Night Noise

You can reduce the noise in low light photography by taking multiple images and merging them to extract the statistical mean or median value. These statistical operations are available in Photoshop’s Layers > Smart Objects > Stack Mode menu. Here is a clear example of the effects of the mean and median operations on a stack of four similar images.

three images showing noise reduction by mean and median operations

Original, mean, and median images compared

The leftmost image is one of four similar images that were stacked into a smart object. In the middle image, the mean value (average) of the four images is used as the value of at each pixel position. In the right image, the median value (midpoint of the range of values) is used. You can find the full median image here.

The noise reduction is pretty dramatic (you’ll have to click on the image and view it full size to see what I mean). I find the mean image somewhat smoother, visually, than the median image, but the median image has some advantages over the mean.

A man in a yellow rainjacket walked across the view while I was shooting. You can see four images of him in the mean image: logically, one fourth of the pixels  in the stack at those points belonged to the moving man, so he has a ghostly presence. In the median image, he has practically disappeared: the influence of details or noise that appear in only one of the images is much less marked than in the mean image. The median operation is particularly useful for removing momentary details from a statistical composite.

Of course, the reason the original images were so noisy is that I was shooting hand-held at a high ISO (1600). If I had used a tripod and lower ISO with time exposure, I would not have had to resort to statistical operations for noise reduction. Knowing that the image would be noisy, I shot multiple images and used Photoshop’s File > Automate > Photomerge… command to position the images in layers. Details of how to do this can be found in an earlier post, Statistical Blending.

Layered Contrast

Here is a Photoshop technique for contrast that uses layers, one for the lights and one for the darks. Contrast can be adjusted with many commands in Photoshop: Brightness/Contrast, Levels, Curves, Exposure, to name a few. Layered contrast provides certain kinds of control you can’t achieve with the other commands. I’ll describe it step by step for you, by way of explanation, and also provide a downloadable action.

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High Pass Enhancements

Photoshop’s high pass filter can be used with layers to achieve some very useful image enhancements. This post discusses how to increase or decrease contrast along object edges and provides a few downloadable PS Actions. High pass edge contrast enhancement is a standard trick for adding “punch” to images: you probably see it all the time without even realizing it. Edge contrast reduction is a logical consequence of edge enhancement. It could be used as a “softening” filter, but probably qualifies as an “effect,” since it runs counter to expectations for good images. In other words, it’s just waiting for someone to exploit its potential.

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Statistical Blending

You can use statistical blending to render high dynamic range images, to reduce noise, or to create multiple exposure effects in Photoshop (CS4 extended edition). All these techniques require that you have multiple images to start with. For HDR images, you need different exposures of the same subject from a stationary viewpoint. The same is true for noise reduction, only the exposures should be identical. Multiple exposure effects can use any number of different images, all of the same dimensions. In each case, you start by stacking all the images into layers, selecting all layers, and converting them into a smart object. Then you use the Layer > Smart Objects > Stack Mode functions Mean or Median to create a statistical combination of all the images, which you can rasterize. Details after the break.

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Worthy of 16-bit Printing

Is there really any difference between printing with 8-bits per channel and printing with 16-bits per channel? I’m not sure yet, but I’ve been dealing with a photo that could reveal the difference. It has some very fine, continuous gradations–exactly the sort of thing that Epson says is worthy of 16-bit printing on the 9900.

Evening light

Evening light (Alma de la Serra, 2009)

I’ve been printing this on Hahnemühle Photo Rag (HPR), an exquisitely unforgiving paper. I reveals every glitch–which is to say, it’s a fantastic paper, capable of recording the finest nuances. I’ve been printing this 16-bit/channel image in 16-bit/channel resolution, and have been very gratified with the results.

Dust has been the only problem. Ink on HPR will not bleed into the gaps left by tiny particles, nor does it have a texture that will hide specks. This particular image really shows such flaws. I throw out about a third of the prints, looking for perfection. Nothing else will do. I haven’t had this problem with other papers–but maybe I’ve just been lucky, or there’s more static charge on HPR. In going digital, photography has not left dust behind.

Incidentally, this is a high dynamic range image, a composite of 5 images. I used qtpfsgui to composite and tonemap the image and finished the processing in Photoshop CS4. Qtpfsgui/ Luminance HDR is an open source application for HDR workflow. It doesn’t have the bells and whistles of Photomatix or Photoshop, but it gets the job done, once you grok the interface.

This print and a few others by Alma de la Serra will be on view at Transistor over the coming weeks.

ColorMunki Quirks

The ColorMunki color profiling device from XRite is one of the core technologies of my color workflow, but it has its oddities. Fortunately, there are some workarounds–and where there are none, patience is a virtue. Profiling a second monitor presented some difficulties, and the device has some ergonomic design shortcomings. You also have to learn to deal with a few good features.

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