves adjustments, this is called non-linear stretching.
As method 1, curves adjustments can also be used to remap the brightness values of pixels in an image, however it differs from the first method as it can be used in a non-linear way. With curves adjustments it is possible to remap pixel values containing the dark detail (low levels)in an image without affecting the pixels with the high brightness levels (stars) !
3) Before we start processing, first something about “clipping” (loss of data).
Clipping occurs when the pixel values in the image are modified, using one of the methods above, in such a way that part of the information is simply lost (forever !).
The most common error is to reset the blackpoint to a brightness level which is too high. For example if the blackpoint is remapped to brightness value 80, all pixels containing a lower brightness level (up to 79) are effectively removed from the image ! This results in an extremely dark background and is mostly done to compensate for local light pollution.
To the left is a good example of clipping which has occured in the dark detail of an image histogram. Instead of sloping back to zero value, the left part of the histogram is cut off. This results in the loss of data which can never be undone by any further processing !
All information contained in the pixels up to the remapped value is removed and it is not possible to bring this data back by any further processing whatsoever !
Although less common, the same error can of course also be made with remapping the white point. Setting this level to low will result in very bright (burnt out) colorless (white) stars. These stars look like almost stamped on instead of being part of the image.
The image at far right shows a good example histogram with highlight clipping (cut off at the right side).
Whenever you are processing an image, always keep checking the histogram to make sure that your actions will not cause any clipping in either the dark or light parts of the histogram.
Photoshop will always show a dynamic preview of the results on the histogram with each action taken.