Digital Image Representation

Digital Image Processing (DIP) Lecture (2) 4th class
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Digital Image Representation
2.1 INTRODUCTION
The digital image processing deals with developing a digital system that performs operations on a digital image. An image is nothing more than a two dimensional signal. It is defined by the mathematical function f(x,y) where x and y are the two co-ordinates horizontally and vertically and the amplitude of f at any pair of coordinate (x, y) is called the intensity or gray level of the
image at that point. When x, y and the amplitude values of f are all finite discrete quantities, we call the image a digital image. The field of image digital image processing refers to the processing of digital image by means of a digital computer.
2.2 Components of Image Processing System
Computer imaging systems are comprised of two primary components
types, hardware and software. The hardware components can be divided into image acquiring sub system (computer, scanner, and camera) and display devices (monitor, printer).The software allows us to manipulate the image and perform any desired processing on the image data.
Digital Image Processing (DIP) Lecture (2) 4th class
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i) Image Sensors
With reference to sensing, two elements are required to acquire digital image. The first is a physical device that is sensitive to the energy radiated by the object we wish to image and second is specialized image processing hardware.
ii) Specialize image processing hardware
It consists of the digitizer just mentioned, plus hardware that performs other primitive operations such as an arithmetic logic unit, which performs arithmetic such addition and subtraction and logical operations in parallel on images.
iii) Computer
It is a general purpose computer and can range from a PC to a supercomputer depending on the application. In dedicated applications, sometimes specially designed computer are used to achieve a required level of performance.
iv) Software
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It consist of specialized modules that perform specific tasks a well designed package also includes capability for the user to write code, as a minimum, utilizes the specialized module. More sophisticated software packages allow the integration of these modules.
v) Mass storage
This capability is a must in image processing applications. An image of size 1024x1024 pixels ,in which the intensity of each pixel is an 8- bit quantity requires one megabytes of storage space if the image is not compressed .
vi) Image displays
Image displays in use today are mainly color TV monitors. These monitors are driven by the outputs of image and graphics displays cards that are an integral part of computer system
vii) Hardcopy devices
The devices for recording image includes laser printers, film cameras, heat sensitive devices inkjet units and digital units such as optical and CD ROM disk. Films provide the highest possible resolution, but paper is the obvious medium of choice for written applications.
viii) Networking
It is almost a default function in any computer system in use today because of the large amount of data inherent in image processing applications. The key consideration in image transmission bandwidth.
2.3 Human Visual System (HVS)
The Human Visual System (HVS) has two primary components:
• Eye.
• Brian.
* The structure that we know the most about is the image receiving sensors (the human eye). the brain can be thought as being an information processing unit analogous to the computer in our computer imaging system. These two are connected by the optic nerve, which is really a bundle of nerves that contains the path ways for visual information to travel from the receiving sensor (the eye) to the processor (the brain).
2.4 A Simple Image Model
Digital Image Processing (DIP) Lecture (2) 4th class
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An image is denoted by a two dimensional function of the form f(x, y). The value or amplitude of f at spatial coordinates {x,y} is a positive scalar quantity whose physical meaning is determined by the source of the image.
When an image is generated by a physical process, its values are proportional to energy radiated by a physical source. As a consequence, f(x,y) must be nonzero and finite; that is
oThe function f(x,y) may be characterized by two components-The amount of the source illumination incidentكمية الضوء الساقط on the scene being viewed. The amount of the source illumination reflected back by the objects in the scene. These are called illumination and reflectance components and are denoted by i (x,y) and r(x,y) respectively. The functions combine as a product to form f(x,y).We call the intensity of a monochrome image at any coordinates (x,y) the gray level (l) of the image at that point
l= f (x, y)
L min ? l ? Lmax
Lmin is to be positive and Lmax must be finite
Lmin = imin rmin
Lamx = imax rmax
The interval [Lmin, Lmax] is called gray scale. Common practice is to shift this interval numerically to the interval [0, L-l] where l=0 is considered black and l= L-1 is considered white on the gray scale. All intermediate values are shades of gray of gray varying from black to white.
Digital Image Processing (DIP) Lecture (2) 4th class
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2.5 Digitization
To create a digital image, we need to convert the continuous sensed data into digital from. This involves two processes – sampling and quantization. An image may be continuous with respect to the x and y coordinates and also in amplitude. To convert it into digital form we have to sample the function in both coordinates and in amplitudes.
Digitalizing the coordinate values is called sampling (spatial resolution)
Digitalizing the amplitude values is called quantization(Gray level resolution)
Digital Image Processing (DIP) Lecture (2) 4th class
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Figure (3) Digitizing (Sampling ) an Analog Video Signal
2.6 Digital Image Definition
A digital image described in a 2D discrete space is derived from an analog image in a 2D continuous space through a sampling process that is frequently referred to as digitization.
The effect of digitization is shown in figure 4. The 2D continuous image is divided into N rows and M columns. The intersection of a row and a column is termed a pixel. The value assigned to the integer coordinates [m, n] with (m=0,1,…..,M) and (n=0,1,….,N-1) is f[m,n].
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A digital image is composed of a finite number of elements, each of which has a particular location and values of these elements are referred to as picture elements, image elements, pels and pixels.
There are three types of computerized processes in the processing of image
1) Low level process: these involve primitive operations such as image processing to reduce noise, contrast enhancement and image sharpening. These kind of processes are characterized by fact the both inputs and output are images.
2) Mid-level image processing: it involves tasks like segmentation, description of those objects to reduce them to a form suitable for computer processing, and classification of individual objects. The inputs to the process are generally images but outputs are attributes extracted from images.
3) High level processing: It involves “making sense” of an ensemble of recognized objects, as in image analysis, and performing the cognitive functions normally associated with vision.
2.7 Representing Digital Images
The result of sampling and quantization is matrix of real numbers. Assume that an image f(x,y) is sampled so that the resulting digital image has M rows and N Columns. The values of the coordinates (x,y) now become discrete quantities thus the value of the coordinates at origin become (x,y) =(0,0) The next Coordinates value along the first signify the image along the first row.
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Due to processing storage and hardware consideration, the number gray
levels typically is an integer power of 2.
Then, the number, B, of bites required to store a digital image is
B=M *N* k
When M=N
The equation become
When an image can have gray levels, it is referred to as “k- bit” . An
image with 256 possible gray levels is called an “8- bit image”(256=28)