Digital imaging can be used for

This tutorial is designed to help you understand that terminology better, and give you some ways to figure out what type of quality you might need when you are considering migrating to a paperless office.

What is Digital Imaging?

Digital imaging is the art of making digital images, including printed text, artwork, and photographs via a digital scanner or other imaging device. Each digital image contains a certain number of pixels or dots that are displayed on a screen.

Each pixel is mapped onto a grid and stored in a specific sequence onto a computer. Each pixel has its own tonal value that determines the image’s hue or color. The tonal value is represented in binary code or “bits” of information.

A computer reads these “bits” of information and converts them to an analog display of the image. Image resolution is determined by the number of pixels-per-inch (ppi/dpi).

Each digital image has its own bit depth, dynamic range, file size, file format, and compression. Digital imaging is used to create web pages, multimedia, pamphlets, visual presentations, and more.

Follow this basic tutorial to get a better understanding of the terminology and concepts of digital imaging:

Digital Images

The digital images created from a scanner may have originally appeared in a magazine, textbook, portfolio, journal, or other source of material.

Each sampled digital image enters the computer as a grid of dots or pixels. Each pixel has an assigned tonal value to represent the image’s color or hue. The tonal value of an image may appear in black, white, shades of gray, or color.

The tonal value is represented in a series of zeroes and ones also known as binary code. The stored sequence of binary information, also called “bits,” may be reduced to a mathematical representation.

The computer interprets and reads these bits of information to produce an analog image for display or printing.

Resolution

The resolution of a digital image refers to the ability to see its spatial detail-essentially, how clear the image is and how much you can enlarge it without losing quality, or making it look fuzzy.  The spatial frequency of a digital image is a good indicator of its resolution.

Resolution is often expressed in pixels-per-inch (ppi/dpi). Digital artists can increase the sampling frequency to create sharper resolution. Each pixel can be seen by zooming in on a digital image.

Pixel Dimensions

Digital cameras have pixel dimensions expressed horizontally and vertically to help define its resolution. For scanned images, calculate the ppi/dpi by dividing a document’s dimension into the aligned pixel dimension. For example, an 8-inch by 10-inch document with a 400 ppi/dpi has the pixel dimensions of 3,200 pixels by 4,000 pixels.

Bit Depth

The number of bits defined in each pixel determines its bit depth. The number of tones, grayscale or color increases along with its bit depth. Digital artists may produce images in black and white, grayscale, or color. A bitonal or black and white image consists of 1 bit each, represents two tones, and uses the values 0 for black and 1 for white.

Bit depth is critical for black and white imaging. A grayscale image consists of multiple bits of information, ranging between 2 to 8 bits or more. A color image has a bit depth ranging between 8 and 24 bits of information or higher.

A 24-bit color image may be divided into three categories, including 8 for red, 8 for green, and 8 for blue. A combination of those three categories will produce various colors. A 24-bit image may produce up to 16.7 million color values.

Dynamic Range

For example, high contrast microfilm has a broader dynamic range but produces fewer tones. The dynamic range may also refer to a digital system’s capability to reproduce tonal information of an image. This may be one of the most important aspects of image quality, especially in terms of digital photography.

File Size

File size is critical for digital imaging, especially for storage and file sharing.  Digital artists can determine file size by multiplying a document’s surface area to the bit depth and the ppi/dpi 2 . Divide the image file size by 8 to represent it in bytes. Multiply the pixel dimensions by each other and the bit depth to calculate the total number of bits in an image file.

For example, if a 24-bit image has pixel dimensions of 2,052 and 3,074, then multiply 2,052 x 3,074 x 24 and then divide by 8 to find out the answer in bytes. The file size is usually represented in increments of 1,024 or more. For instance, 1 kilobyte equals 1,024 bytes, 1 megabyte equals 1,024 kilobytes, 1 gigabyte equals 1,024 megabytes, and 1 terabyte equals 1,024 gigabytes.

Compression

All compression techniques reduce the binary code of a regular digital image to a form based on complicated algorithms.

There are two types of compression techniques to choose from, including standard and proprietary. Most file sizes require a standard compression technique rather than a proprietary one. Standard compression techniques tend to be more efficient than their counterpart.

Proprietary compression techniques may lend themselves to more long-term digital preservation.

Compression schemes may also include lossless or lossy formats. Lossless schemes shorten binary code without removing any information, an ideal choice when decompressing image files back to their original format.

Lossy schemes discard as little information as they can without altering the image entirely. Lossless is best used for bitonal scanning. Lossy is good for tonal images.

File Formats

File formats contain bits of information that consist of the image and header. The file format tells the computer how to read and interpret the file. There are many types of file formats that vary in color capabilities, bit-depth, resolution, compression, and metadata.