Image Processing Lecture 2

Computer Imaging Systems 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.

Components of an Image Processing System The figure shows the basic components comprising a typical general-purpose system Used for digital image processing. The function of each component is discussed in the following: 1.Sensing: two elements are required to acquire digital images. The first is a physical device that is sensitive to the energy radiated by the object we wish to image. The second, called a digitizer, is a device for converting the output of the physical sensing device into digital form. For instance, in a digital video camera, the sensors produce an electrical output proportional to tight intensity. 2.Specialized image processing hardware: usually consist of the digitizer plus hardware that performs other primitive operations, such as an arithmetic logic unit (ALU), that performs arithmetic and logical operations in parallel on entire images. This unit performs functions that require fast data through puts ( e.g., digitizing and averaging video images at 30 frames/s) that the typical main computer cannot handle.

3.The computer in an image processing system is a general-purpose computer and can range from a PC to a supercomputer. Almost any well-equipped PC- type machine is suitable for off-line image processing tasks. 4.Software for image processing consists of specialized modules that perform special tasks. A well designed package also includes the capability for the user to write code that as a minimum, utilizes the special modules. 5.Mass storage 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 megabyte of storage space if the image not compressed. aDigital image processing applications falls into three principle categories:

6.Image displays in used today are color flat screen, TV monitor. Monitors are driven by the outputs of image and graphics display cards that are an integral part of the computer system. 7.Hardcopy devices for recording images include laser printers, film cameras, heat- sensitive devices, inkjet unit, and digital unit, such as optical and CD-ROM disks. 8.Networking is almost a default function in any computer system is use today. Because of the large amount of data inherent in image processing applications, the key consideration in image transmission is bandwidth.

the basic components of an image processing system

Image Representation We have seen that the human visual system (HVS) receives an input image as a collection of spatially distributed light energy; this is form is called an optical image. Optical images are the type we deal with every day –cameras captures them, monitors display them, and we see them. we know that these optical images are represented as video information in the form of analog electrical signals and have seen how these are sampled to generate the digital image I(r, c). The digital image I (r, c) is represented as a two- dimensional array of data, where each pixel value corresponds to the brightness of the image at the point (r, c). in linear algebra terms, a two-dimensional array like our image model I( r, c ) is referred to as a matrix, and one row ( or column)is called a vector. The image types we will consider are:

We can convert the color image into grayscall image using several equations : Gray= [ Im_Red( x, y) + Im_Green( x, y) + Im_Blue( x, y) ] / 3 the second transformations is the ITU-R(International Telecommunications Union-Radio) this based on the luminance signal(Y)and two color different signal(Cr and Cb) given a 24 bits/pixel RGB signal, we can find Y, Cr, and Cb values as follows: Y = R G B Y = R G B Cr = R G B +128 Cr = R G B +128 Cb = 0.5 R G B +128 Cb = 0.5 R G B +128

3.) Color images Color image can be modeled as three band monochrome image data, The actual information stored in the digital image data is brightness information in each spectral band. When the image is displayed, the corresponding brightness information is displayed on the screen by picture elements that emit light energy corresponding to that particular color. where each band of the data corresponds to a different color. Typical color images are represented as red, green,and blue or RGB images.using the 8-bit monochrome standard as a model, the corresponding color image would have 24 bit/pixel – 8 bit for each color bands (red, green and blue ). The following figure we see a representation of a typical RGB color image.

For many applications, RGB color information is transformed into mathematical space that that decouples the brightness information from the color information. The hue/saturation /lightness (HSL) color transform allows us to describe colors in terms that we can more readily understand.

The lightness is the brightness of the color, and the hue is what we normally think of as “color” and the hue (ex: green, blue, red, and orange). The saturation is a measure of how much white is in the color (ex: Pink is red with more white, so it is less saturated than a pure red). [Most people relate to this method for describing color}. Example: “a deep, bright orange” would have a large intensity (“bright”), a hue of “orange”, and a high value of saturation (“deep”).we can picture this color in our minds, but if we defined this color in terms of its RGB components, R=245, G=110 and B=20. Modeling the color information creates a more people oriented way of describing the colors.

4.)Multispectral Images Multispectral Images typically contain of information outside the normal human perceptual range. This may include infrared, ultraviolet, X-rays, acoustic radar data. These are not images in the usual sense because the information represented is not directly visible by human system. However the information is often represented in visual form by mapping the different spectral bands to RGB components. If more than three bands of information are in the multispectral images, the dimensionality is reduced by applying principle component transform. Source of this types of image are Satellite system, under water sonar system, Infrared imaging system, medical diagnostic imaging system.

The process of generating colors with three basic components The process of generating colors with three basic components is based on the RGB Color cube as shown in the below figure. The three dimensions of the color cube correspond to the three basic colors. The cube's corners are assigned each of the three primary colors, their complements, and the colors black and white. Complementary colors are easily calculated by subtracting the Color values from 255. For example, the color ( 0,0,255 ) is a pure blue tone. Its complementary color is ( 255-0,255-0, ), or ( 255,255,0), which is a pure yellow tone. Blue and Yellow are complementary colors, and they are mapped to opposite corners of the cube. The same is true for red and cyan, green and magenta, and black and white. Adding a color to its complement gives white.

Most the type of file format fall into category of bitmap images. In general, these types of images contain both header information and the raw pixel data. The header information contain information regarding 1. The number of rows(height) 2. The number of columns(Width) 3. The number of bands. 4. The number of bit per pixel. 5. the file type 6. Additionally, with some of the more complex file formats, the header may contain information about the type of compression used and other necessary parameters to create the image, I(r,c).

4. TIFF(Tagged Image File Format) and GIF(Graphics Interchange Format): They are used on World Wide Web (WWW). GIF files are limited to a maximum of 8 bits/pixel and allows for a type of compression called LZW. The GIF image header is 13 byte long & contains basic information.. JPEG (Joint photo Graphic Experts Group): 5. JPEG (Joint photo Graphic Experts Group): It is simply becoming standard that allows images compressed algorithms to be used in many different computer platforms. JPEG images compression is being used extensively on the WWW. It’s, flexible, so it can create large files with excellent image equality. 6.VIP(visualization in image processing )formats: It is developed for the CVIP tools software, when performing temporary images are created that use floating point representation which is beyond the standard 8 bit/pixel. To represent this type of data the remapping issued, which is the process of taking original image and adding an equation to translate it to the rang (0-225).

PNG is also a lossless storage format. However, in contrast with common TIFF usage, it looks for patterns in the image that it can use to compress file size. The compression is exactly reversible, so the image is recovered exactly. file size. 8. RAW is an image output option available on some digital cameras. Though lossless, it is a factor of three of four smaller than TIFF files of the same image. The disadvantage is that there is a different RAW format for each manufacturer, and so you may have to use the manufacturer's software to view the images.. PSD, PSP, etc., are proprietary formats used by graphics programs. Photoshop's files have the PSD extension, while Paint Shop Pro files use PSP. These are the preferred working formats as you edit images in the software, because only the proprietary formats retain all the editing power of the programs. These packages use layers,

Sign Filesize Unused Dataofset headresize width height colorplanes bitperpixel Typeo fco press ImagesizeHresoltion Vresolution nofcoloredused nofcolorimportant Image file

Private Type header_bmp  Sign (1 To 2) As Byte  Filesize As Long  Unused1 As Long  Dataofset As Long  headresize As Long  width As Long  height As Long  colorplanes As Integer  bitperpixel As Integer  Typeofcopress As Integer  Imagesize As Long  Hresoltion As Long  Vresolution As Long  nofcoloredused As Long  nofcolorimportant As Long End Type Dim imh As header_bmp General In visual basic Private Type Pixel R as byte G as byte B as byte End type Dim pix ( ) as pixel

cd1.ShowOpen Picture1.Picture = LoadPicture(cd1.FileName) Open cd1.FileName For Binary As #1 Get #1,, imh Close #1 cd1.ShowOpen Picture1.Picture = LoadPicture(cd1.FileName) Open cd1.FileName For Binary As #1 Get #1,, imh Close #1 private

cd1.ShowOpen Picture1.Picture = LoadPicture(cd1.FileName) Open cd1.FileName For Binary As #1 Get #1,, imh Redim pix(imh. Width, imh. height ) Get #1,,pix() Close #1 cd1.ShowOpen Picture1.Picture = LoadPicture(cd1.FileName) Open cd1.FileName For Binary As #1 Get #1,, imh Redim pix(imh. Width, imh. height ) Get #1,,pix() Close #1 Redim إيعاز لإعادة تحجيم المصفوفات اعتمادا على حجم الصورة