Objectives:

$$ To Determine the codes to be used for transmitting your name using Huffman coding.

Deliverables:

$$ Huffman code of your name, along with answers to the given questions.

Background information : In the field of multimedia content development, understanding the factors that influence the quality of images, sound, and other elements is crucial. One such factor is the efficiency of data compression techniques. Huffman coding is a widely$-$used method for lossless data compression. The idea is to assign variable$-$length codes to input characters, lengths of the assigned codes are based on the frequencies of corresponding characters. The most frequent character gets the smallest code and the least frequent character gets the largest code. The variable$-$length codes assigned to input characters are Prefix Codes, means the codes $($bit sequences$)$ are assigned in such a way that the code assigned to one character is not the prefix of code assigned to any other character. This is how Huffman Coding makes sure that there is no ambiguity when decoding the generated bitstream. $($ Reference : geeksforgeeks.com$)$ Your task is to evaluate how Huffman coding can contribute to enhancing multimedia content quality, particularly focusing on the compression of textual data. Follow the steps below to complete this task:

Your report will be evaluated based on the following points.

$1.$ Executed the given java program and got the output$-$

$2.$ Huffman code of your name is written properly $.$

$3.$ All the given tasks are completed successfully

CLO$3$ marks $(5$ marks$)$

Task $1$

$1.$ Copy the following program and save it as Huffman.py

$2.$ Execute the program$-$ give and check the output

$3.$ Take snapshot of the output along with timestamp.

$4.$ The output shows the codes used for each letter of your name.

University of Fujairah

BIT$-$Networking and Security Program

Task $2$

Answer the following :

$1.$ Determine the maximum length of the code used and for which letter it is used?

$2.$ Determine the letter which gets shortest length code?

Task $3$:

Draw a table as given in the example.

Eg:

MULTIMEDIA

Text: MULTIMEDIA

$--$ intervals $--$

$\text{'}$A$\text{'}$ : $0\mathrm{.}1$

$\text{'}$D$\text{'}$ : $0\mathrm{.}1$

$\text{'}$E$\text{'}$ : $0\mathrm{.}1$

$\text{'}$I$\text{'}$ : $0\mathrm{.}2$

$\text{'}$L$\text{'}$ : $0\mathrm{.}1$

$\text{'}$M$\text{'}$ : $0\mathrm{.}2$

$\text{'}$T$\text{'}$ : $0\mathrm{.}1$

$\text{'}$U$\text{'}$ : $0\mathrm{.}1$

$---$ Printing Codes $---$

$\text{'}$A$\text{'}$ : $101$

$\text{'}$D$\text{'}$ : $1100$

$\text{'}$E$\text{'}$ : $100$

$\text{'}$I$\text{'}$ : $00$

$\text{'}$L$\text{'}$ : $011$

$\text{'}$M$\text{'}$ : $111$

$\text{'}$T$\text{'}$ : $1101$

University of Fujairah

BIT$-$Networking and Security Program

$\text{'}$U$\text{'}$ : $010$

$--$ Encoding$/$Decoding $--$

Encoded Text: $111010011110100111100110000101$

Decoded Text: MULTIMEDIA

Arrange them as given in the following table

LETTER

M

U

L

T

I

M

E

D

I

A

FREQUNCY

$2/10=0\mathrm{.}2$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

$2/10=0\mathrm{.}2$

REPETITION

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

REPETITION

$1/10=$

$0\mathrm{.}1$

CODE USED

$111$

$010$

$011$

$1101$

$00$

$100$

$1100$

$101$

Task $4$:

Arranging the entries in order$-$

Write them without repetition, and in descending order of frequency

LETTER

I

M

E

U

L

A

T

D

FREQUNCY

$2/10=0\mathrm{.}2$

$2/10=0\mathrm{.}2$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

$1/10=$

$0\mathrm{.}1$

CODE USED

$00$

$111$

$100$

$010$

$011$

$101$

$1101$

$1100$

Write your inference from the above table.

University of Fujairah

BIT$-$Networking and Security Program

Huffman.py

from heapq import heappush, heappop, heapify

from collections import defaultdict

class Node:

def $\_\_$init$\_\_($self$,$ char, freq$)$:

self.char $=$ char

self.freq $=$ freq

self.left $=$ None

self.right $=$ None

def $\_\_$lt$\_\_($self$,$ other$)$:

return self.freq $<$ other.freq

def build$\_$huffman$\_$tree$($freq$\_$map$)$:

heap $=[$Node$($char$,$ freq$)$ for char, freq in freq$\_$map.items$()]$

heapify$($heap$)$

while len$($heap$)>1$:

left $=$ heappop$($heap$)$

right $=$ heappop$($heap$)$

merged $=$ Node$($None$,$ left.freq $+$ right.freq$)$

merged.left $=$ left

merged.right $=$ right

heappush$($heap$,$ merged$)$

University of Fujairah

BIT$-$Networking and Security Program

return heap$[0]$

def generate$\_$codes$($root$,$ code$=\text{'}\text{'},$ codes$=\{\})$:

if root is not None:

if root.char is not None:

codes$[$root$.$char$]=$ code

generate$\_$codes$($root$.$left, code $+\text{'}0\text{'},$ codes$)$

generate$\_$codes$($root$.$right, code $+\text{'}1\text{'},$ codes$)$

def huffman$\_$encoding$($text$)$:

freq$\_$map $=$ defaultdict$($int$)$

for char in text:

freq$\_$map$[$char$]+=1$

if len$($freq$\_$map$)==1$:

return $\{\text{'}0\text{'}$: text$\}$

root $=$ build$\_$huffman$\_$tree$($freq$\_$map$)$

codes $=\{\}$

generate$\_$codes$($root$,\text{'}\text{'},$ codes$)$

encoded$\_$text $=\text{'}\text{'}.$join$($codes$[$char$]$ for char in text$)$

return codes, encoded$\_$text

def huffman$\_$decoding$($codes$,$ encoded$\_$text$)$:

decoded$\_$text $=\text{'}\text{'}$

reverse$\_$codes $=\{$v: k for k$,$ v in codes.items$()\}$

University of Fujairah

BIT$-$Networking and Security Program

code $=\text{'}\text{'}$

for bit in encoded$\_$text:

code $+=$ bit

if code in reverse$\_$codes:

decoded$\_$text $+=$ reverse$\_$codes$[$code$]$

code $=\text{'}\text{'}$

return decoded$\_$text

def main$()$:

text $=$ input$("$Enter the text: $")$

codes, encoded$\_$text $=$ huffman$\_$encoding$($text$)$

print$("$Encoded text:", encoded$\_$text$)$

print$("$Frequency count and codes:"$)$

for char, code in codes.items$()$:

print$($f$"\text{'}\{$char$\}\text{'}$: $\{$code$\}")$

decoded$\_$text $=$ huffman$\_$decoding$($codes$,$ encoded$\_$text$)$

print$("$Decoded text:", deco