What is Image Processing

Image Processing

Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Today, the medical industry, astronomy, physics, chemistry, forensics, remote sensing, manufacturing, and defense are just some of the many fields that rely upon images to store, display, and provide information about the world around us. The challenge to scientists, engineers and business people is to quickly extract valuable information from raw image data. This is the primary purpose of image processing - converting images to information. Here we  explains how to process images using IDL (Interactive Data Language). IDL is a high-level programming language that contains an extensive library of image processing and analysis routines. With IDL, you can quickly access image data and begin investigating the best way to extract useful information.

Each part introduces image processing topics and includes information regarding when one method may be preferred over another to enhance specific image features. Numerous step-by-step examples illustrate IDL's image processing and analysis routines, allowing you to quickly understand how to get the desired results when working with your own image data. This topic is not intended to be a complete source for image processing knowledge, an advanced image processing manual or an image processing reference guide. This topic is designed to teach people how to use IDL to perform basic image processing, and does not assume that they are already experts in the field of image processing.

Digital Images and Image Processing

A digital image is composed of a grid of pixels and stored as an array. A single pixel represents a value of either light intensity or color. Images are processed to obtain information beyond what is apparent given the image's initial pixel values. Image processing tasks can include any combination of the following:

Modifying the Image View

Transforming, translating, rotating and resizing images are common tasks used to focus the viewer's attention on a specific area of the image. Transforming Image Geometry provides information on how to precisely position images using IDL.

Adding Dimensionality to Image Data

Some images provide more information when they are placed on a polygon, surface, or geometric shape such as a sphere. Mapping an Image onto Geometry shows how to display images over surfaces and geometric shapes.

Working with Masks and Calculating Statistics

Image processing uses some fundamental mathematical methods to alter image arrays. These include masking, clipping, locating, and statistics.  Working with Masks and Image Statistics introduces these operations and provides examples of masking and calculating image statistics.

Warping Images

Some data acquisition methods can introduce an unwanted curvature into an image. Image warping using control points can realign an image along a regular grid or align two images captured from different perspectives. See Warping Images for more information.

Specifying Regions of Interest (ROIs)

When processing an image, you may want to concentrate on a specific region of interest (ROI). ROIs can be determined, displayed, and analyzed within IDL as described in Working with Regions of Interest (ROIs).

Manipulating Images in Various Domains

One of the most useful tools in image processing is the ability to transform an image from one domain to another. Additional information can be derived from images displayed in frequency, time-frequency, Hough, and Radon domains. Moreover, some complex processing tasks are simpler within these domains. See Transforming Between Domains for details.

Enhancing Contrast and Filtering

Contrasting and filtering provide the ability to smooth, sharpen, enhance edges and reduce noise within images. See Contrasting and Filtering for details on manipulating contrast and applying filters to highlight and extract specific image features.

Extracting and Analyzing Shapes

Morphological operations provide a means of determining underlying image structures. Used in combination, these routines provide the ability to highlight, extract, and analyze features within an image. See Extracting and Analyzing Shapes for details.

Before processing images, it is important to understand how images are defined, how image data is represented, and how images are accessed (imported and exported) within IDL. 

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