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Digital Image Compression Using Bit Plane Slicing Method Digital Image Compression Using Bit Plane Slicing Method

Digital Image Compression Using Bit Plane Slicing Method - PowerPoint Presentation

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Uploaded On 2018-03-21

Digital Image Compression Using Bit Plane Slicing Method - PPT Presentation

Póth Miklós Fürstner Igor Subotica Tech Data compression Lossless all original data can be recovered when the file is uncompressed The signal is perfectly reconstructed from the available samples ZIP GIF PNG ID: 659046

planes bit hilbert image bit planes image hilbert data curve signal compression noise scanning original cameraman images effect question

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Presentation Transcript

Slide1

Digital Image Compression Using Bit Plane Slicing Method

Póth Miklós

Fürstner Igor

Subotica TechSlide2

Data compression

Lossless - all original data can be recovered when the file is uncompressed. The signal is perfectly reconstructed from the available samples. (ZIP, GIF, PNG)

Loss

y – reduces a file by eliminating certain information. Permits reconstruction only of an approximation of the original data. (JPEG, MPEG, MP3)

SiP

201

7Slide3

Test images

SiP

2017

Cameraman

Lena

Clock

Einstein

Mandril

MRISlide4

2D-1D transformation

Prior to compression, it is needed to transform the 2D image data to 1D data.

Horizontal, vertical, Hilbert, …Slide5

Image scanning

Horizontal

Perimeter

Hilbert

Z-curve

Zig-zagSlide6

Hilbert curve

Fractal curve, self similar

Hausdorff-Besicovich

dimension 2Capable of collecting all image pixels

Applicable only to

square images

Image side must be

a power of 2Slide7

Hilbert curve scanning

Hilbert curve always takes adjacent pixelSlide8

Hilbert curve scanning

Original image Cameraman

Cameraman after Hilbert scanningSlide9

Differential encoding

Run-length coding Slide10

Bit planesSlide11

Bit planesSlide12

Bit planes

Bit planes of Cameraman image

MSB carries the contours of the image, LSB reminds of noiseSlide13

Bit planes

Question: How many bit-planes can be ignored?

How will it effect the image?Slide14

Bit planes

Question: How many bit-planes can be ignored?

How will it effect the image?Slide15

Bit planes

Question: How many bit-planes can be ignored?

How will it effect the image?Slide16

Bit planesSlide17

Bit planesSlide18

Savings

By ignoring 3 bit planes we save

3/8 = 37.5% of total image space.Slide19

Peak signal to noise ratio - PSNR

ratio

between the maximum possible power of a

signal and the power of corrupting noiseThe signal in this case is the original data, and the noise

is the error introduced by compressionSlide20

Peak signal to noise ratio - PSNR

It has been experimentally discovered that no disturbing visual artifacts are seen if

PSNR>25 dB

Quality is also based on image content, for some images it is 30 dBSlide21

Thank you for your attention.

Questions?