177x Filetype PDF File size 0.52 MB Source: pdfs.semanticscholar.org
Introduction to Digital Image Processing Overview (1): What is Digital Image Processing (DIP) ? What is an image ? Relationship to Computer Vision Fall 2005 Origins of Digital Image Processing Brief historical overview Introduction Fields that Use Digital Image Processing Image categorization and the electromagnetic Bill Kapralos spectrum (EM) Gamma ray, x-ray, ultraviolet, visible, infrared, microwave, radio wave ELIC 629, Fall 2005, Bill Kapralos Overview (2): Fundamental Steps Methodologies Overview of what this course will cover What is Digital Image Components of a Digital Image Processing System Processing ? Hardware Software Conclusions Summary ELIC 629, Fall 2005 Bill Kapralos Introduction to Digital Image Processing What is a Digital Image ? (1): What is a Digital Image ? (2): A Discrete Two-Dimensional Function f(x,y) Intensity x,y denote the spatial coordinates The value (or amplitude) of the function f at spatial Consider a table (or matrix or grid) where x coordinates (x,y) indicates the row and y the column Finite and discrete when considering digital images Example: matrix with 5 rows and 6 columns (5 x 6) Non-discrete and non-finite → not a digital image! 012345 NOTE: 0 0,0 0,1 0,2 0,3 0,4 0,5 ) 1 1,0 1,1 1,2 1,3 1,4 1,5 ) The digital image is obtained x x ( ( by sampling an analog 2D w 2 2,0 2,1 2,2 2,3 2,4 2,5 w image but for now, lets not Ro 3 3,0 3,1 3,2 3,3 3,4 3,5 Ro be concerned with this. 4 4,0 4,1 4,2 4,3 4,4 4,5 Sampling will be discussed Column (y) next week! Column (y) What is a Digital Image ? (3): What is a Digital Image ? (4): Intensity (continued…) Pixel The intensity of a digital image can vary from a wide Each element of a digital image e.g., each entry in the range of values grid (matrix) with its distinct spatial location Typical examples: 0 – 255, 0 – 32,767 etc… Also known as Can also have more than one intensity value Picture element or pel associated with each spatial location Image element Color images → one intensity value for each color (e.g., red, green, blue color channels – more of this Pixel in the future)… Single color → intensity also known as gray level ELIC 629, Fall 2005 Bill Kapralos Introduction to Digital Image Processing Digital Image Processing (1): Digital Image Processing (2): Definition Covers a Large and Varied Field of Processing digital images with a digital computer Applications Two Principle Applications of Digital Image Although the human visual system can only respond to the visual band of the electromagnetic spectrum, Processing machines can be used to image (sample) the (almost) entire electromagnetic spectrum Improvement of images for human interpretation More about this later Processing of image data for storage, transmission and representation for autonomous machine perception Digital Image Processing (3): Digital Image Processing (4): Relationship to Other Fields Relationship to Other Fields (cont…) Computer vision Too restrictive! e.g., then the common operation of Create real-world model from one or more images computing the average intensity of an image is not Recovers useful information about a scene from a part of image processing! 2D projection of the 3D world A useful paradigm is to consider three types of Ultimately emulate human visual system! computerized processes Where does image processing stop and image Low level → primitive operations such as noise analysis/computer vision start ? reduction, contrast enhancement, image sharpening No clear cut boundaries! Mid Level → segmentation, classification, How about defining image processing such that High level → making sense of recognized objects, both input and output are images ? even performing cognitive functions ELIC 629, Fall 2005 Bill Kapralos Introduction to Digital Image Processing Digital Image Processing (5): Origins of Digital Image Processing (1): Definition Used in this Course One of the First Applications was in the Processes whose inputs and outputs are images but Newspaper Industry we also include processes which extract attributes from images including the recognition of individual Pictures sent by submarine cable between Europe and objects North America As an “Aside” – Computer Graphics Bartlane transmission system → transfer picture in a couple of hours instead of more than one week Computer used to recreate a “picture” given some Code picture at the transmitting end, send coded description of a scene/environment data over cable, receive and decode at the “Almost” like the opposite problem to image receiving end processing although there is some overlap! Five discrete levels of gray and later up to 15 Origins of Digital Image processing (2): Origins of Digital Image Processing (3): Bartlane Transmitter Early Examples did not Include Computer! Technically, do not fall into our definition of image processing since we require the use of a computer! Although the notion of a computer can be traced back more than 5000 years, the modern digital computer dates back to the 1940s and the two key concepts introduced by John von Neumann 1. Memory to hold stored programs and data Sample Image 2. Conditional branching ELIC 629, Fall 2005 Bill Kapralos
no reviews yet
Please Login to review.