High Dynamic Range Imaging (HDR)
There are many resources on line where this topic is handled in depth but for the vistors to my site who are just "curious" I thought I would at least show you what I mean when I mention HDR in my captions.
The dynamic range or range of brightness that a modern digital cemera sensor can handle is about 6 f-stops or arguably 60% of what the human eye / brain combination can handle. The challenge for a photographer is to capture this high dynamic range scene and keep detail in the light and the dark area that they can see with their amazing visual senses.
This challeng is not new and not a digital phenomon. In fact digital cameras have a better dynamic range than film and photographers have been "tweaking" brightness and contrast in specific areas of tricky photos to maximise the perceived dynamic range for years. HDR is an approach for the digital age.
One increasingly popular way to deal with this is to use High Dynamic Range (HDR) techniques.
Example: Salmon Creek falls Big Sur, CA
This image of Salmon Creek Falls in California is about the best one can do with a single image. The best solution would be to come back on an evenly lit overcast day or better still an atmospheric early morning but this is what I had to deal with.
Mouse over the image to see the effect of HDR >>
The Water is in direct sunlight and the shadows are deep. Apart from coming back another day there's only one chance to capture anything. remotely work keeping.
The 5 images below show a variation of exposures which capture a different information in differently lit areas.
For example the left hand image is 2 stops under exposed (1/4 of the light the meter wanted) and still the water is bright.
On the far right, this image shows detail in the shadow areas but the water is horrible.
f22 0.1 sec (-2)
The process.
There are other ways to do this but a popular way is using Photomatix Pro software to combine the 5 images above. Once it has aligned and combined the information in the images the next step is called tone mapping. This takes the information of each pixel location and determines it's value by looking at the overall values of the image (loosely speaking). There are a number of somewhat confusing controls to use to modify the result and the only way to understand this is to play around with it.
The results is not to everyone's liking and in most cases not the classic photo that would achieved in optimum lighting but with subtle processing it can mean the difference between a decent image and no image.
