1/07/2003 W03/Lecture 1 1Digital Image ProcessingECE 178Winter 2003B. S. MANJUNATHRM 3157 ENGR ITel:[email protected]://vision.ece.ucsb.edu/Manjunath1/07/2003W03/Lecture 1 2On the WEBFor course information and slides and more:http://varuna.ece.ucsb.edu/ECE178Teaching AssistantsJelena Tesic ([email protected]) Marco Zuliani ([email protected])1/07/2003W03/Lecture 1 3Class e-mail list/Discussion sessions■ ALL Registered students: please send an e-mail to [email protected].– subject = “ECE 178– with your name (last, first)– e-mail address (if different)– If you have any schedule conflicts for either of the two discussion sessions (12-1250 or 0100-0150PM) on Fridays.■ Your e-mail address is needed to send course related information/announcements.1/07/2003W03/Lecture 1 4Today: Jan 07-2003■ Course outline■ Requirements for the course■ Introduction to image processing■ Matlab basics and the image processing toolbox1/07/2003W03/Lecture 1 5About this course■ Prerequisites– Strong motivation, basic calculus– MATLAB is the programming environment, but no prior background in MATLAB is assumed.■ Who can take this course?– Juniors/Seniors/Graduate students in ECE/CE/CS/ME/MATP/…■ Text Book: – Gonzalez and Woods, 2ndEdition (2002)– http://www.imageprocessingbook.com1/07/2003W03/Lecture 1 6Grading■ H/W /Comp* 20% due by 11:59pm on the due date■ Project 20%■ Midterms 20% (two mid-terms)■ Finals 40%* All homeworks are required. A non-submission will affectyour grade non-linearly.1/07/2003W03/Lecture 1 7Important Dates ■ Mid-term I: Tuesday, February 4, 2003.■ Mid-Term II: Tuesday, February 25 (tentative)■ Final Examination: Monday, March 17, 12-3pm (as per schedule)1/07/2003W03/Lecture 1 8Why Image Processing?■ The future is multimedia information processing……■ Images (and video) are everywhere!■ Many and diverse applications– Astronomy, biology, geology, geography, medicine, law enforcement, defense, Industrial inspection,…– Different imaging modalities: visual, X-ray, ultra-sound, …1/07/2003W03/Lecture 1 9Entertainment■ Digital camcorders■ HDTV ■ DVDs: High quality image/video compression (MPEG-2: about 5-10 Million bits/second)■ Digital Cinema– New compression technologies are needed– Consider a 2 hour movie: 1920 x 1080 x 30 bits/pixel x 24 frames/second ~~ 1.5 billion bits/second ! 1.3 terra bytes / 2 hr program1/07/2003W03/Lecture 1 10Security■ Person Identification– Face recognition– Finger print identification■ Watermarking– Copyright protection and authentication■ Data hiding– Secret communication (Steganography)1/07/2003W03/Lecture 1 11Some Applications■ X-ray imaging and radiology■ Computer Tomography[545x700 24-bit color JPEG, 69069 bytes] Section through Visible Human Male - head, including cerebellum, cerebral cortex, brainstem, nasal passages (from Head subset) http://www.nlm.nih.gov/research/visible/photos.html)1/07/2003W03/Lecture 1 12An Ultrasound imageProfile of a fetus at four months. This face is approximately 1 ½ inches (4cm) long. (http://www.parenthood.com)1/07/2003W03/Lecture 1 13Computer Tomography■ Generating 3-D images from 2-D slices.■ CAD, CAM applications■ Industrial inspectionsCT Scanner Picker PQ 6000 Model•GE Medical High Speed Advantage scanner •Picker PQ 60001/07/2003W03/Lecture 1 14Image/video Processing Methods■ Image Enhancement■ Image Restoration■ Compression■ Image reconstruction■ Morphological image processing■ Feature extraction and recognition"computer vision1/07/2003W03/Lecture 1 15Chapter 1: IntroductionChapter 1: Introduction1/07/2003W03/Lecture 1 16Image EnhancementEnhancement: Improve the visual quality of the image.Eg. Noise removal using median filtering(from http://www.nist.gov/lispix/imlab/noise/shotfc.html)1/07/2003W03/Lecture 1 17Image Restoration■ same as image enhancement, but you have additional information concerning the quality degradation. Example: removing motion blur in an image of a fast moving object.■ A page from Matlab examples or the matlab site at http://www.mathworks.com/products/demos/imagetlbx/examples/deblur/deblur.html1/07/2003W03/Lecture 1 18IP methods (cont.)■ Reconstruction: reconstruction from projections. Used in constructing 3D data from 2D projections in computer tomography.■ Image representation using features– Low level representations using color, texture, shape, motion, etc.– High level features for recognitions; e.g., facial features.■ Recognition and scene understanding1/07/2003W03/Lecture 1 19Image Processing, Pattern Recognition, Graphics, and Computer Vision■ Image Processing– This is about image to image transformation (image coding, enhancement, restoration, etc.) ECE 178, ECE 278a.■ Computer Graphics: CS 180/280■ Pattern Recognition: ECE 277b■ Computer Vision: ECE 181b/281b■ Multimedia computing: ECE 1601/07/2003W03/Lecture 1 20Course Outline■ Introduction – Chapters 1-2■ 2-D Linear Systems– Class notes;■ Sampling and Quantization– Class notes; Ch 2.4■ Image Enhancement – Ch. 3, 4■ Image and Video Coding■ Project presentations1/07/2003W03/Lecture 1 21Course Projects■ Why project?– To learn more about applications of image processing and get hands-on experience.– typically, the material (needed) is NOT covered in class - thus requires independent study (ten weeks is too short to cover all interesting topics!.)■ Winter 2003: This quarter we will explore Image compression in more detail– Wavelets based image compression (~JPEG2000)1/07/2003W03/Lecture 1 22Image Compression using Wavelets■ What are wavelets? (we will learn more about them later on..)■ Using wavelets for data compression– JPEG 2000 standard is based on wavelets– JPEG (original) is based on the Discrete Cosine Transform—you will learn DCT based compression in our discussions on image coding.1/07/2003W03/Lecture 1 23Previous year (2002) projects■ JPEG 2000■ Data hiding■ Streaming Video■ Image Mosaicing1/07/2003W03/Lecture 1 24Data HidingDroeshout engraving ofWilliam Shakespeare(192x240)A text message (1535 bytes)Steganography is the art and science of communicating in a way which hides the existence of the communication. In contrast to cryptography, where the "enemy" is allowed to detect, intercept and modify messages without being able to violate certain security premises guaranteed by a cryptosystem, the goal of