This document discusses several key digital imaging fundamentals in Photoshop, including benefits of higher megapixel counts such as more detail and ability to digitally zoom, pixel aspect ratios, anti-aliasing techniques, primary colors in RGB and CMYK systems, color and alpha channels, grayscale vs bitmap modes, understanding Lab color and histograms.

1. Ch 3: Digital Imaging Fundamentals
Photoshop CS6 Essentials
By Scott Onstott

2. Ch 3: Digital Imaging Fundamentals
Benefits of More Megapixels
• Larger DSLR sensors capture millions
more pixels (megapixels) compared to
point-and-shoot cameras
• More megapixels means you have
more detail and less noise
• You can digitally zoom in to large
images and the details remain crisp
• More megapixels also means more
data, larger file sizes, and more RAM
required

3. Ch 3: Digital Imaging Fundamentals
Pixel Aspect Ratio
• Pixels can have non-square aspect
ratios
• Use square pixels for print and for the
Web
• Video clips often use non-square
pixels
• You can change the pixel aspect ratio
using the View menu and in the File >
New dialog box

4. Ch 3: Digital Imaging Fundamentals
Aliasing and Anti-Aliasing
• Aliasing is the stair-stepping artifact
that occurs in grids of pixels
• Lines are not aliased when you draw
them horizontally, vertically, or at 45
degree angles
• Off-angled lines exhibit aliasing which
can be reduced by dithering the edge
(blue line at right) with intermediate
values
• Anti-aliased edges appear blurry
compared to aliased edges but the
stair-stepping is removed

5. Ch 3: Digital Imaging Fundamentals
Primary Colors
• Red, Green, and Blue are the primary
additive colors
• Cyan, Magenta, and Yellow are the
primaries of subtractive colors
• CMY are secondary colors in the RGB
system
• RGB are secondary colors in the CMY
system
• Black (abbreviated as K) is added to the
subtractive system, making CMYK the 4-
colors used in offset printing

6. Ch 3: Digital Imaging Fundamentals
Color Channels
• Color is split into primary components such as Red, Green, and Blue
• Primary color components are stored in grayscale image channels
• Color is reconstituted by illuminating red, green, and blue sub-pixels in
your monitor with varying intensities according to the luminance values
in the corresponding color channels
Photo courtesy of iStockphoto, ©Neustockimages, Image #7007990

7. Ch 3: Digital Imaging Fundamentals
Alpha Channels
• Alphas are additional channels
• Alpha 1 is used to store
transparency information
• When the Alpha 1 channel is
displayed against the RGB
channels a red rubylith overlay
appears to indicate areas of
transparency
• Not all formats support alpha
channels
• TIF and TGA do support alphas
Photo courtesy of iStockphoto,
©Neustockimages, Image #7007990

8. Ch 3: Digital Imaging Fundamentals
Understanding Lab Color
• L* a* b* stands for Lightness, a, and b
channels
• Detail is carried in the Lightness
channel
• Color is carried using a combination of
a and b channels
• Lab color is a convenient mode that
isolates image detail (can be used for
sharpening or grayscale conversion)
Photo courtesy of iStockphoto, ©Terry J Alcorn, Image #14990625

9. Ch 3: Digital Imaging Fundamentals
Grayscale vs. Bitmap Modes
• Grayscale images have a range of
tonal values in a single channel (256
gradations in 8-bit)
• Bitmap images also employ a single
channel
• Bitmap images are the most
primitive images having only black
and white pixels without any
intermediate shades of gray
• Bitmap images can be dithered or
processed with a halftone screen
Photo courtesy of iStockphoto,
©Terry J Alcorn, Image #14990625

10. Ch 3: Digital Imaging Fundamentals
Understanding Histograms
• Histograms help you see how well the
dynamic range is being utilized
• Histograms are made of black vertical bars
representing how many pixels are in the
shadows, mid-tones, and highlights
• Blank areas at the edges of a histogram show
there are values (blackest blacks or whitest
whites) that aren’t being used
• Gaps or spikes in a histogram show that
information has been “destroyed” by being
pushed beyond certain mathematical limits