1、Digital Image Processing Chapter 2: Digital Image Fundamental 6 June 2007,What is Digital Image Processing ?,Processing of a multidimensional pictures by a digital computer,Why we need Digital Image Processing ?,To record and store images To enhance images using mathematics To analysis images To syn

2、thesize images To create computer vision systems,Digital Image,Digital image = a multidimensional array of numbers (such as intensity image) or vectors (such as color image),Each component in the image called pixel associates with the pixel value (a single number in the case of intensity images or a

3、 vector in the case of color images).,Visual Perception: Human Eye,(Picture from Microsoft Encarta 2000),Cross Section of the Human Eye,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,The lens contains 60-70% water, 6% of fat. The iris diaphragm controls a

4、mount of light that enters the eye. Light receptors in the retina - About 6-7 millions cones for bright light vision called photopic - Density of cones is about 150,000 elements/mm2. - Cones involve in color vision. - Cones are concentrated in fovea about 1.5x1.5 mm2. - About 75-150 millions rods fo

5、r dim light vision called scotopic - Rods are sensitive to low level of light and are not involved color vision. 4. Blind spot is the region of emergence of the optic nerve from the eye.,Visual Perception: Human Eye (cont.),Range of Relative Brightness Sensation,Simutaneous range is smaller than Tot

6、al adaptation range,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Distribution of Rods and Cones in the Retina,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Image Formation in the Human Eye,(Picture from Micr

7、osoft Encarta 2000),(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Brightness Adaptation of Human Eye : Mach Band Effect,Mach Band Effect,Intensities of surrounding points effect perceived brightness at each point. In this image, edges between bars appear

8、 brighter on the right side and darker on the left side.,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,In area A, brightness perceived is darker while in area B is brighter. This phenomenon is called Mach Band Effect.,Position,Intensity,A,B,Mach Band Eff

9、ect (Cont),Simultaneous contrast. All small squares have exactly the same intensity but they appear progressively darker as background becomes lighter.,Brightness Adaptation of Human Eye : Simultaneous Contrast,Simultaneous Contrast,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image

10、Processing, 2nd Edition.,Optical illusion,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Visible Spectrum,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Image Sensors,Single sensor,Line sensor,Array sensor,(Ima

11、ges from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Image Sensors : Single Sensor,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Image Sensors : Line Sensor,Fingerprint sweep sensor,Computerized Axial Tomography,(Images

12、 from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,CCD KAF-3200E from Kodak. (2184 x 1472 pixels, Pixel size 6.8 microns2),Charge-Coupled Device (CCD),w Used for convert a continuous image into a digital image w Contains an array of light sensors w Converts photon i

13、nto electric charges accumulated in each sensor unit,Image Sensors : Array Sensor,Horizontal Transportation Register,Output Gate,Amplifier,Photosites,Output,Image Sensor: Inside Charge-Coupled Device,Image Sensor: How CCD works,Vertical shift,Horizontal shift,Image pixel,Horizontal transport registe

14、r,Output,Image “After snow storm”,Fundamentals of Digital Images,w An image: a multidimensional function of spatial coordinates. w Spatial coordinate: (x,y) for 2D case such as photograph, (x,y,z) for 3D case such as CT scan images (x,y,t) for movies w The function f may represent intensity (for mon

15、ochrome images) or color (for color images) or other associated values.,Digital Images,Digital image: an image that has been discretized both in Spatial coordinates and associated value. w Consist of 2 sets:(1) a point set and (2) a value set w Can be represented in the form I = (x,a(x): x X, a(x) F

16、 where X and F are a point set and value set, respectively. w An element of the image, (x,a(x) is called a pixel where - x is called the pixel location and - a(x) is the pixel value at the location x,Conventional Coordinate for Image Representation,(Images from Rafael C. Gonzalez and Richard E. Wood

17、, Digital Image Processing, 2nd Edition.,Digital Image Types : Intensity Image,Intensity image or monochrome image each pixel corresponds to light intensity normally represented in gray scale (gray level).,Gray scale values,Digital Image Types : RGB Image,Color image or RGB image: each pixel contain

18、s a vector representing red, green and blue components.,RGB components,Image Types : Binary Image,Binary image or black and white image Each pixel contains one bit : 1 represent white 0 represents black,Binary data,Image Types : Index Image,Index image Each pixel contains index number pointing to a

19、color in a color table,Index value,Color Table,Digital Image Acquisition Process,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Generating a Digital Image,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Image Sa

20、mpling and Quantization,Image sampling: discretize an image in the spatial domain Spatial resolution / image resolution: pixel size or number of pixels,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,How to choose the spatial resolution,Original image,Samp

21、led image,Under sampling, we lost some image details!,Spatial resolution,How to choose the spatial resolution : Nyquist Rate,Original image,No detail is lost!,Nyquist Rate: Spatial resolution must be less or equal half of the minimum period of the image or sampling frequency must be greater or Equal

22、 twice of the maximum frequency.,2mm,1mm,Sampling rate: 5 samples/sec,Aliased Frequency,Two different frequencies but the same results !,Effect of Spatial Resolution,Effect of Spatial Resolution,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Moire Pattern

23、 Effect : Special Case of Sampling,Moire patterns occur when frequencies of two superimposed periodic patterns are close to each other.,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Effect of Spatial Resolution,(Images from Rafael C. Gonzalez and Richard

24、 E. Wood, Digital Image Processing, 2nd Edition.,Can we increase spatial resolution by interpolation ?,Down sampling is an irreversible process.,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2nd Edition.,Image Quantization,Image quantization: discretize continuous pi

25、xel values into discrete numbers Color resolution/ color depth/ levels: - No. of colors or gray levels or - No. of bits representing each pixel value - No. of colors or gray levels Nc is given by,where b = no. of bits,Quantization function,Light intensity,Quantization level,0,1,2,Nc-1,Nc-2,Darkest,B

26、rightest,Effect of Quantization Levels,256 levels,128 levels,32 levels,64 levels,Effect of Quantization Levels (cont.),16 levels,8 levels,2 levels,4 levels,How to select the suitable size and pixel depth of images,Low detail image,Medium detail image,High detail image,Lena image,Cameraman image,To s

27、atisfy human mind 1. For images of the same size, the low detail image may need more pixel depth. 2. As an image size increase, fewer gray levels may be needed.,The word “suitable” is subjective: depending on “subject”.,(Images from Rafael C. Gonzalez and Richard E. Wood, Digital Image Processing, 2

28、nd Edition.,Basic Relationship of Pixels,x,y,(0,0),Conventional indexing method,Neighbors of a Pixel,p,4-neighbors of p:,(x-1,y) (x+1,y) (x,y-1) (x,y+1),Neighborhood relation is used to tell adjacent pixels. It is useful for analyzing regions.,Note: q N4(p) implies p N4(q),4-neighborhood relation co

29、nsiders only vertical and horizontal neighbors.,p,(x+1,y),(x-1,y),(x,y-1),(x,y+1),(x+1,y-1),(x-1,y-1),(x-1,y+1),(x+1,y+1),Neighbors of a Pixel (cont.),8-neighbors of p:,(x-1,y-1) (x,y-1) (x+1,y-1) (x-1,y) (x+1,y) (x-1,y+1) (x,y+1) (x+1,y+1),N8(p) =,8-neighborhood relation considers all neighbor pixe

30、ls.,p,(x+1,y-1),(x-1,y-1),(x-1,y+1),(x+1,y+1),Diagonal neighbors of p:,ND(p) =,(x-1,y-1) (x+1,y-1) (x-1,y+1) (x+1,y+1),Neighbors of a Pixel (cont.),Diagonal -neighborhood relation considers only diagonal neighbor pixels.,Connectivity,Connectivity is adapted from neighborhood relation. Two pixels are

31、 connected if they are in the same class (i.e. the same color or the same range of intensity) and they are neighbors of one another. For p and q from the same class w 4-connectivity: p and q are 4-connected if q N4(p) w 8-connectivity: p and q are 8-connected if q N8(p) w mixed-connectivity (m-connectivity): p and q are m-connected if q N4(p) or q ND(p) and N4(p) N4(q) = ,Adjacency,A pixel p is adjacent to pixel q is they are connected. Two image subsets S1 and S2 are adjacent if some pixel in