Chapter 11

Common Tasks

In the previous chapter we gave a brief overview of the core concepts involved in processing digital images in software, as well as a practical introduction to methods for selecting regions of an image.  In this chapter we continue in the more practical vein by surveying the most common tasks needing to be performed in the correction of digital bird photos.  In the next chapter (Chapter 12) we’ll place these tasks into the context of a workflow, to further improve your efficiency when digitally processing large numbers of photos.  The succeeding chapter (Chapter 13) will in turn cover some more advanced techniques than those considered here.

11.1 Reducing Noise

One of the most important differences between camera models (and especially between more and less expensive models) is their ability to create low-noise images in challenging lighting conditions.  Recall from section 2.5 that noise can limit your effective detail level, since the further you zoom in to an image (so as to enlarge fine details), the more likely it is that any noise present in the image will be amplified to an unacceptable level.  Fortunately, the noise-reduction capabilities in Photoshop—in the hands of a competent user—can in many cases overcome the noise limitations imposed by a cheaper camera model.  Indeed, one might go so far as to say that if you have a choice between buying a more expensive camera together with some cheap (or free) photo processing software, versus buying a slightly cheaper camera plus a copy of Photoshop, you might be better off opting for the latter.  (The case is made even stronger if by buying the cheaper camera you can then purchase a more expensive lens to go with it).
    Reducing noise in Photoshop is simple—though as we’ll see shortly, reducing noise without also obliterating detail in the bird requires some more effort.  The figure below shows the Reduce Noise window in Photoshop.  At right are several sliders: Strength, Preserve Details, Reduce Color Noise, and Sharpen Details.  I generally only use the first and second sliders.  As you can see here, I’m applying full strength (Strength=10) while preserving details at a level of 30% and then applying a post-noise-reduction sharpening pass at 30%.

Fig. 11.1.1: Reducing noise in Photoshop.  The four sliders at right dictate how aggressively
noise is reduced, and how much detail is lost as a result.  I typically set Strength to 10 and
Preserve Details to 30%.  The other slides I typically leave at 0.  Note that for RAW files
you can also reduce noise during RAW conversion, and this is often more effective than
reducing it directly in Photoshop.

    The figure below illustrates the relative effects of these sliders.  The leftmost pane shows the raw image, with no noise reduction applied.  In the middle pane I’ve applied full-strength noise reduction with 0% detail preservation and no sharpening.  As you can see, the noise in the background has been considerably reduced, but so has the detail in the bird; the bird now appears very watery and blurred.  In the rightmost pane I’ve set the detail preservation to 30% and sharpening to 30%.  Now the bird retains most of its detail, but you can see that the noise in the background has not been reduced as much as in the middle pane.

Fig. 11.1.2: The effect of noise reduction strength and detail retention.  Left pane: the original
image.  Middle pane: after noise reduction at strength 10, with 0% detail retention.  Right pane:
after noise reduction at strength 10, with 30% detail retention and 30% sharpening.  Global
noise reduction always involves a tradeoff between reduction of noise and loss of detail.
For this reason, non-global methods can be far more effective.

    This is the problem with virtually all automatic noise-reduction filters: because they can’t tell the difference between the subject and the background, they end up reducing noise at the expense of subject detail.  Fortunately, in Photoshop it’s possible to apply any filter to just specific portions of the image, as desired.  As described in section 10.6, this is one of the most powerful features of Photoshop (and similar software).  The practice of separately processing different parts of an image with different filters—what I like to call Differential Processing of Image Elements, or D-PIE—is a technique we’ll revisit several times in the next several chapters. 
    In the specific case of noise reduction, the D-PIE technique is fairly straightforward.  You first select the bird (as well as its perch and any other foreground objects that you’d like to avoid blurring) using the Quick Selection tool described in section 10.6.  Next, invert the selection via the menu option Select > Inverse (I have this set to the key combination Cmd-Shift-I on my computer) so that the background is now selected rather than the foreground.  Now press Ctrl-J (Cmd-J on a Mac) to copy the selected region to a new layer.  Finally, invoke the noise reduction filter (set to key combination Cmd-N on my computer).  Because you’ll now be reducing noise only in the background regions of the image, you can be as aggressive as you like, setting Strength to 10 and Preserve Details to 0%.  The figure below speaks for itself.

Fig. 11.1.3: Local noise reduction via the use of layers.  Left pane: the original
image.  Right pane: after splitting the image into two layers (foreground and
background) and applying three iterations of aggressive noise reduction only
to the background layer.

As you can see in the figure above, the result of applying this technique can be rather striking.  In the left pane of the figure is the original image, while the right pane shows the result of noise reduction applied only to the background layer (Layer 2).  In this case I’ve actually applied the noise reduction filter three times in succession, resulting in a perfectly smooth background gradient with virtually no noise whatsoever.  Because the bird is on a different layer, its details were completely unaffected by the noise filter.
    Now there are a few subtle details that need to be mentioned.  In the right pane of the figure above, you can see the Layers palette, which shows that Layer 2 is currently selected.  Before applying the noise filter, it’s a good idea to lock the transparent pixels in the layer.  This is accomplished by clicking the tiny checkerboard icon next to
Lock near the top of the Layers palette.  If you apply aggressive noise reduction without first locking the transparent pixels, a slight haze can be induced around the boundaries of the opaque regions in the layer, and this can affect the apparent sharpness of your foreground layer.
    Another subtle detail is that in the above example I expanded the selection of the bird by 1 pixel before inverting the selection and creating the background layer.  This creates a small buffer zone around the bird that can help to reduce the effect of imperfections in your selection, and can help preserve fine details in the contour of the bird.  Expanding the selection is as simple as selecting the menu option Select > Modify > Expand and entering the expansion radius, as shown below.

Fig. 11.1.4: Expanding the foreground selection by 1 pixel prior to inverting
the selection and reducing noise can reduce the effect of sloppy selection.  In
this image, the selection doesn’t follow the outer contour of the bird with perfect
precision.  Expanding the selection by 1 or 2 pixels adds a safety buffer.

As you can see in the above figure, the selection of the bird’s beak is not entirely precise.  Expanding the selection by one or two pixels prior to inverting the selection and reducing noise can help to avoid losing fine details around the perimeter of the foreground.  As mentioned in section 10.6, you can also feather the selection by a small radius to force the filter strength to fall off around the edges of the selection or active layer. 
    In the example above I selected the bird via the Quick Select tool, which works extremely well in simple cases like the one shown here—where the bird and background are visually separable both spacially and chromatically (i.e., are of starkly different colors).  For more challenging foreground/background separation scenarios, you can resort to other selection techniques (such as Select by Color Range or by painting in Quick Mask mode) as discussed in section 10.6.  For the purpose of noise reduction, however, many of these more complex scenarios admit a simpler solution: the blur tool.  If only very limited regions of the image show excessive noise, such as around the corners or in a few restricted dark areas, you can remove the noise manually by painting it away using the blur tool, as illustrated below.

Fig. 11.1.5: Reducing noise manually via the blur
tool.  The black circle is the blur tool cursor; the
diagonal swath painted with the blur tool is now
devoid of noise.  This technique is most useful for
images in which only small areas have noise.

    In the figure above, I’ve enabled the blur tool and swept it repeatedly across a diagonal swath of the background, just to illustrate the effect.  If you look closely, you can see that the diagonal region where the brush is located (the large, black circle denotes the brush cursor) is virtually devoid of any noise.  In theory, you could brush away all the noise in this image’s background in this way, but you’d have to be very careful when working close to the edge of the bird (to avoid accidentally brushing away detail in the bird); that could be very tedious and time consuming, so I recommend only using the blur tool when the noisy parts of the image are very limited in size and aren’t close to the bird or other important foreground elements.
When we get to Chapter 12 we’ll consider the task of developing a personal workflow—a stereotyped ordering of processing operations that you typically apply to all your bird images—and there we’ll consider some of the tradeoffs involved in applying certain filters before or after certain other ones.  In the case of  noise reduction, the order in which you apply the noise filter and (separately) a sharpening filter can affect the resulting appearance of your image.  For example, a fine-scale sharpening filter can reduce the effectiveness of a subsequent noise-reduction filter by, in effect, sharpening the noise and making it harder for the noise filter to see the noise as noise rather than detail.  If you follow the above D-PIE technique for noise reduction, this issue becomes less relevant since you’ll typically be reducing the noise only in the background, and sharpening details only (or, at least, most aggressively) in the foreground.
    In section 2.5 we discussed the types and sources of noise, from the perspective of sensor technologies.  In the realm of image postprocessing, noise is typically classified instead by its visual effect on the image, with the primary classification being between luminance noise and chrominance (or
chroma) noise.  Luminance noise results from fine-scale errors in pixel intensity (brightness), whereas chroma noise results from errors in pixel color.  I’ve rarely found a need to reduce chroma noise in images taken with my digital cameras, and indeed aggressive use of the Reduce Color Noise slider in Photoshop often  reduces color saturation to a significant degree, so I typically leave that slider set at zero.  However, if you shoot at very high ISO settings with a non-pro DLSR camera, chroma noise may indeed be a problem in your images, especially in dark areas of underexposed photos.
    If you’re shooting in RAW (and you should be), there’s another option for reducing both luminance and chrominance noise in Photoshop.  When you open a RAW file in Photoshop, you’re first taken to the Adobe Camera Raw (ACR) application, which converts the camera-specific RAW file into a brand-independent format that Photoshop proper can work with.  During this RAW-conversion process, certain basic image manipulations can be performed, and in some cases these manipulations will have higher image fidelity when performed during RAW conversion than if performed after conversion in Photoshop proper.  The reasons for this are a bit technical (e.g., access to the original linear color space, the ability to read the un-interpolated values measured via the Bayer pattern, etc.), but the important point is that noise reduction can sometimes be more effective when performed in ACR than when performed in Photoshop proper1,2.  The figure below illustrates how to reduce noise in ACR.

Fig. 11.1.6: Reducing noise during RAW conversion can be more effective than
doing it later in Photoshop.  In Adobe Camera Raw I typically set the luminance
slider to 100; for most of my images, this significantly reduces background noise
without affecting foreground detail in any noticable way.

    In the figure above, the Luminance noise reduction slider is set to 100, while the color slider is set to 0.  When processing RAW files from my Canon EOS 1D Mark III camera, I’ve found that reducing luminance noise in this way can be extremely effective, often completely removing background noise without having any discernible effect on the foreground detail.  Since this process doesn’t require that I select the bird and process the background separately from the foreground, this is a very efficient option (though in most cases I
ll still need to separate the bird from the background anyway when adjusting exposure and sharpness).  Note that the effectiveness of this process will differ from camera to camera (especially between pro and non-pro camera bodies), and also depends on how noisy your images are to begin with.

Fig. 11.1.7: The result of reducing noise during RAW conversion.  Left pane: the original image.
Right pane: after aggressive noise reduction in RAW conversion.  Notice that the background
noise has been very substantially reduced, while the foreground detail is almost entirely
unaffected.  Results may vary between camera models and images.

    The figure above shows the same image, without noise reduction in ACR (left panel) and with noise reduction in ACR (right panel); in both cases the luminance noise reduction was set to 100 and the chrominance noise reduction to 0.  As you can see, the background noise has been largely eliminated, without any discernible effect on the bird.  Note in particular that the
whiskers (what ornithologists call rictal bristles) are retained here, whereas the method detailed earlier in this section, which relied on separating the foreground from the background, largely obliterates these types of details, since they’re generally too difficult to efficiently select with the Quick Selection tool.
    Keep in mind also that different cameras, each using different imaging sensor technologies, will produce different types and amounts of noise, and these will be more or less difficult to remove during RAW processing.  Many comparisons can be found in photography forums (see Appendix A) between the quality of different RAW processing engines and different noise-reduction programs, with different programs coming out ahead or behind depending on which version of the software is used, which settings in the software are selected, and which images are compared.  Incorporating third-party noise-reduction software into your workflow is addressed in Chapter 12.
    The issue of noise is often less important when your sole purpose is to post your images on the internet at reasonable sizes.  Prior to posting an image on the internet you’ll typically want to reduce your image from, say, 3000
×3000 pixels to perhaps 800×800 pixels.  The process of reducing the resolution of an image often results in a free reduction of visible noise.  In the figure below, the bluebird images from the previous figure are shown at 40% crop.  The image on the right has undergone noise reduction in ACR; the image on the left has not.  As you can see, the noise in the left image is very subtle, and on my monitor it appears quite acceptable as-is.

Fig. 11.1.8: Noise reduction is less important for images posted on the internet.
When reducing an image’s resolution prior to posting on the internet, low levels
of luminance noise are often effectively eliminated by the down-sampling algorithm.
Left: original image with no noise reduction.  Right: same image, but with noise
reduction applied during RAW conversion.  The resulting differences are very subtle.

    Note that for some (perhaps many) viewers, the total absence of noise is not always ideal.  Though it’s fairly easy in Photoshop to render all of your backgrounds perfectly smooth and 100% noise-free, a small amount of fine-grained noise can sometimes mimic the impression of traditional film grain, which more mature audiences may find to be simultaneously familiar and pleasing.  Overly smoothed images can in some cases appear almost like computer-generated scenes as seen in a video game or virtual reality simulation, and though some audiences may find this pleasing, others may not.  At the very least, be careful not to be overy aggressive in reducing noise in regions that do retain some foreground details (such as branches in or near the focal plane), since this does tend to look a bit unnatural when overdone. 
    It needs to be mentioned that there are cases in which noise can affect the main subject, rather than just the background.  This is typically only the case when using excessively high ISO values (e.g., above ISO 1600 for models comparable to the Canon EOS 1D Mark III), though it can also occur for subjects with both white and black plumage elements, when exposing for the white elements.  In such cases, you may want to consider applying moderate noise reduction to the bird, but with the Preserve Details and Sharpen Details sliders set to some non-zero value.  Indeed, you may to some extent be able to use the Sharpen Details feature of the noise reduction filter in place of the Unsharp Mask, to sharpen the bird while also reducing noise.  I’ve had only very moderate success in applying this technique, but it’s at least worth keeping in the back of your mind as you explore your processing options.
    Finally, note that the use of in-camera noise reduction (sometimes called
high-ISO noise reduction) is generally a bad idea, since once it’s been applied it can’t be undone.  Noise reduction and sharpening, when done in-camera, are often only available when shooting JPEG images (rather than RAW).  When shooting in RAW, in-camera sharpening and noise reduction functions typically only affect the in-camera preview, not the RAW image itself.  These settings may be transmitted along with the RAW file as sidecar instructions to the processing software, but they typically don’t destructively (i.e., irreversibly) affect the RAW file itself.  Also, since many sharpening and noise reduction algorithms are compute-intensive, the in-camera versions of these algorithms are sometimes simplified so as to execute faster (and more sloppily) than the corresponding functions that you’d perform later on your computer in Photoshop.

1. http://www.adobe.com/digitalimag/pdfs/ps_workflow_sec2.pdf
2. Photoshop CS3 for Windows and Macintosh by E. Weinmann and P .Lourekas (2007)