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1、Courseware download:ftp:/download password:download,Digital Image Processing:Digital Imaging Fundamentals,Dr.Guangming LuL,Contents,Main purpose:introduce several concepts related to DIP and some of the notation used throughout the course.This lecture will cover:Human vision systemLight and Electrom
2、agnetic spectrumImage acquisitionSampling and QuantizationResolutionBasic Relationships Between Pixels,Human Visual System,The best vision model we have!Knowledge of how images form in the eye can help us with processing digital imagesWe will take just a whirlwind tour of the human visual system,Str
3、ucture of the Human Eye,The lens focuses light from objects onto the retinaThe retina is covered with light receptors called cones(6-7 million)and rods(75-150 million)Cones are concentrated around the fovea and are very sensitive to colourRods are more spread out and are sensitive to low levels of i
4、llumination,Structure of the Human Eye,Blind-Spot Experiment,Draw an image similar to that below on a piece of paper(the dot and cross are about 6 inches apart)Close your right eye and focus on the cross with your left eyeHold the image about 20 inches away from your face and move it slowly towards
5、youThe dot should disappear!,Brightness Adaptation&Discrimination,Because digital images are displayed as a discrete set of intensities,the eyes ability to discriminate between different intensity levels is an important consideration in DIP results.The human visual system can perceive approximately
6、1010 different light intensity levelsSubjective brightness is a logarithm function of the light intensity incident on the eye.However,at any one time we can only discriminate between a much smaller number brightness adaptation,For a given set of conditions,the current sensitivity level of the visual
7、 system is called the brightness adaptation level.,Brightness Adaptation&Discrimination,Brightness Adaptation&Discrimination(cont),Perceived brightness is not a simple function of intensity：Mach Bands(1865),Seeing is believing?,Brightness Adaptation&Discrimination(cont),Similarly,the perceived inten
8、sity of a region is related to the light intensities of the regions surrounding it,Brightness Adaptation&Discrimination(cont),Another experiment:a piece of paper on a desk is always white,but can appear totally black when used to shield the eyes while looking directly at a bright sky,Optical Illusio
9、ns,Our visual systems play lots of interesting tricks on us,Optical Illusions(cont),Light and the Electromagnetic Spectrum,Newton,1666Violet,Blue,Green,Yellow,Orange,and Red,Blends smoothly into the next.,Light is just a particular part of the electromagnetic spectrum that can be sensed by the human
10、 eye,Light and the Electromagnetic Spectrum,Light and the Electromagnetic Spectrum,Visible light:0.430.79umThe electromagnetic spectrum is split up according to the wavelengths of different forms of energyWhere c is the speed of the light,v is the frequency,and h is the Plancks constant,Light and th
11、e Electromagnetic Spectrum,A stream of massless particlesEach massless particle contains a certain amount of energy.Each bundle of energy is called a photonHigh frequency electromagnetic phenomena carry more energy per photon.That is the reason that gamma rays are so dangerous to living organisms.,L
12、ight and the Electromagnetic Spectrum,The colours that we perceive are determined by the nature of the light reflected from an objectFor example,if white light is shone onto a green object most wavelengths are absorbed,while green light is reflected from the object,White Light,Colours Absorbed,Green
13、 Light,Light reflectance properties,A body that reflects light and is relatively balanced in all visible wavelengths appears white to the observer.A body that favors reflectance in a limited range of the visible spectrum exhibits some shades of color.Achromatic or monochromatic light:the only attrib
14、ute is intensity-Gray-levelBlack to Gray to White,Light and the Electromagnetic Spectrum,Chromatic light,Three basic quantities to describe the quality of a chromatic light source:Radiance(Watts:W)（发光强度）The total amount of energy that flows from the light source.Luminance(lumen:lm)(光通量）A measure of
15、the amount of energy an observer perceives from a light source.Example:Far Infrared RegionBrightnessSubjective descriptor of light perception that is practically impossible to measure.,Light and the Electromagnetic Spectrum,Light and the Electromagnetic Spectrum,In principle,if a sensor can be devel
16、oped that is capable of detecting energy radiated by a band of the electromagnetic spectrum,we can image events of interest in that band.However,the wavelength of an electromagnetic wave require to“see”an object must be of the same size as or smaller than the object.Electromagnetic waves is not the
17、only method for image generation.Such as sound reflection-ultrasonic imagesNote there is an error in the reference book in this section,far infrared should be far ultraviolet.Page 35.,Other EM Spectrum:Short-wavelength End,Gamma raysMedical ImagingAstronomical ImagingRadiation in nuclear environment
18、sHard X RaysIndustrial ApplicationsSoft X RaysChest X-Ray(shorter wavelength end)Dental X-Ray(lower energy end)UltravioletMicroscopy ImagingInfrared region:Near-infraredFar-InfraredMicrowaveMicrowave Ovens,Communication,RadarRadio waveAM,FM,TV,and Medical imagingStellar bodies observation,Light and
19、the Electromagnetic Spectrum,Image Acquisition,Images are typically generated by illuminating a scene and absorbing the energy reflected by the objects in that scene.,Imaging Sensors,Image acquisition sensorsSingle sensorStrip sensorSensor array,Incoming energy lands on a sensor material responsive
20、to that type of energy and this generates a continuous voltageTo create a digital image,we need to convert the continuous sensed data into digital form.This involves two steps:sampling and quantization.,Image Sampling and Quantization,Image Sampling and Quantization,Image Sampling and Quantization,D
21、igitizing the coordinate values is called sampling,and digitizing the amplitude values is called quantization.Quantisation is the process of converting a continuous analogue signal into a digital representation of this signal,Mathematical Statement,Let Z be the set of real integersR the set of real
22、numbersSampling:Partition the xy plane into a grid.The coordinates of the center of each grid being a pair of elements from the Cartesian product Z2.The set of all ordered pairs of elements(zi,zj).With zi and zj being integers from Z.Quantization:f is a function that assigns a gray-level value(a rea
23、l number in R)to each distinct pair of coordinate(x,y).,Image Sampling and Quantization,Representation,Both spatial and gray level resolutions determine the storage size of an image(bytes)e.g.spatial resolution:40 x 40gray level resolution:64(log264=6 bits/pixel)The number of pixels:40 x 40=1600 pix
24、els The storage size(no compression,no overhead):1600 x 6=9600 bits=1200 bytes 1.17 KB,Representation,Usually,the M and N are positive integers,and the number of gray levels is an integer power of 2:,Representation,Spatial&Intensity Level Resolution,The spatial resolution of an image is determined b
25、y how sampling was carried out.Spatial resolution simply refers to the smallest discernable detail in an imageVision specialists will often talk about pixel sizeGraphic designers will talk about dots per inch(DPI),5.1 Megapixels,Intensity level resolution refers to the number of intensity levels use
26、d to represent the imageThe more intensity levels used,the finer the level of detail discernable in an imageIntensity level resolution is usually given in terms of the number of bits used to store each intensity level,Number of Bits,Number of Intensity Levels,Examples,1,2,0,1,2,4,00,01,10,11,4,16,00
27、00,0101,1111,8,256,00110011,01010101,16,65,536,1010101010101010,Spatial&Intensity Level Resolution,Spatial&Intensity Level Resolution,1024*1024,512*512,256*256,128*128,64*64,32*32,Spatial&Intensity Level Resolution,128 grey levels(7 bpp),64 grey levels(6 bpp),32 grey levels(5 bpp),16 grey levels(4 b
28、pp),8 grey levels(3 bpp),4 grey levels(2 bpp),2 grey levels(1 bpp),256 grey levels(8 bits per pixel),Spatial&Intensity Level Resolution,Spatial resolution:M*NGray level resolution：LHow many samples and gray levels are required for a good approximation?Resolution(the degree of discernible detail)of a
29、n image depends on sample number and gray level number.i.e.the more these parameters are increased,the closer the digitized array approximates the original image.But:storage&processing requirements increase rapidly as a function of N,M,and k,Spatial&Intensity Level Resolution,The big question with r
30、esolution is always:“how much is enough?”This all depends on what is in the image and what you would like to do with itKey questions includeDoes the image look aesthetically pleasing?Can you see what you need to see within the image?,Spatial&Intensity Level Resolution,The picture on the right is fin
31、e for counting the number of cars,but not for reading the number plate,Spatial&Intensity Level Resolution,Zooming OversamplingShrinking Subsampling,Zooming and Shrinking Digital Images,Zooming:The creation of new pixel locationsThe assignment of gray levels to those new locationsNearest neighbor int
32、erpolation(NN)Pixel replication:a special case of NNNN produces checkerboard effect,Zooming and Shrinking Digital Images,Zooming:Bilinear interpolationUsing the four NNs of a point.G(A),G(B),G(C),G(D)are the gray levels of pint A,B,C,D.,Zooming and Shrinking Digital Images,Zooming and Shrinking Digi
33、tal Images,Shrinking:Similar manner as just described for zooming.DeleteExpand the grid:Nearest Neighbor interpolationBilinear interpolation,Zooming and Shrinking Digital Images,Basic Relationships Between Pixels,A pixel p at(x,y)has 2 horizontal and 2 vertical neighbors:(x+1,y),(x-1,y),(x,y+1),(x,y
34、-1)This set of pixels is called the 4-neighbors of p:N4(p),The 4 diagonal neighbors of p are:(ND(p)-(x+1,y+1),(x+1,y-1),(x-1,y+1),(x-1,y-1)-N4(p)+ND(p)N8(p):the 8-neighbors of p,Definitions:f(x,y):digital imagePixels:q,p,Basic Relationships Between Pixels,Connectivity,Connectivity between pixels is
35、important:Because it is used in establishing boundaries of objects and components of regions in an image,Two pixels are connected if:They are neighbors(i.e.adjacent in some sense-e.g.N4(p),N8(p),)Their gray levels satisfy a specified criterion of similarity(e.g.equality,)V is the set of gray-level v
36、alues used to define adjacency(e.g.V=1 for adjacency of pixels of value 1),Adjacency,We consider three types of adjacency:4-adjacency:two pixels p and q with values from V are 4-adjacent if q is in the set N4(p)8-adjacency:p&q are 8-adjacent if q is in the set N8(p)m-adjacency:p&q with values from V
37、 are m-adjacent ifq is in N4(p)orq is in ND(p)and the set N4(p)N4(q)has no pixels with values from V,Adjacency,Mixed adjacency is a modification of 8-adjacency and is used to eliminate the multiple path connections that often arise when 8-adjacency is used.,V=1,8-adjacency,m-adjacency,Path(通路)A sequ
38、ence of adjacent pixels.For example:a path from pixel p with coordinate(x,y)to pixel q with coordinate(s,t)is defined(x0,y0)，(x1,y1)，(xn,yn)Where(x0,y0)=(x,y)，(xn,yn)=(s,t),(xi,yi)and(xi-1,yi-1)are adjacent,1 i n,n is called the length of the path.If(x0,y0)=(xn,yn),the path is a closed path(闭合通路).We
39、 can define 4-,8-,and m-path depending on the type of adjacency.,Path,Path,4-Path,m-Path,8-Path,Definitions:Let S represent a subset of pixels in an image.Two pixel p and q are said to be connected(连通)in S if there exists a path between them.For any pixel p in S,the set of pixels that are connected
40、to it in S is called a connected component（连通分量）of S.If it only has one connected component,then set S is called a connected set(连通集).Let R be a subset of pixels in an image.We also called R a region(区域)of the image is R is a connected set.The boundary(边界，或边缘、轮廓)of a region R is the set of pixels in
41、 the region that have one or more neighbors that are not in R.,Connected Set and Region,Distance Measures,For pixels p,q,z with coordinates(x,y),(s,t),(u,v),D is a distance function or metric if:D(p,q)0(D(p,q)=0 if p=q)D(p,q)=D(q,p)andD(p,z)D(p,q)+D(q,z),Distance Measures,Euclidean distance(p(x,y),q
42、(s,t):De(p,q)=(x-s)2+(y-t)21/2Points(pixels)having a distance less than or equal to r from(x,y)are contained in a disk of radius r centered at(x,y).,Distance Measures,D4 distance(city-block distance):D4(p,q)=|x-s|+|y-t|forms a diamond centered at(x,y)e.g.pixels with D42 from p,D4=1 are the 4-neighbo
43、rs of p,Distance Measures,D8 distance(chessboard distance):D8(p,q)=max(|x-s|,|y-t|)Forms a square centered at pe.g.pixels with D82 from p,D8=1 are the 8-neighbors of p,Euclidean distance(2-norm),D4 distance(city-block distance),D8 distance(checkboard distance),0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,2
44、,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,4,4,4,4,2,2,2,2,Common Distance Definitions,Summary,We have looked at:Human vision systemLight and Electromagnetic spectrumImage acquisitionSampling and QuantizationResolutionBasic Relationships Between PixelsNext time we start to look at techniques for image enhancement,
