1、Courseware download:ftp:/ download password: downloadDigital Image Processing:Digital Imaging FundamentalsDr. Guangming LuL3of58ContentsMain purpose: introduce several concepts related to DIP and some of the notation used throughout the course.This lecture will cover: Human vision system Light and E

2、lectromagnetic spectrum Image acquisition Sampling and Quantization Resolution Basic Relationships Between Pixels4of58Human Visual SystemuThe best vision model we have!uKnowledge of how images form in the eye can help us with processing digital imagesuWe will take just a whirlwind tour of the human

3、visual system5of58Structure of the Human EyenThe lens focuses light from objects onto the retinanThe retina is covered with light receptors called cones (6-7 million) and rods (75-150 million)nCones are concentrated around the fovea and are very sensitive to colournRods are more spread out and are s

4、ensitive to low levels of illumination6of58Structure of the Human Eye7of58Blind-Spot ExperimentDraw 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 yo

5、ur face and move it slowly towards youThe dot should disappear!8of58Brightness Adaptation & Discriminationn 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.n Th

6、e human visual system can perceive approximately 1010 different light intensity levelsn Subjective brightness is a logarithm function of the light intensity incident on the eye.n However, at any one time we can only discriminate between a much smaller number brightness adaptation 9of58nFor a given s

7、et of conditions, the current sensitivity level of the visual system is called the brightness adaptation level.Brightness Adaptation & Discrimination10of58Brightness Adaptation & Discrimination (cont)Perceived brightness is not a simple function of intensity：Mach Bands(1865)Seeing is believi

8、ng? 11of58Brightness Adaptation & Discrimination (cont)nSimilarly, the perceived intensity of a region is related to the light intensities of the regions surrounding it12of58Brightness Adaptation & Discrimination (cont)Another experiment: a piece of paper on a desk is always white, but can a

9、ppear totally black when used to shield the eyes while looking directly at a bright sky13of58Optical IllusionsOur visual systems play lots of interesting tricks on us14of58Optical Illusions (cont)15of58Light and the Electromagnetic SpectrumNewton, 1666Violet, Blue, Green, Yellow, Orange, and RedBlen

10、ds smoothly into the next.Light is just a particular part of the electromagnetic spectrum that can be sensed by the human eye16of58Light and the Electromagnetic Spectrum17of58Light and the Electromagnetic SpectrumnVisible light: 0.430.79umnThe electromagnetic spectrum is split up according to the wa

11、velengths of different forms of energyWhere c is the speed of the light, v is the frequency, and h is the Plancks constanthvEvc,18of58Light and the Electromagnetic SpectrumlA stream of massless particleslEach massless particle contains a certain amount of energy.lEach bundle of energy is called a ph

12、otonlHigh frequency electromagnetic phenomena carry more energy per photon. That is the reason that gamma rays are so dangerous to living organisms. 19of58Light and the Electromagnetic SpectrumnThe colours that we perceive are determined by the nature of the light reflected from an objectnFor exampl

13、e, if white light is shone onto a green object most wavelengths are absorbed, while green light is reflected from the objectWhite LightColours AbsorbedGreen Light20of58Light reflectance propertiesA body that reflects light and is relatively balanced in all visible wavelengths appears white to the ob

14、server.A body that favors reflectance in a limited range of the visible spectrum exhibits some shades of color.Achromatic or monochromatic light: the only attribute is intensity-Gray-level Black to Gray to WhiteLight and the Electromagnetic Spectrum21of58Chromatic light Three basic quantities to des

15、cribe the quality of a chromatic light source:Radiance (Watts: W)（發光強度） The total amount of energy that flows from the light source.Luminance (lumen: lm)(光通量） A measure of the amount of energy an observer perceives from a light source. Example: Far Infrared RegionBrightness Subjective descriptor of

16、light perception that is practically impossible to measure.Light and the Electromagnetic Spectrum22of58Light and the Electromagnetic SpectrumnIn principle, if a sensor can be developed that is capable of detecting energy radiated by a band of the electromagnetic spectrum, we can image events of inte

17、rest in that band.nHowever, the wavelength of an electromagnetic wave require to “see” an object must be of the same size as or smaller than the object.nElectromagnetic waves is not the only method for image generation. Such as sound reflection-ultrasonic imagesnNote there is an error in the referen

18、ce book in this section, far infrared should be far ultraviolet. Page 35.23of58Other EM Spectrum: Short-wavelength EndGamma rays Medical Imaging Astronomical Imaging Radiation in nuclear environmentsHard X Rays Industrial ApplicationsSoft X Rays Chest X-Ray (shorter wavelength end) Dental X-Ray (low

19、er energy end)Ultraviolet Microscopy ImagingInfrared region: Near-infrared Far-InfraredMicrowave Microwave Ovens, Communication, RadarRadio wave AM, FM, TV, and Medical imaging Stellar bodies observationLight and the Electromagnetic Spectrumtumourinfraredvisible24of58Image AcquisitionImages are typi

20、cally generated by illuminating a scene and absorbing the energy reflected by the objects in that scene.25of58Imaging SensorsuImage acquisition sensorsuSingle sensoruStrip sensoruSensor array26of58nIncoming energy lands on a sensor material responsive to that type of energy and this generates a cont

21、inuous voltagenTo create a digital image, we need to convert the continuous sensed data into digital form.nThis involves two steps: sampling and quantization.Image Sampling and Quantization27of58Image Sampling and Quantization28of58Image Sampling and QuantizationnDigitizing the coordinate values is

22、called sampling, and digitizing the amplitude values is called quantization.nQuantisation is the process of converting a continuous analogue signal into a digital representation of this signal29of58Mathematical StatementLet Z be the set of real integersR the set of real numbersSampling: Partition th

23、e 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 real number in R) to eac

24、h distinct pair of coordinate (x, y).Image Sampling and Quantization30of58Representation) 1, 1() 1 , 1()0 , 1() 1, 1 () 1 , 1 ()0 , 1 () 1, 0() 1 , 0()0 , 0(),(NMfMfMfNfffNfffjif1, 11 , 10, 11, 11 , 10, 11, 01 , 00, 0NMMMNNaaaaaaaaaA31of58)(BitkNMbk2LBoth spatial and gray level resolutions determine

25、 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 pixels The storage size (no compression, no overhead):1600 x 6 = 9600 bits = 1200 bytes 1.17 KBRepresentationUsually, the M and N are positive in

26、tegers, and the number of gray levels is an integer power of 2:32of58Representation33of58Spatial & Intensity Level ResolutionuThe spatial resolution of an image is determined by how sampling was carried out.uSpatial resolution simply refers to the smallest discernable detail in an image Vision s

27、pecialists will often talk about pixel size Graphic designers will talk about dots per inch (DPI)5.1 Megapixels34of58Intensity level resolution refers to the number of intensity levels used to represent the image The more intensity levels used, the finer the level of detail discernable in an image I

28、ntensity level resolution is usually given in terms of the number of bits used to store each intensity levelNumber of BitsNumber of Intensity LevelsExamples120, 12400, 01, 10, 114160000, 0101, 1111825600110011, 010101011665,5361010101010101010Spatial & Intensity Level Resolution35of58Spatial &am

29、p; Intensity Level Resolution36of581024 * 1024512 * 512256 * 256128 * 12864 * 6432 * 32Spatial & Intensity Level Resolution37of58128 grey levels (7 bpp)64 grey levels (6 bpp)32 grey levels (5 bpp)16 grey levels (4 bpp)8 grey levels (3 bpp)4 grey levels (2 bpp)2 grey levels (1 bpp)256 grey levels

30、 (8 bits per pixel)Spatial & Intensity Level Resolution38of58Spatial resolution: M*NGray level resolution：LHow many samples and gray levels are required for a good approximation? Resolution (the degree of discernible detail) of an image depends on sample number and gray level number. i.e. the mo

31、re 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 kSpatial & Intensity Level Resolution39of58The big question with resolution is always: “how much is enough?” T

32、his all depends on what is in the image and what you would like to do with it Key questions include Does the image look aesthetically pleasing? Can you see what you need to see within the image?Spatial & Intensity Level Resolution40of58The picture on the right is fine for counting the number of

33、cars, but not for reading the number plateSpatial & Intensity Level Resolution41of58Zooming OversamplingShrinking SubsamplingZooming and Shrinking Digital Images42of58Zooming: The creation of new pixel locations The assignment of gray levels to those new locations Nearest neighbor interpolation

34、(NN) Pixel replication: a special case of NN NN produces checkerboard effectZooming and Shrinking Digital ImagesNNGray level43of58Zooming: Bilinear interpolation Using 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 ImagesABUEQCBOC

35、PSARTVDDFXYXYZ(a)(b)x, y()x, y, z)()()()()()(AgAgBgixEg)()()()()(CgCgDgixFg)()()()(),(EgEgFgjyyxg44of58Zooming and Shrinking Digital Images45of58Shrinking: Similar manner as just described for zooming. Delete Expand the grid: Nearest Neighbor interpolation Bilinear interpolationZooming and Shrinking

36、 Digital Images46of58Basic Relationships Between PixelsA pixel p at (x,y) has 2 horizontal and 2 vertical neighbors: (x+1,y), (x-1,y), (x,y+1), (x,y-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(

37、p) + ND(p) N8(p): the 8-neighbors of pDefinitions: f(x,y): digital image Pixels: q, pN4N4PN4N4NDNDPNDNDN8N8N8N8PN8N8N8N847of58Basic Relationships Between Pixels000000000000000110000000001111100000011111110000011111110000001111110000001111111000001111111110000001111110000000000000SN4(p)QN8(p)PND(p)48

38、of58ConnectivityConnectivity between pixels is important: Because it is used in establishing boundaries of objects and components of regions in an imageTwo pixels are connected if:uThey are neighbors (i.e. adjacent in some sense - e.g. N4(p), N8(p), )uTheir gray levels satisfy a specified criterion

39、of similarity (e.g. equality, )V is the set of gray-level values used to define adjacency (e.g. V=1 for adjacency of pixels of value 1)49of58AdjacencyWe 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 &

40、 q are 8- adjacent if q is in the set N8(p) m-adjacency: p & q with values from V are m-adjacent if q is in N4(p) or q is in ND(p) and the set N4(p)N4(q) has no pixels with values from V50of58AdjacencyMixed adjacency is a modification of 8-adjacency and is used to eliminate the multiple path con

41、nections that often arise when 8-adjacency is used.100010110100010110100010110V=1 8-adjacencym-adjacency51of58Path(通路)u A sequence of adjacent pixels.u 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,

42、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. uIf (x0, y0) = (xn, yn), the path is a closed path(閉合通路閉合通路). uWe can define 4-, 8-, and m-path depending on the type of adjacency. Path52of58Path4-Pathm-Path8-Path53of58Definitions:uLet S repres

43、ent a subset of pixels in an image. Two pixel p and q are said to be connected (連通連通) in S if there exists a path between them.uFor any pixel p in S, the set of pixels that are connected to it in S is called a connected component（連通分量）（連通分量） of S.uIf it only has one connected component, then set S is called a connected set(連通集連通集).uLet R be a subset of pixels in an image. We also