digital image processing ligang liu zhejiang university ligangliu@zju.edu.cn

Digital Image Processing

Ligang LiuZhejiang University

ligangliu@zju.edu.cn

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 hardwa

re 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 netwo

rk 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 sl

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