Managing resolution is a fundamental part of the digital imaging process. Resolution concepts, and the terminology used to describe it, can sometimes lead to some confusion. In the most basic sense, resolution relates to the amount of detail contained in an image. In digital imaging, resolution refers to the number of specific points of picture information contained in an image file. These points are known as picture elements, or pixels. The number of pixels in an image, or pixel-count, has an effect on both resolution and file size. High-resolution images contain a relatively high number of pixels and can exhibit great image detail. When an image is low in resolution, or has too few pixels for a given use, the pixels will be large and quite visible as small blocks or “jaggies”. A high-resolution image would have to be magnified before individual pixels would become noticeable. Because pixel-count also affects file size, image resolution should be matched to output requirements in order to maintain efficiency in image processing and file storage.
Bit depth, which is sometimes referred to as brightness resolution, also has an effect on the perceived quality of an image. A bit, or binary digit, is the smallest unit of digital information. Bit depth refers to the number of bits or brightness levels that are recorded for each pixel in an image file. A 1-bit value (21) for a grayscale image would consist of two brightness levels, 0 (pure black), and 1 (pure white). An 8-bit (28) image can contain up to 256 brightness levels. Grayscale images are typically 8-bit, and can display 256 shades of gray.
Most modern color input devices will capture 8-bits for each of the primary color channels, red, green, and blue. The result is commonly referred to as 24-bit color and results in over 16 million color possibilities. Photographic images look best when captured and displayed in 24-bit color. The latest generation of digital cameras and scanners are capable of capturing at higher bit depth numbers of 10, 12 or 14 bits per color (30 bit, 36 bit and 42 bit color). Although most current monitors and printers are limited to 24-bit color output, capture at higher bit depth results in extra data that can reduce noise, improve exposure latitude and increase detail in shadows and highlights.
One of the reasons why resolution may seem confusing is that it is often expressed in different ways. Pixel dimension refers to the number of pixels in an image. An image 1600 pixels wide by 1200 pixels high would have pixel dimensions of 1600 x 1200. Resolution is also expressed in pixels-per-inch (ppi). If your intended output is a print, then ppi is useful for determining the resolution and physical dimensions of the printed image. For example, an image with a pixel dimension of 1600 x 1200 would print at a physical size of 8 x 6 inches with the resolution set at 200 ppi.
Screen resolution is quite different than print resolution. As output devices, monitors do not recognize the number of pixels-per-inch, only the pixel dimensions of an image. Monitor resolution varies, and is user-adjustable for pixel dimensions and bit depth. Because of these variables, images with the same resolution will appear different in size on monitors with different sizes or resolution settings. When capturing or preparing an image for screen display, pixel dimensions are a more appropriate measure of resolution.
Some hardware manufacturers and imaging professionals also use the term dots-per-inch (dpi) to refer to image resolution. Usually they are referring to pixels-per-inch, but this can be confusing because dpi is also used to describe printer resolution. In some cases, printer “dpi” is a completely different number and should not be confused with image “ppi”.
Resizing: scaling vs. resampling
When discussing resolution we also need to consider sizing. Scaling or resampling an image is often necessary to size it properly for a given display or output resolution. A digital file doesn’t really have a physical size until you map the pixels to an output device.
Scaling is the best way to resize an image while maintaining quality. Scaling does not affect the pixel count of the image. It simply stretches or compresses the pixels to fill a particular physical dimension. The size of the pixels themselves will increase or decrease accordingly.
Dragging the corner sizing handles to increase or decrease image size in a page layout or presentation program is a common method of scaling. In this case you are scaling an image by how it looks within a page layout.
You can also scale an image by specifying the size in inches or centimeters for printing. If you have an image with a pixel count of 1200 x 900, resizing would allow you to specify the physical dimensions for printing. Sizing this image for printing at a size of 4 x 3 inches would result in a resolution of 300 ppi. Increasing the print size to 8 x 6 inches would reduce the resolution to 150 ppi. If you need an image printed at this physical size with a higher resolution, you have two choices, reacquire the image at a higher resolution or resample it.
Resampling is another way to resize an image. Unlike scaling, resampling either increases or decreases the total number of pixels to achieve the desired ppi.
Downsampling to resize an image is acceptable; it simply means discarding pixels to reach an appropriate resolution. This is commonly performed on high-resolution images that are being prepared for Internet use. High-resolution images require long download times and are unnecessary for screen display. Images with pixel dimensions greater than the resolution of the monitor will yield no additional image quality.
Upsampling, or increasing the number of pixels through interpolation will not create new detail. Upsampling asks the software program to invent pixels that don’t exist. Although image-editing programs use sophisticated algorithms to upsample in this manner, the results may be disappointing. Resampling may not actually give you the expected increase in resolution. Yes the pixel count will be higher, but detail will not increase. When you need to resample, try to keep the amount of upsampling to a minimum.
Selecting the best resolution for a given use is often a compromise. Interpolation or resampling is lurking everywhere. Scanners interpolate unless the scan resolution is set at the (full) optical resolution of the scanner. Scanning at a setting higher or lower than optical resolution, will result in pixels being discarded or manufactured by the driver software. Inkjet printers also interpolate image data in order to determine a drop pattern for blending colors. Some interpolation in digital imaging may be unavoidable. For best results however, try to limit the number of times that interpolation is performed throughout the imaging chain.