The Hidden Power of Photoshop Elements 3, Pt. 1 | 4
The Hidden Power of Photoshop Elements 3, Pt. 1.
Separating luminosity from your images is another way to extract valuable tonal information and representation of black-and-white. Luminosity is a component of Lab color, which is a color model that distinguishes color components from tone (lightness). Because this color model considers tone separately from color, the luminosity component is often a good representation of what we would expect to see in black-and-white.
Photoshop Elements does not have Lab as one of the image color modes. However, as with RGB, luminosity and color components can be extracted from an image in more than one way, and can easily be represented using layers. As a purer measure of tone, the lightness component is often useful when RGB separations may not provide an advantage. For example, and as you will see, luminosity and color separation is invaluable for color noise reduction, as often happens in images recorded by digital cameras using fast shutter speeds.
Extracting Luminosity from Color
The following steps will enable you to extract luminosity from any RGB image. Use the
flower image again (
lily.psd) with these steps so you can compare the differences in the
resulting grayscale components.
1. Open the
2. Duplicate the Background layer (Layer > Duplicate Layer). This will be a temporary layer, so it does not need to be named. Change the layer mode to Luminosity by choosing it from the Blending Mode drop-down list in the upper left of the Layers palette.
3. Activate the Background layer by clicking on it in the Layers palette.
4. Create a new layer (Layer > New > Layer). This creates a new layer between the background and the copy. Name the layer Luminosity and click OK.
5. Fill the new layer with gray by choosing Edit > Fill and then selecting 50 percent Gray from the drop-down menu.
6. Duplicate the Composite layer. Name the layer Luminosity and click OK. Your layers should look like this graphic.
7. Activate the Background Copy layer by clicking on it in the Layers palette.
8. Merge the Background Copy and the Luminosity layer (Layer > Merge Down).
9. Choose Luminosity from the Blending Mode drop-down list in the upper left of the Layers palette. Your layers palette should look like the next graphic.
With the layer mode changed to Luminosity, what will display is the lightness (or L channel from the Lab color model), which is a representation of image tone. Save the resulting file so that you can come back to it later. Comparing this result to the components of an RGB separation as well as the straight conversion to grayscale by desaturation (as shown in Figure 2.2) should show some distinct differences in quality. Depending on the source of the image (digital capture or analog), the content of the image, and the quality and quantity of light in the capture, these differences will be moreÂor lessÂpronounced.
The luminosity component information can be extracted from an image in a single step by using Hidden Power tools. Just click the Split Luminosity Hidden Power tool in the PowerSeparations category of Effects; the steps for separating luminosity will execute when the tool is clicked. The tool will create three elements: the Luminosity component, the Color component, and the Composite layer. The Color component is Luminosity's partner: the components work together to create image color and tone in a similar way that RGB color components combine to create a color image. The Composite layer is just a canvas for the layer components to present againstÂas if the components are being projected to a screen. To view the image without the color, activate the Color layer and click its visibility toggle on the Layers palette to shut off the view. To view the image without the luminosity (essentially this is color and saturation), activate the Luminosity layer and click its layer visibility toggle to off (the Color layer toggle should be on).
The Split Luminosity power tool should be used on flattened RGB images. We'll look more at the color component a little later when we look at how saturation information can help in CMYK separation.
Making Black-and-White by Borrowing the Best Tone
Sometimes a simple conversion works just fine for changing a color image to black-andwhite. The most straightforward conversion to black-and-white is accomplished by converting RGB to Grayscale or desaturating. You can also create black-and-white representations of an image by using components from the RGB or luminosity separations. Sometimes a component of one of these conversions will suffice, and other times you have to look around and be more creative by borrowing and combining the tones that you can find lurking in various components from different separations. This is where the art of converting to blackand- white comes in: you have to have the vision to see what will combine for an interesting result.
If you look at the components of an RGB separation, the most representative component of what you'd expect to see in black-and-white will often be the green channel. This is because green is more naturally in the center of the visual spectrum and more closely resembles how humans perceive tone. The red channel is toward the infrared spectra, and the blue channel is toward the ultraviolet. Therefore, the red channel more closely represents infrared capture, and blue is more like ultraviolet.
Figure 2.2 The luminosity, or lightness, separation for the image (a) shows a somewhat different and often better representation of image tone than simply desaturating the image (b).
Very often, luminosity will provide an easy source to extract a good black-and-white representation of any image. It is less prone to color noise and at times will look surprisingly smooth, even when RGB separations have strong color noise (again, this color noise can happen with images shot with a digital camera in low light).
All of the separation possibilities can show you tonal representations that are somewhat differentÂdifferent from each other and different from straight desaturation. Sometimes a subtle adjustment in any of these three representations can yield greatly improved results in what otherwise would have been a straight conversion. These adjustments may be simple changes in tone using correction tools such as Curves (a Hidden Power tool that we'll look at in Chapter 3) or Levels. Or the changes may be made by using different areas of the image from different components and combining them with isolation, masking, or selection. We will look at methods for making these adjustments in later chapters.
Figure 2.3 shows five possibilities for a simple conversion to black-and-white from a single image, plus one result that combines three of the separations. For simple conversions, the blue and red can usually be discarded right away as sources because they are not often good representations of the way you will perceive image tone. However, red and blue can sometimes be used to make other adjustments (for example, to create selections, create masks, make calculations between components, mix components, or apply using historiesÂall of these techniques are presented in subsequent chapters). Comparison of the green, luminosity, and grayscale conversion from RGB may reveal different specific advantages. Adjustment of the available tones in more than one of the separated components may create the best result.
Figure 2.3 Looking at the five simple conversions of image tone can reveal distinct advantages in both representing the images and selecting objects or components.
The composite image in Figure 2.3 uses the luminosity, red, and green components. First, the luminosity component is used as a background: it is lightened to act as a canvas to set off the flower. The flower is isolated from the green component by using the red component as a mask. The flower is then just overlaid on the luminosity component by using layers. The techniques for masking and combining components is covered in later pages, so we won't look at those techniques here. We will look more at how to specifically make adjustments like this in topics that arise throughout the book.
Created: March 27, 2003
Revised: November 30, 2004