Multimedia SystemsMultimedia Systems
Image IImage I
(Acquisition and Representation)(Acquisition and Representation)
Course PresentationCourse Presentation
(Acquisition and Representation)(Acquisition and Representation)
Mahdi Amiri
March 2014
Sharif University of Technology
Image RepresentationColor DepthColor Depth
2bit2bit 8bit8bitThe number of bits used The number of bits used
to represent the color of to represent the color of
a single pixel.a single pixel.
bits per pixel (bits per pixel (bppbpp).).
1bit: Monochrome1bit: Monochrome
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1bit1bit 4bit4bit 24bit24bit
1bit: Monochrome1bit: Monochrome
24bit: 24bit: TruecolorTruecolor
Image RepresentationIndexed Color, PaletteIndexed Color, Palette
It is a form of vector quantization compression.
A 2A 2--bit indexed bit indexed
color image color image
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Color tableColor table
(the palette)(the palette)
88--bit (256bit (256--color) color)
Indexed image and Indexed image and
its own paletteits own palette
88--bit Grayscale bit Grayscale
image and paletteimage and palette
Multimedia Systems, Mahdi Amiri, Image I
Image Representation, PaletteDisadvantagesDisadvantages
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.
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44--bitbit88--bitbit2424--bitbit Incorrect Incorrect
palettepalette
Multimedia Systems, Mahdi Amiri, Image I
Image RepresentationHalftoneHalftone
A technique that simulates continuous tone imagery through the use
of dots, varying either in size, in shape or in spacing.
Color
Color
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How the human eye How the human eye
would see this sort of would see this sort of
arrangement from a arrangement from a
sufficient sufficient distancedistance..
Halftone Halftone
dotsdots
Three examples of Three examples of color color halftoninghalftoning with CMYK separations. From left to with CMYK separations. From left to
right: The cyan separation, the magenta separation, the yellow separation, the right: The cyan separation, the magenta separation, the yellow separation, the
black separation, the combined halftone pattern and finally how the human eye black separation, the combined halftone pattern and finally how the human eye
would observe the combined halftone pattern from a sufficient distance.would observe the combined halftone pattern from a sufficient distance.
Color
Color H
alftoning
Halfto
ning
Multimedia Systems, Mahdi Amiri, Image I
Image Representation, DitheringDefinitionDefinition
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
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Application: Increasing color depth without adding new bits
11--bitbit
black and white black and white thresholdingthresholding
2424--bitbit 11--bit,bit,
with Floydwith Floyd--Steinberg ditheringSteinberg dithering
Multimedia Systems, Mahdi Amiri, Image I
Image Representation, DitheringFloydFloyd––Steinberg AlgorithmSteinberg Algorithm
Distribute the quantization residual to neighboring
pixels that have not yet been processed.
Pseudocode:
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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 matrixDistribution matrix
Multimedia Systems, Mahdi Amiri, Image I
Image Representation, DitheringColor Banding ArtifactColor Banding Artifact
Dithering prevents large-scale patterns such as "banding" in images.
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WebWeb--safe color palette safe color palette
with no ditheringwith no dithering
WebWeb--safe color palette safe color palette
with Floydwith Floyd––Steinberg Steinberg
ditheringdithering
Multimedia Systems, Mahdi Amiri, Image I
Image ResolutionImage ResolutionImage Resolution
Image Resolution, Most Common Display ResolutionsImage Resolution, Most Common Display Resolutions
HD
Full-HD
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Aspect R
atioAspect R
atio
Multimedia Systems, Mahdi Amiri, Image I
3rd gen. of
iPad (QXGA)Google's Nexus 10
(WQXGA)
Image ResolutionDigital TV ResolutionsDigital TV Resolutions
The term 4K refers to the
horizontal resolution of these
formats, which are all on the
order of 4,000 pixels.
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en.wikipedia.org/wiki/4K_resolution
4K Ultra high definition television (UHD)
is a resolution of 3840 pixels × 2160 pixels
(8.3 megapixels, aspect ratio 16:9).
8K UHD which is 7680 pixels × 4320
pixels (33.2 megapixels).
16:9 resolutions in comparison.
Image ResolutionUHDTV, HDTD, SDTVUHDTV, HDTD, SDTV
SDTV: Standard-definition television.
HDTV: high-definition television.
UHDTV: Ultra HDTV.
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http://en.wikipedia.org/wiki/Ultra_high_definition_television
Chart showing resolutions for 8K UHDTV, 4K
UHDTV, 1080p HDTV, and 480i SDTV.
Diagram of the CIE 1931 color space that shows the Rec. 2020
(UHDTV) color space in the outer triangle and Rec. 709 (HDTV)
color space in the inner triangle. Both Rec. 2020 and Rec. 709 use
Illuminant D65 for the white point.
Image ResolutionMegapixel (MP)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
8 MP Phone 8 MP Phone
CameraCamera
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The number of display elements of digital displays
2048×1536 sensor elements, or QXGA display
���� 3.1 MP (2048 × 1536 = 3,145,728)
160 MP 160 MP
CameraCamera
Multimedia Systems, Mahdi Amiri, Image I
Image ResolutionPixels per inch (Pixels per inch (ppippi))
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.
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18 18 ppippi
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72 72 ppippi 150 150 ppippi
Image ResolutionPixels per inch (Pixels per inch (ppippi))
The average human eye can only detect 300 ppi.
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iPhone 5/5s
4"
1136x640
326 ppi
Multimedia Systems, Mahdi Amiri, Image I
List of displays by pixel density
http://en.wikipedia.org/wiki/List_of_displays_by_pixel_density
HTC One
4.7"
1920x1080
468 ppi
Galaxy Note 3
5.7"
1080x1920
388 ppi
iPad 4/Air
9.7"
2048x1536
264 ppi
Lumia 920
4.5"
1280x768
332 ppi
Xperia Z
5"
1920x1080
443 ppi
Image ResolutionPixels per inch (Pixels per inch (ppippi))
Pixels per inch for a
few more devices.
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iPhone 4, 4s
3.5"
640x960
326 ppi
Multimedia Systems, Mahdi Amiri, Image I
iPad 1, iPad 2
9.7"
1024x768
132 ppi
Nokia N95
2.6"
240x320
153 ppi
Google Nexus One
3.7"
480x800
254 ppi
iPad 3
9.7"
2048x1536
264 ppi
Nokia Lumia 800
3.7"
800x480
252 ppi
Samsung I9100 Galaxy S II
4.27"
480x800
219 ppi
Galaxy Note II
5.55"
720x1280
267 ppi
Image VisionHistogramHistogram
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.
Count (Number of
pixels for each
different intensity
value)
Image
histogram
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Intensity (tonal value)
Image VisionContrastContrast
Contrast is the difference in visual properties that Contrast is the difference in visual properties that
makes an object distinguishable from other objects makes an object distinguishable from other objects
and the background.and the background.
FormulaFormula
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Typ. histogram ofTyp. histogram of
a low contrast imagea low contrast image
Typ. histogram ofTyp. histogram of
a high contrast imagea high contrast image
Image VisionHistogram EqualizationHistogram Equalization
Histogram equalization is a method in image processing of Histogram equalization is a method in image processing of
contrast adjustment using the image's histogram.contrast adjustment using the image's histogram.
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Image Vision Histogram equalization, ExampleHistogram equalization, Example
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Image File FormatsRaster and Vector GraphicsRaster and Vector Graphics
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Raster Graphics (Bitmap)Raster Graphics (Bitmap)
.BMP, .JPG, .PNG, .GIF.BMP, .JPG, .PNG, .GIF
Vector GraphicsVector Graphics
.CGM, .SVG.CGM, .SVGBothBoth
.AI, .CDR, .PSD, .TIFF.AI, .CDR, .PSD, .TIFF
Multimedia Systems, Mahdi Amiri, Image I
Image RepresentationPanoramaPanorama
Example Software:Example Software:
““HuginHugin” and “” and “AutoStitchAutoStitch””
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Stitching images captured Stitching images captured
above above MiladMilad TowerTower
Multimedia Systems, Mahdi Amiri, Image I
Image RepresentationAutoStitchAutoStitch ProcessProcess
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Example algorithm: SIFT Example algorithm: SIFT KeypointKeypoint detection and matching.detection and matching.
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Image RepresentationLarge Screen ProjectionLarge Screen Projection
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Image AcquisitionHighHigh--DynamicDynamic--Range (HDR)Range (HDR)
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HDR, Accurately HDR, Accurately
representing the range representing the range
of intensity levels of intensity levels
found in real scenesfound in real scenes
4 Images captured with 4 Images captured with
different Exposure different Exposure
Values (EV or stop)Values (EV or stop)
Multimedia Systems, Mahdi Amiri, Image I
Image AcquisitionHDR Movie DemoHDR Movie Demo
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Play HDR movie demoPlay HDR movie demo
Multimedia Systems, Mahdi Amiri, Image I
Image Acquisition, HDRAlgorithm: Tone MappingAlgorithm: Tone Mapping
Tone mapped HDR imageTone mapped HDR image
This isThis is
Exposure BracketingExposure Bracketing
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To overcome the limited dynamic To overcome the limited dynamic
range of current standard digital range of current standard digital
imaging techniquesimaging techniques
A simple version of tone mapping: A simple version of tone mapping:
Mean Value MappingMean Value Mapping
Multimedia Systems, Mahdi Amiri, Image I
Image AcquisitionFocus BracketingFocus Bracketing
Bracketing is the general technique of taking several shots of the same subject using different camera settings.
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Focus stacked image Focus stacked image
A sequence of 5 incrementally focused imagesA sequence of 5 incrementally focused images
Example Software: Example Software:
““CombineZPCombineZP””
Multimedia Systems, Mahdi Amiri, Image I
Image AcquisitionFocus BracketingFocus Bracketing
Example Application:Example Application:
MicroscopyMicroscopy
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The resulting focus stacked image with an The resulting focus stacked image with an
extended depth of fieldextended depth of field
The three source image The three source image
slices at three focal depthsslices at three focal depths
Contributions in the final Contributions in the final
"focus stacked" image"focus stacked" image
Multimedia Systems, Mahdi Amiri, Image I
Thank You
Multimedia SystemsMultimedia Systems
Image IImage I
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Thank You
1. http://ce.sharif.edu/~m_amiri/
2. http://www.dml.ir/
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