Enhancing Efficiency of Huffman Coding

8/9/2019 Enhancing Efficiency of Huffman Coding

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Enhancing Efciency o HumanCoding Using Lempel Ziv Coding orImage Compression


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Contents Image compression

Flow o compression

ypes o image compression

HL !chemeHL Coding " !tage #

HL Coding " !tage $

HL %ecoding

Comparison

Conclusion

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Image Compression

%igital images re(uire huge amounts o space or

storage and large )andwidths or transmission*

◦ + ,-. / -0. color image re(uires close to #12 o

space*

he goal o image compression is to reduce the

num)er o )its re(uired to store and transmit a

digital image*

◦ 3educe storage re(uirements and increase

transmission rates*

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Flow o compression

• he image 5le is converted into a series o

)inary data6 which is called the )it7stream

• he decoder receives the encoded )it7stream

and decodes it to reconstruct the image

• he total data (uantity o the )it7stream is

less than the total data (uantity o the original$#' -


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ypes o imagecompression

Image compression

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Lossless Compression

he original image can )e perectly recovered

orm the compressed image

8oiseless 7 they do not add noise to the signal

9image:

+lso called entropy coding 7 decomposition

techni(ues to eliminate&minimi;e redundancy

Used only or a ew applications with stringent

re(uirements such as medical imaging

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HL !CHE1E

a ast lossless image compression schemes

consists o $ stages>

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!tage # > Human CodingExample :

%ata > ?#44=#'-'#''#4'=.,4-= @

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Symbols Probability

. .*.'

# .*$

$ .

4 .*$

- .*#

' .*$'

, .*.'

= .*#'


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contd****

Symbols Hufman Codewords

# ..

4 .#

' #.

= ##.

$ ###...

. ###..#

, ###.#

- ####

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contd***

$#' ##

Code tree


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!tage $ > LZ< Coding

Butput o stage # Input to stage $ >

Encoded data 9using Human Coding: >

..6.#6.#6##.6..6#.6####6#.6..6#.6#.6..6.#6

#.6##.6###..#6###.#6.#6####6##.

Concatenate all the Human code words

apply LZ< algorithm

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contd***

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LZ< %ictionary


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!tage # > LZ< %ecoding3ead a value rom the encoded input and

output the corresponding string rom the

initiali;ed dictionary*

+t the same time6 o)tain the ne/t value romthe input6 add to the dictionary the

concatenation o the string Dust output and the

5rst character o the string o)tained )y

decoding the ne/t input value*

he decoder then proceeds to the ne/t input

value which was alread read in as the ne/t$#' #'

!t $ H


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!tage $ > Human%ecoding he result o the #st stage is the concatenated

Human code words >

...#.###...#.#####...#.#....##.##.###

..####.#.#######.

+ter the code has )een created6 coding and&or

decoding is accomplished in a simple loo7up

ta)le manner*

+ter decoding the a)ove Human codeword

)y using the Human tree we get the original

message i*e* ?#44=#'-'#''#4'=.,4-=@

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Comparison )etween HumanCoding HL Coding

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Conclusion+ new compression and decompression

techni(ue called as HL !cheme )ased on

Human coding and Lempel Ziv coding is very

efcient techni(ue or compressing the image

to a great e/tent*

his techni(ue is simple in implementation and

utili;es less memory*

he advantage )ecome most apparent or

images with more si;e*

Future wors may )e on improving the$#' #0


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3eerences >

?Enhancing Efciency o Human Coding using

Lempel Ziv Coding or Image Compression@6 C*

!aravanan6 1* !urender6 International Gournal o

!ot Computing and Engineering 9IG!CE: I!!8> $$4#7

$4.=6 olume7$6 Issue7,6 Ganuary $.#4

? A study o various image compression techniues@6

!onal6 %inesh umar6 %epartment o Computer

!cience Engineering Juru Gham)heswar

University o !cience and echnology6 Hisar

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Enhancing Efficiency of Huffman Coding

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