Image refers to a 2D light intensity function f(x,y), where (x,y) refers to the spatial coordinates and the value of f at point (x,y) is proportional to the brightness or gray levels of the image at that particular point. Each element of such a digital array are called pixels.
Why do we need image processing?
To improve the pictorial information for human interpretation so that more and clear message can be transferred from the image.
To add on image data storage, transmission and representation for autonomous machine perception.
Applications of image processing:
Target recognition in fighter aircraft
Interpretation of aerial photography
Facial expression recognition
Hand gesture recognition
Medical application to find out exact location of cancer
Fundamental steps of image processing:
Image Acquisition: It involves acquiring a digital image using an image sensor or camera and do necessary pre-processing. If this image is not digital, an analog to digital conversion process is required.
Image Enhancement:It improves the quality of an image by highlighting certain features of interest in an image like increasing or decreasing the contrast of an image. Quality gets improved with two methods:a. Spatial Domain: Deals with time constraints.b. Frequency Domain: Deals with frequency constraints.
Image Restoration:It is an area that deals with restoration of image by improving its appearance based on mathematical or probabilistic models of image restoration. It includes eliminating noise from an image which can be done by filtering technique and so on.
Image Morphology:It deals with tools for extracting image components that are useful in the representation and description of shape.
Image Degradation / Segmentation:It involves breaking an image into consistent parts. It is one of the most difficult task in digital image processing. A good segmentation simplifies the problem whereas a poor segmentation makes the image processing task impossible.
Image Representation:It involves the process of converting the input data to a form suitable for computer processing.
Image Recognition:It involves assigning a label to an object based on the information provided by its descriptors.
Image Interpretation:It involves assigning meaning to the collection of recognized objects.