Introduction to Image Processing
Image processing is computer based image handling, and process input and output will be images. The process input is an image and the output is a classification or description of it. The computer chart area involves the image generation based on its descriptions.
The objective to use digital image processing is to improve visual aspect of certain structure appearance to the human analyst and provide other subsidies to its interpretation including product generation that can be submitted to later processing.
DIP techniques besides allow analyze a scene in many electromagnetic regions of the spectrum, also make possible to integrate many data types and registered data accordingly.
DIP happens in three different independent steps: preprocessing, improvement and classification. Preprocessing refers to the initial processing of raw data to radiometric calibration of image, geometrical distortion corrections and noise removal. More common improvement techniques in PID are contrast improvement, filtering, arithmetic operations, IHS transform and main components. Classification techniques can be divided in supervised classification (per pixel) and non-supervised classification (per region).
Note: user can choose not to use classification algorithms once he can opt to use direct interpretation on improved image.
DIP techniques are performed always with gray levels assigned to pixels in an image. Depending on involved technique user will work with only one image (band or layer) or with several images, the most known is the multi spectrum technique handling several images of the same scene in different electromagnetic spectrum.