Introduction to Image Processing And Its Applications PPT:
They work on two principles: improvement of pictorial information and processing of scene data. Image is a replica of an object. Images are of different types like gray tone images, line copy images and half tone images. There are various steps in image processing like preprocessing, segmentation, representation, recognition, interpretation, and knowledge base.
Image enhancement: this technique is used to increase the level of noise to noise signals. It is used to process the image so that the image obtained is more suitable the original image. Process of image may lead to image degradation. They generally use two categories for image processing.
Spatial domain method: they directly manipulate image pixels to obtain the new enhanced image.
Frequency domain method: they use Fourier transformation for the image processing before any modification.
For error free compression three types of coding methods are employed. Huffman coding, arithmetic coding and bit plane coding. For image segmentation two techniques are used fixed threshold and istogram-derived thresholds
There are also different techniques available for filtering the image like: spatial filter, which is further classified in 3 techniques,: mean filter, median filter and smoothing filter. Filtering can also be done in frequency domain. It is can be done by 4 ways like low pass filter, ideal low pass filter, butter worth low pass filter and homomorphic filter. They are used in x-rays to obtain clear image. It reduces the blur effect of the image.
Image compression models: they consist of source encoder which is responsible coding, inter-pixel and psycho visual processing in the input image.
Image restoration: this technique is just for improve the image. This method is applied towards modeling the degradation and then applied in reverse in order to obtain original image again.
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