EEE 6512 Image Processing and Computer Vision Lecture 2 Introduction to Digital Image ProcessingDr. Dapeng Oliver WuUniversity of FloridaDepartment of Electrical and Computer EngineeringFall 2015

*Lecture OutlineApplications of image processingImage formation and perceptionImage representationMatlab primerImage processing demos

*Application Areas of Image ProcessingPurpose of image processingImprovement of pictorial information for human interpretationProcessing of image data for storage, transmission, and representation for autonomous machine perceptionTypical application areasTelevision Signal ProcessingSatellite Image ProcessingMedical Image ProcessingComputer Vision and Robot ControlVisual CommunicationsBiometrics for Law Enforcement

*Television Signal ProcessingImage brightness, contrast, color hue adjustmentTelevision image enhancementHigh Definition TV (HDTV)

*Satellite Image ProcessingRemote sensingClimate SatelliteDoppler radarGeologyLand resourceFlood monitorNew York (from Landast-5 TM)Doppler refers to the principle the Austrian scientist Christian Doppler discovered in 1842.

*Medical Image ProcessingImages are acquired to get information about Anatomy and Physiology of a patient

Ultra Sound (US)

Magnetic Resonance Imaging

Positron Emission Tomography (PET)

Computer Tomography (CT)

XRays

*Computed Tomography (CT) Allan M. Cormack and Godfrey N. Hounsfield won Nobel Prize in Physiology or Medicine in 1979 for development of CTHow CT was invented?Cormack proposed the back-projection method to generate a three-dimensional image of the internals of a human body from a large series of two-dimensional X-ray images taken around a single axis of rotation. Hounsfield constructed the first CT system practicable in medical care.

*Magnetic Resonance Imaging (MRI)Paul C Lauterbur and Peter Mansfield won Nobel Prize in Physiology or Medicine in 2003 for development of MRIHow MRI was invented?Paul Lauterbur proposed a method that uses gradient magnets along with the main magnet to detect signals for creating 2D images.Peter Mansfield proposed a signal processing method to transform the detected signals into a 2D image.

*Computer Vision and Robot ControlIndustry robots on production lineUnmanned operationsAutonomous Vehicle drivingDARPA Grand Challenge Race, LA to VegasAUVSI and ONR's Autonomous Underwater Vehicle Competition (U.F. SubjuGator won the first place in 2005, 2006, 2007)International Micro Air vehicle Competition (U.F. won every year since 1999)

Mars Rover

*Visual CommunicationVideophoneTele-conferencingTele-shoppingVideo codingVideo transmission

*Biometrics for Law EnforcementBiometric identification technology Fingerprint

Face recognition

IrisRetinaPalm DNAAR Face Database

*Components in Digital Image ProcessingKnowledge baseImageacquisitionImageenhancementImagerestorationColor imageprocessingWavelets andMultiresolutionprocessingCompressionMorphologicalprocessingSegmentationRepresentation& descriptionObject recognitionInputImageOutput are imagesOutput are image attributes

*Image Formation (Image Capture)Light source (: wavelength of the source)

Each point of the scene has a reflectivity function.

Light reflects from a point and the reflected light is captured by an imaging device.

*What is Light?Light is a form of electromagnetic (EM) radiation, with from 430nm to 790nm (visible light band).

*Illuminating and Reflecting LightIlluminating light sources: emit light (e.g. the sun, light bulb, TV monitors)perceived color depends on the emitted freq. follows additive ruleR+G+B=WhiteReflecting light sources: reflect an incoming light (e.g. the color dye, matte surface, cloth)perceived color depends on reflected freq (=emitted freq-absorbed freq.)follows subtractive ruleC+M+Y=Black

*ProjectionProjection (P) from world coordinates (x, y, z) to camera or image coordinates (x, y)

Two types of projections (P) of interest to us:Perspective ProjectionObjects closer to the capture device appear bigger. Most image formation situations can be considered to be under this category, including images taken by camera and the human eye.Orthographic ProjectionThis is unnatural. Objects appear the same size regardless of their distance to the capture device.

*Perspective Projection12z1z212PinholeFilmCoverObject 1Object 2

*Orthographic Projection12z1z212FilmObject 1Object 2

*Math Involved in Image FormationEuclidean geometryProjective geometryFormalize one of the central principles of perspective art: parallel lines meet at infinity and therefore are to be drawn that wayAffine geometryDo not involve any notions of origin, length or angle, but with the notion of subtraction of points giving a vector.

*Projective Geometry & Affine Geometry

*Light SensitivityEach capture device has its sensitivity function V().

The result is an image function which determines the amount of reflected light that is captured at the camera coordinates (x, y).

*Human Eye SystemEye Anatomy

*Receptors in the RetinaRodsNight visionLow acuity (low resolution)Achromatic ConesDay visionHigh acuityChromaticThree sets700nm (R), 546nm (G), 435nm (B)

*Image RepresentationAnalog image -> Digital imageSampling Quantization2D array of picture elements (pixels)

*Grayscale ImageThe intensity value of each pixel is 0 ~ 255Matrix representation

*Color ImageThree components M = {R, G, B}RGB

*A Brief Matlab TutorialAn interactive program from the MathWorks for high-performance numeric computation and visualization.Refer to Matlab Primer for general useType help image to see functions in image processing toolboxRun demos in image processing toolboxhttp://www.mathworks.com/products/image/demos.html

*Simple Matlab Commands>> x = imread('baboon.bmp');>> whos Name Size Bytes Class

x 256x256x3 196608 uint8 array

Grand total is 196608 elements using 196608 bytes

>> imshow(x);>> g = rgb2gray(x);>> imshow(g);>> g(1:2, 1:2)

ans =

64 46 77 75

*Image Processing DemosSimple point processingSpecial effectsNoise reductionImage enhancementImage restorationFace detectionImage segmentation

*Simple point processingOriginal imageHorizontal flipDiagonal flipDigital Negative

*Special EffectsOriginal ImageRotationSwirlWave

*Noise ReductionDegraded ImageNoise reduced Image

*Image EnhancementObserved ImageEnhanced Image

*Image RestorationDegraded ImageRestored Image

*Face DetectionFace tracking in a videoFace recognition

*Image SegmentationSegmentation of different object in the scene

*High Performance Imaging Using Large Camera ArraysImage mosaic: stitch multiple images into a panoramic viewHigh speed video capture: convert space into timeE.g., 52 cameras, each with 30 fps, provide 1560 fps Slowly replay high speed event (e.g., a moving bullet through balloons). Can a human see a moving bullet? Why not?

*Synthetic Aperture PhotographyBennett Wilburn et al., High performance imaging using large camera arrays, ACM SIGGRAPH 2005

*SpriteVideo object (foreground)Sprite (complete background)BlendingA sprite, also referred to as mosaic, is an image composed of pixelsbelonging to a video object visible throughout a video sequence.

Warping based on camera motion, e.g., perspective, bilinear, or affine mapping

*Example of MosaicMerge 10 pictures into one picture(how to remove the overlapped part?)

*Homework 1Use a digital camera or web cam to take a color picture of yourself and save the picture as a JPEG file with filename YourLastNameColor.jpg. Then use rgb2gray function in Matlab to convert your RGB color picture to a gray-scale image and save the gray-scale image as a JPEG file with filename YourLastNameGray.jpg. (You will need to use YourLastNameColor.jpg and YourLastNameGray.jpg for image processing in other homework assignments.)Submit the above two JPEG files through E-Learning web site under the directory of Homework 1. Due: 4pm, 9/9. Late submission will not be accepted.You can also check the calendar at https://lss.at.ufl.edu/ for all the assignment due dates.

*Homework 1 (no submission for the following items) Read the Matlab Primer and get familiar with Matlab. The Matlab primer can be found athttp://math.ucsd.edu/%7Edriver/21d-s99/matlab-primer.htmlType help image to see functions in image processing toolboxRun demos in image processing toolboxhttp://www.mathworks.com/products/image/demos.html

*Reading AssignmentDigital Image Processing, Chapter 1, Chapter 2 (Section 2.1 2.3)

******The embryo image from ultra soundThe CT of throaxXRays of hand*************************************