Multimedia Systems -...

Multimedia Systems

Image I

(Acquisition and Representation)

Mahdi Amiri

April 2012

Sharif University of Technology

Course Presentation

Multimedia Systems, Mahdi Amiri, Image I

Image Representation Color Depth

1bit

2bit

4bit

8bit

24bit

The number of bits used

to represent the color of

a single pixel.

bits per pixel (bpp).

1bit: Monochrome

24bit: Truecolor

Image Representation Indexed Color, Palette

It is a form of vector quantization compression.

A 2-bit indexed

color image

Color table

(the palette)

8-bit (256-color)

Indexed image and

its own palette

8-bit Grayscale

image and palette


Image Representation, Palette Disadvantages

Limited set of simultaneous colors per image.

If the original color palette for a given indexed image is

lost, it can be nearly impossible to restore it.

4-bit 8-bit 24-bit Incorrect

palette


Image Representation Halftone

A technique that simulates continuous tone imagery through the use

of dots, varying either in size, in shape or in spacing.

How the human eye

would see this sort of

arrangement from a

sufficient distance.

Halftone

dots

Three examples of color halftoning with CMYK separations. From left to

right: The cyan separation, the magenta separation, the yellow separation, the

black separation, the combined halftone pattern and finally how the human eye

would observe the combined halftone pattern from a sufficient distance.

Colo

r Halfto

nin

g


Image Representation, Dithering Definition

An intentionally applied form of noise used to randomize

quantization error.

Etymology: …Mechanical computers performed more accurately

when flying on board the aircraft, and less well on ground!

Application: Increasing color depth without adding new bits

1-bit

black and white thresholding

24-bit 1-bit,

with Floyd-Steinberg dithering


Image Representation, Dithering Floyd–Steinberg Algorithm

Distribute the quantization residual to neighboring

pixels that have not yet been processed.

Pseudocode:

for each y from top to bottom

for each x from left to right

oldpixel := pixel[x][y]

newpixel := find_closest_palette_color(oldpixel)

pixel[x][y] := newpixel

quant_error := oldpixel – newpixel

pixel[x+1][y] := pixel[x+1][y] + 7/16 * quant_error

pixel[x-1][y+1] := pixel[x-1][y+1] + 3/16 * quant_error

pixel[x][y+1] := pixel[x][y+1] + 5/16 * quant_error

pixel[x+1][y+1] := pixel[x+1][y+1] + 1/16 * quant_error

Distribution matrix


Image Representation, Dithering Color Banding Artifact

Dithering prevents large-scale patterns such as "banding" in images.

Web-safe color palette

with no dithering

Web-safe color palette

with Floyd–Steinberg

dithering


Image Resolution Image Resolution

Image Resolution, Most Common Display Resolutions

Asp

ect Ratio


New iPad: 2048× 1536 (QXGA)

Image Resolution Megapixel (MP)

One million pixels

To express:

The number of pixels in an image

The number of image sensor elements of digital cameras

The number of display elements of digital displays

2048×1536 sensor elements, or QXGA display

3.1 MP (2048 × 1536 = 3,145,728)

8 MP Phone

Camera

160 MP

Camera


Image Resolution Pixels per inch (ppi)

Pixels per inch (PPI) or pixel density is a measurement of the

resolution of devices in various contexts; typically computer displays,

image scanners, and digital camera image sensors.

18 ppi


72 ppi 150 ppi

Image Resolution Pixels per inch (ppi)

The average human eye can only detect 300 ppi.

iPhone 4, 4s

3.5"

640x960

326 ppi


iPad, iPad2

9.7"

1024x768

132 ppi

List of displays by pixel density

http://en.wikipedia.org/wiki/List_of_displays_by_pixel_density

Nokia N95

2.6"

240x320

153 ppi

Google Nexus One

3.7"

480x800

254 ppi

New iPad

9.7"

2048x1536

264 ppi

Nokia Lumia 800

3.7"

800x480

252 ppi

Samsung I9100 Galaxy S II

4.27"

480x800

219 ppi

Image Vision Histogram


Plots the number of pixels for each tonal value. By looking at the histogram for a specific

image a viewer will be able to judge the entire tonal distribution at a glance.

Intensity (tonal value)

Count (Number of

pixels for each

different intensity

value)

Image

histogram

Image Vision Contrast


Typ. histogram of

a low contrast image

Typ. histogram of

a high contrast image

Contrast is the difference in visual properties that

makes an object distinguishable from other objects

and the background.

Formula

Image Vision Histogram Equalization


Histogram equalization is a method in image processing of

contrast adjustment using the image's histogram.

Image Vision


Histogram equalization, Example

Image File Formats Raster and Vector Graphics

Raster Graphics (Bitmap)

.BMP, .JPG, .PNG, .GIF

Vector Graphics

.CGM, .SVG Both

.AI, .CDR, .PSD, .TIFF


Image Representation Panorama

Stitching images captured

above Milad Tower

Example Software:

“Hugin” and “AutoStitch”


Image Representation AutoStitch Process

Example algorithm: SIFT Keypoint detection and matching


Image Representation Large Screen Projection


Image Acquisition High-Dynamic-Range (HDR)

HDR, Accurately

representing the range

of intensity levels

found in real scenes

4 Images captured with

different Exposure

Values (EV or stop)


Image Acquisition HDR Movie Demo

Play HDR movie demo


Image Acquisition, HDR Algorithm: Tone Mapping

To overcome the limited dynamic

range of current standard digital

imaging techniques

Tone mapped HDR image

A simple version of tone mapping:

Mean Value Mapping

This is

Exposure Bracketing


Image Acquisition Focus Bracketing

Focus stacked image

A sequence of 5 incrementally focused images

Example Software:

“CombineZP”


Bracketing is the general technique of taking several shots of the same subject using different camera settings.

Image Acquisition Focus Bracketing

The resulting focus stacked image with an

extended depth of field

The three source image

slices at three focal depths

Contributions in the final

"focus stacked" image

Example Application:

Microscopy


Thank You

1. http://ce.sharif.edu/~m_amiri/

2. http://www.dml.ir/

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