Unit 2: The Digital Image Process
At the conclusion of this unit, learners should be able to:
- Define the term digital image processing.
- Identify and describe five classes of digital imaging processing operations.
- Describe four characteristics of a digital image and how they affect the appearance of the image.
Digital Image Processing
Digital Image processing is the process of using a computer to convert a digital image from its numerical representation to its output image. The numerical image can be altered in numerous different ways based upon the needs of the viewer. It can also be manipulated to improve or enhance the diagnostic interpretation and management of the images acquired from patients. Digital image processing is now part of the regular workflow of managing images and is a routine function of radiologic technologists and radiologists.
All digital radiography modalities including computed radiography, flat panel digital radiography, and digital fluoroscopy utilize digital image processing as a central feature of their operations. Digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and allows the technologist to manipulate the data to produce a diagnostic image rather than re-radiating the patient.
Digital Image Processing Operations
There are several fundamental operations used in digital image processing to convert the digital image to an output image. This course will discuss four of them: image enhancement, image restoration, image analysis, and image compression.
The purpose of image enhancement is to create an image that is more pleasing to the viewer and improve the overall quality of the image. The functions of this processing class include contrast enhancement, edge enhancement, spatial and frequency filtering, image combining, and noise reduction.
Image restoration is used to improve the quality of images that are degraded or have distortions. Image restoration is commonly utilized in spacecraft imagery to improve images sent to Earth from space camera systems. Blurred images can be filtered to appear sharper by using image restoration.
Image analysis processing allows measurements and statistics to be performed, as well as image segmentation, feature extraction, and classification of objects. This process can be utilized by post processing data for computed tomography. Image segmentation and extraction can be used for 3D rendering of a particular area of interest in a scan.
Image compression processing is used to reduce the size of the image. This function is performed to decrease transmission time of the image and to decrease the amount of space needed to store the image. Compression improves the efficiency of the processing of the image without compromising the quality.
Four Characteristics of a Digital Image
A digital image has four basic characteristics or fundamental parameters: matrix, pixels, voxels, and bit depth.
A digital image is made up of a 2D array of numbers called a matrix. A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. Generally, diagnostic images are rectangular in shape and the matrix size or field of view (FOV) must be selected by the operator. The size selected is dependent upon the anatomy to be imaged. The larger the image, the larger the matrix and the more time it takes to process the image and the more storage space is required.
The individual matrix boxes are known are known as pixels. Each pixel contains a number (discrete value) that represents a brightness level, which reflects that tissue characteristics being imaged. The larger the matrix size, the smaller the pixel size and the better the spatial resolution.
The pixel size can be calculated using the relationship: Pixel size = FOV/matrix
Pixels in a digital image represent the information the information contained in a volume of tissue in a patient. Such volume is referred to as a voxel or volume element. Voxel information is converted into numerical value and expressed in the pixel.
The number of bits, or binary digits, per pixel is called the bit depth. They encode the signal intensity (gray scale) of each pixel for the digital image.
Test your knowledge - Digital Image Processing Quiz
Answer key - DR quiz answer key
Course Home: Digital Radiology for the Imaging Professional