ABSTRACT
This chapter deals with image formation, image storage, and image representation. It discusses the filtering techniques used for images, namely, low-pass filters, high-pass filters, edge enhancement filter, high-frequency emphasis filter, and contrast enhancement filters in spatial domain. The chapter describes different spatial masks for image smoothing and edge detectors such as Sobel and Prewitt. It explains the edge detection using derivative of gradient, that is, Laplacian mask. This chapter presents the different processing techniques like image compression, noise cancellation, and image resizing using transform domain techniques like Discrete cosine transform and wavelet transform. It discusses the method to draw the histogram for the image, mapping probability density function values to cumulative distributive function and then equalizing the histogram. The smoothing operator called Gaussian is a mask used for executing a 2D convolution. It is used to blur the image so that it removes the noise pixels.
