benz

Dynamic Range and a Different Kind of Analyzer

Blog Post created by benz on Oct 13, 2016

Originally posted May 22, 2015

 

Signals and noise in the optical realm

It looks like I’m not the only one who finds myself wrestling with noise quite a bit, and recent developments in digital photography spurred me to briefly depart from my usual focus (pun intended) on the RF world .

I’m not departing very much, though, because digital photography can be seen as a two-dimensional type of signal analysis. Not surprisingly, many of the electrical engineers I know have at least a hobbyist interest in photography, and for quite a few it’s more than that. Our engineering knowledge helps a lot in understanding the technical aspects of making a good photograph, and I’d like to explain one recent development here.

The megapixel race in digital imaging is abating, perhaps because sensor resolution now exceeds the performance of some lenses and autofocus systems. I see this as a positive development, shifting attention to other important factors such as sensitivity or low-light performance. Sensitivity is as critical as resolution in those all-too-common situations when light is scarce and camera shake or subject movement render long exposures impractical.

Camera sensitivity goes back to the days of film, and the parameter called ISO quantifies it. In film, this sensitivity is related to grain size, but in digital imaging it’s more closely related to gain applied to the signal coming from the sensor. In an interesting correspondence, high ISO settings in a digital camera will produce noisier images that echo the coarser grain of high-ISO film.

This dance of gain and noise is awfully familiar to all of us, and I wonder if we should be suggesting to the digital imaging folks some sort of measure based on noise figure.

Today’s best digital cameras offer impressive sensitivity, driving new emphasis on a parameter near and dear to all of us: dynamic range. In the last several years, dramatic improvements in dynamic range have made cameras that are almost ISO-invariant, and this provides a big benefit for photographers.

Here’s my crude attempt at a graphical representation of the situation.

This digital image “tone flow” diagram shows how a scene with wide dynamic range may be clipped and compressed in the process of capture and conversion to JPEG format. If you rotate this diagram 90 degrees to the left, it corresponds well with the amplitude levels of an RF signal measurement.

This digital image “tone flow” diagram shows how a scene with wide dynamic range may be clipped and compressed in the process of capture and conversion to JPEG format. If you rotate this diagram 90 degrees to the left, it corresponds well with the amplitude levels of an RF signal measurement.

For RF engineers, this is familiar territory. Wider dynamic range in a measurement tool is always a good thing, and sometimes there is no substitute.

Taking advantage of this ISO-invariance is simple, though perhaps not intuitive. Instead of exposing normally for a challenging scene, the metering is set to capture desired highlights as a raw sensor output—not JPEG—file format. This may leave parts of the scene apparently underexposed, but the raw format preserves the full dynamic range of the sensor, and this allows all the tones to be brought into the desired relationship for the end result. In an ISO-invariant camera deep shadows may be brought up several stops or more without significant noise problems.

The result is more easily demonstrated than described, and an article at dpreview.com discusses the theory with examples. The folks at DPReview even consulted with Professor Eric Fossum, the inventor of the modern CMOS camera sensors that make this possible.

 

In a related article they also discuss the sources of noise in digital imaging, and once again there are parallels to our common vexations. I’m sure Boltzmann is in there somewhere.

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