Fundamental Steps in Digital Image Processing
An image can be defined as a two-dimensional function f(x,y)
- x,y: Spatial coordinate
- f: the amplitude of any pair of coordinate x,y, which is called the intensity or gray level of the image at that point.
- x,y and f, are all finite and discrete quantities.
Step 1: Image Acquisition
The image is captured by a sensor (eg. Camera), and digitized if the output of the camera or sensor is not already in digital form, using analogue-to-digital convertor.
It could be as simple as being given an image that is already in digital form. Generally the image acquisition stage involves processing such as scaling.
Step 2: Image Enhancement
It is among the simplest and most appealing areas of digital image processing. The idea behind this is to bring out details that are obscured or simply to highlight certain features of interest in image. Image enhancement is a very subjective area of image processing.
Step 3: Image Restoration
It deals with improving the appearance of an image. It is an objective approach, in the sense that restoration techniques tend to be based on mathematical or probabilistic models of image processing.
Enhancement, on the other hand is based on human subjective preferences regarding what constitutes a “good” enhancement result.
Step 4: Colour Image Processing
Use the colour of the image to extract features of interest in an image.
It is an area that is been gaining importance because of the use of digital images over the internet. Color image processing deals with basically color models and their implementation in image processing applications.
Step 5: Wavelets and Multiresolution Processing
Are the foundation of representing images in various degrees of resolution. It is used for image data compression.
Step 6: Compression
Techniques for reducing the storage required to save an image or the bandwidth required to transmit it.
It deals with techniques reducing the storage required to save an image, or the bandwidth required to transmit it over the network. It has to major approaches:
- Lossless Compression
- Lossy Compression
Step 7: Morphological Processing
Tools for extracting image components that are useful in the representation and description of shape. In this step, there would be a transition from processes that output images, to processes that output image attributes.
It deals with tools for extracting image components that are useful in the representation and description of shape and boundary of objects. It is majorly used in automated inspection applications.
Step 8: Image Segmentation
Segmentation procedures partition an image into its constituent parts or objects.
Step 9: Representation and Description
Representation: Make a decision whether the data should be represented as a boundary or as a complete region. It is almost always follows the output of a segmentation stage.
- Boundary Representation: Focus on external shape characteristics, such as corners and inflections.
- Region Representation: Focus on internal properties, such as texture or skeleton shape.
Choosing a representation is only part of the solution for transforming raw data into a form suitable for subsequent computer processing (mainly recognition).
Description: also called, feature selection, deals with extracting attributes that result in some information of interest.
Step 9: Recognition and Interpretation
Recognition: the process that assigns label to an object based on the information provided by its description.
Step 10: Knowledge Base
Knowledge about a problem domain is coded into an image processing system in the form of a knowledge database.
Knowledge about a problem domain is coded into an image processing system in the form of a knowledge base. This knowledge may be as simple as detailing regions of an image where the information of the interest in known to be located. Thus limiting search that has to be conducted in seeking the information.
The knowledge base also can be quite complex such interrelated list of all major possible defects in a materials inspection problems or an image database containing high resolution satellite images of a region in connection with change detection application