It is a method of enhancing the visual quality of image and also extracting useful information from it. This field is strongly correlated with signal processing.
Motivation:
- Enhancing the quality of image for human perception like noise filtering, deblurring , contrast enhancement , remote sensing cameras ( satellite imaging, city planning, terrain mapping) etc.
2. Image processing for various autonomous task like self-driving car, drones, object recognition, video synthesis etc. This branch of image processing is known as Computer Vision, here our goal is to extract feature and information from image using image processing techniques.
3. Efficient storage and transmission like image compression.
Image Representation :
Before diving deeper into the field of image processing, it is very important to know about the how actually the image is represented??
So image is represented as a two dimensional intensity function matrix, and element of matrix is discrete finite value. And it is represented in form of product of reflectivity of the surface and intensity of incident light.
f(x,y) = r(x,y) * i(x,y)
where r is reflectivity of surface and i is the intensity of incident light.
Image representation is divided into two techniques:
- Spatial discretisation by sampling.
- Intensity discretisation by quantization.
I hope this tutorial covers the basic introduction of image processing.
In next tutorial of Image processing i will talk about Sampling and Quantization process in details.
Thank You!!!!!
