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Tuesday, October 13, 2009

Noise: Lose It, Part II

Reducing chrominance and luminance noise at capture

This Article Features Photo Zoom

Noise can be characterized by magnitude (contrast) and frequency (distance): 7) High-frequency noise 8) Low-frequency noise 9) High-magnitude noise 10) Low-magnitude noise Noise affects tonal structure unevenly: 11) Darker regions contain more noise

The presence of luminance noise is more readily accepted than chrominance noise. Luminance noise is harder to reduce than chrominance noise. Luminance information encodes contour, volume and texture—key elements in representational images. Aggressive amounts of luminance-noise reduction subdue image texture, creating a synthetic or overly smooth appearance, and blurs contours, lessening the appearance of focus. In-camera noise reduction tends to be crude. RAW-conversion software produces significantly improved results. For more extreme noise reduction, third-party software such as Nik Software’s Dfine (www.niksoftware.com), PictureCode’s Noise Ninja (www.picturecode.com) and Imagenomic’s Noiseware (www.imagenomic.com) offer superior functionality and results.

Noise also varies in both magnitude and spatial frequency. Noise occurring over short distances has a high frequency (it’s “fine-grained”), while noise occurring over long distances has a low frequency. Noise magnitude, often described by the statistical measure of “standard deviation,” quantifies the variance a pixel will have from its “true” value. Higher-magnitude noise overpowers fine texture and becomes exceptionally difficult to remove.

With a thorough understanding of what produces noise, how it’s produced and what kinds and types of noise to be on the lookout for, you can take steps to reduce it at the point of capture. You want to start with as little noise as possible. If you want noise, you can always add it later, which gives you the possibility of customizing it with almost infinite precision. If you begin with noise in your originals, you’re locked in, and it can be challenging to reduce it without compromising image quality—sharpness, texture, saturation and hue variety. Given that noise isn’t the only concern you balance, for some uses this may be an acceptable trade-off.

There are a number of ways you can reduce noise during postprocessing. One could even say there’s an art to it. Learning these techniques can improve many fine exposures and even save others. I’ll address these in detail in upcoming columns.

John Paul Caponigro, author of Adobe Photoshop Master Class and the DVD series R/Evolution, is an internationally renowned fine artist and authority on digital printing. Get over 100 free downloads and his free e-newsletter Insights at www.johnpaulcaponigro.com.