tailieunhanh - Lecture Digital image processing - Lecture 2: Image Digitization I

After studying this chapter you will be able to understand: Need for the digitization, to digitize the image, sampling, quantization, how to digitize an image? Why do we need to digitization? What is digitization? How to digitize an image? | Digital Image Processing DIGITIZATION Summery of previous lecture Digital image processing techniques Application areas of the digital image processing History of image processing techniques Steps in digitization of images Todays lecture Why do we need to digitization? What is digitization? How to digitize an image? Why digitization we need? Why digitization we need? Theory of real numbers: between any two given points there are infinite numbers of points. An image is represented by infinite number of points Its not possible to represent infinite number in computer Digitization 1: An image shall be represented in a form of a finite 2D matrix 2: The element values of f should also be finite Image as a matrix of numbers representation What is digitization ? Image representation by D2 finite matrix (sampling) Values of the Elements at the matrix are from the finite set of discrete values (quantization) To process images we need To digitize the image Sampling (we will focus on it) Quantization To visualize the image it needs to for displaying the images, it has to be first converted into the analog signal which is then displayed on a normal display. Sampling , Quantization and display Sampling 1 D sampling Assuming that we have a 1 dimensional signal x (t) Which is a function of t. Here, we assume this t to be time It is known that whenever some signal is represented as a function of time; signal is represented in the form of hertz Hertz means it is cycles per unit time. Sampling Instead of taking considering the signal values at every possible value of t; consider the signal values at certain discrete values of t. X (t) at t equal to 0. the signal X (t) at t equal to 2 delta t S The value of signal X (t) at t equal to delta 2 t S, at t equal to delta 3 t S and so on. delta t S is the sampling interval and corresponding sampling frequency is represent it by f S, it becomes 1 upon delta t S. Issue is local minimum, local maximum, Sampling issue increase the sampling . | Digital Image Processing DIGITIZATION Summery of previous lecture Digital image processing techniques Application areas of the digital image processing History of image processing techniques Steps in digitization of images Todays lecture Why do we need to digitization? What is digitization? How to digitize an image? Why digitization we need? Why digitization we need? Theory of real numbers: between any two given points there are infinite numbers of points. An image is represented by infinite number of points Its not possible to represent infinite number in computer Digitization 1: An image shall be represented in a form of a finite 2D matrix 2: The element values of f should also be finite Image as a matrix of numbers representation What is digitization ? Image representation by D2 finite matrix (sampling) Values of the Elements at the matrix are from the finite set of discrete values (quantization) To process images we need To digitize the image Sampling (we will focus on it) .

• Đồ họa - Thiết kế - Flash
• Digital image processing
• Lecture Digital image processing
• Digital images
• Digital computers
• Image processing
• Image digitization
• Theory of sampling
• Image segmentation
• Local processing
• Global processing
• Morphological image processing
• Autonomous machine applications
• Region growing
• Image transformation
• Image enhancement
• Image restoration
• Image transform
• Image compression
• Dark image