Lecture 10: Modifying Images - University of...

Lecture 10: Modifying Images

The Digital World of MultimediaProf. Mari Ostendorf

EE299 Lecture 1030 Jan 2008

AnnouncementsHW3 due Friday in classGuest lecture Friday Feb 1 (EEB 403)

A cultural history of JPEG… Dr. Joan MitchellAnother lecture by Dr. Mitchell on Thurs

Patenting a wet suit… Thurs 1/31 10:30 EEB 125Lab3: Read the lab *before* lab


Goals for TodayReview of frequency content of imagesSampling and aliasing for imagesAnalogies in sound vs. image processingImage filtering


Simple Cosines in Space


2D Frequency Content of Images

DCT = Discrete Cosine Transform


Display Artifacts of the DCT (and DFT)

F=100300ppi

F=160480ppi

F=200600ppi


Aliasing for Images

F=50 for cosine, 300ppi original


Aliasing for Images (cont)Highest frequencies in center aliasingRegion of aliasing grows with downsampling

This is aliasing, not zooming in.


Another Aliasing Example

For more interesting examples, see Orsak et al. pp. 133-134


Sound vs. Image SP AnalogiesSound

Time-scalingAmplitude scaling: change loudnessEchoTime reverseFilter:

LPF: smoothing, sounds more muffledHPF: detect onsets, sounds more tinny

ImageExpand/shrink imageAmplitude scaling: change brightnessDouble exposureImage flipFilter

LPF: blurring, speckle removalHPF: deblurring, edge detection


Resizing ImagesShrinking:

Grayscale: replace KxK block with single pixel with average gray level of the K2 pixels in the originalColor: Repeat for each color plane

Enlarging:Grayscale: insert interpolated pixel valuesColor: repeat for each color plane, as in shrinking


+90

-90

Amplitude Scaling for Images


Review: Grayscale vs. ColorGray: MxN matrix Color: MxNx3

B/W intensity:• 0 = black• 1 = white

X(i,j)=0.4

X(i,j,2)=0.6 X(i,j,3)=1.0

R/G/B intensity:• [0,1]=[none, full]• (0,0,0)=black• (1,1,1)=white

X(i,j,1)=0.75

8 bits/pixel 256 gray levels

8 bits/color-pixel 2563 colors,

24 bits/pixel


Color Digital ImagesComponent colors


Adjusting Amplitude in Color Images

par=min(255,par+100);

par(:,:,2)=min(255,par(:,:,2)+100);

More of all colors more white

More green


Changing Color Images (cont.)

Turning off a color:X(:,:,1)=0;


Swapping Color Planes

Swap:G RB GR B

original


Reminder of Time Signal Filtering

original

low pass filtered(15 sample average)

high pass filtered(avg of 5 samples – avg of next 5 samples)


Image Filtering

original

2D low pass filtered(average over 15x15 block) 2D high pass filtered1D high pass filtered

Using the same filters as in the previous slide, but in 2D, e.g.

filt2d=filt*filt’


More Filtering Examples

original 2D low pass filtered 2D high pass filtered


Another Example

filteredoriginal

What type of filter was used?


Modifying Color Images

original

Blur only the green plane

Blur everything

Each color plane can be manipulated as a grayscale image, e.g. filtered, contrast enhanced, etc.


NEW TOPIC: COMPRESSIONWhat is compression?

Representing an signal (sound file, image or video) with fewer total bits

Why bother?Storage: You can fit more songs & videos on your IPODCommunication: It takes less time to download stuff; real-time video conferencing


Types of CompressionLossless

Represent the sound/image/video with fewer bits without changing the signal *at all* (you can perfectly reconstruct the original)How? (like the 20 questions game)

Map the different levels to a variable-length code, using short codes for more frequent things

LossyRepresent the sound/image/video with fewer bits with some changes from the originalHow?

Throw out the stuff that people don’t pay attention to

Lecture 10: Modifying Images - University of...

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