Digital Image Processing Ligang Liu Zhejiang University

Media

A picture is worth 1000 words … A video is worth 1000 sentences … Rich information from visual data Examples of images around us Natural photographic images Artistic and engineering drawings Scientific images (satellite, medical, etc.) Motion picture – video Movies, TV programs, news Family video Surveillance and highway camera

Why do we process images? Enhancement and restoration remove artifacts and scratches from an old photo/movie improve contrast and correct blurred images Transmission and storage images from oversea via Internet, or from a remote planet Information analysis and automated recognition providing “ human vision ” to machines Security and rights protection encryption and watermarking

Why Digital? “ Exactness ” Perfect reproduction without degradation Perfect duplication of processing result Convenient & powerful computer-aided processing Can perform rather sophisticated processing through hardware or software Even kindergartners can do it! Easy storage and transmission 1 CD can store hundreds of family photos! Paperless transmission of high quality photos through network within seconds

Human Vision System Image is to be seen. Perceptual Based Image Processing Focus on perceptually significant information Discard perceptually insignificant information Issues: Biological Psychophysical

Color Color is the perceptual result of light having wavelength 400 nm to 700 nm that is incident upon the retina. “ Power distribution exists in the physical world, but color exists only in the eye and the brain. ” Does “ red ” mean the same to different people?

Color Spectrum

Grassman's First Law of Additive Color Mixture Any color can be matched by a linear combination of three other colors (primaries, eg RGB), provided that none of those three can be matched by a combination of the other two. C= Rc(R ) + Gc(G) + Bc(B)

Color Spaces RGB CMY CIE XYZ s

Different Image Types Binary images (0 or 1) Gray images (0~255) Color images indexed color images full color images (24 bits per pixel, 8-red, 8-green, 8-blue) )

A Binary Image

Gray Images 8 bits per pixel

Full Color Images 24 bits per pixel, and the three channels R G B are three gray images respectively

Color Components

Image Programming class CImage { unsigned int width; unsigned int height; unsigned char *data; }; Not difficult …

Related Fields Imaging Medical, remote sensing, weather Computer vision Computer graphics Machine learning Video processing

Related Math Fourier analysis Wavelet Probability and statistics PDE Linear/nonlinear optimization Machine learning …

References Journals IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI) IEEE Transaction on Image Processing IEEE Transaction on Signal Processing IEEE Transaction on Circuits and System for Video Technology International Journal on Computer Vision (IJCV) Pattern Recognition Conferences Graphics Conferences (Siggraph … ) Vision conferences: ICCV, ECCV, ACCV, CVPR

Course Information Seminar Report papers by yourselves Grading Seminar reports and final report Course homepage and FTP

Objectives Learn something interesting Do something interesting Find some interesting problems Improve your abilities and experiences!

Requirements Reporter Over-prepared: read a series of important papers, PPT (texts and images) Professional: PPT, explaining, interaction … List all references on the last slide His own idea or own work Audience Challenging the reporter Ask questions Learn something new Active and creative!

Q&A