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Lossless compression methods Mohammed Chassab Mahdi

Assist .Lecturer-Institute of Technical /Kufa

Abstract

the aim of research is to find compression methods which are more appropriate to

compress files with different extensions, and what the effect of changing the size of the

file on the compression ratio .

In this research have been selected eight most common of file extensions and for each

one of these extensions have been selected ten different size files as a samples to

compress by using three lossless compression methods(RLE, Huffman ,LZW ) have

also been discussed the response of each extension to the three methods. All programs

have been written using visual basic language

المستخلص ة لضغط الملفات مالءم األكثرالضغط طرق إيجاد إلىالبحث يهدفً ددادات ذات اال فة ،الم هدف ماكمخدل لىي سة إ جم درا ير ح دأثير دغ

Compression Ratio .ضغطالنسبة علىملف ال

طاارق الضااغط بااد اادا ماا ثالثااة يدنااا ه اااذا البحااثLossless compression methods اي طري ة (RLE ,Huffman ,LZW)يسادخدمها

فات ذا ضغط مل اي ل فه ددادات مخدل ية ام ثرت ثمان كه األك شي عا لكما دمت مناقشة اسدجابة مخدلفة بإحجامامدداد دم ضغط عشرة ملفات اه كه البرامج كدبت بلغة الفج . الثالثةكه امدداد للضغط بالطرق

بيسيك.

1-Introduction

Data compression is a general term used to describe the process of recoding data

so that it requires fewer bytes of storage space .Two very important terms used in all

however are lossless compression and lossy compression [6].

Lossless data is the ability to shrink a file then reconstitute it to its original form. Lossy

compression however, is the ability to eliminate some data during the process (rather

than shrink) then reconstitute it. These terms are vital in understanding the differences

between the different types.

There are many different kinds of ways to perform data compression. Each one is

used differently and has its intended purpose.

The first kind of compression is dictionary-based compression. In this type

compression replaces characters with one individual codeword. This codeword is then

directed to a dictionary that is able to find the original structure of the word. It shortens

words, sentences, or paragraphs so that the entirety of each do not have to be

transported.

Another type of compression is statistical compression. During this process the

frequencies of characters are manipulated in order to perform the necessary task.

Characters that are repeated throughout the file are given bit patterns. In this process

letters or individual characters that are repeated many times throughout a piece are

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recoded. This type of compression makes it possible for a file to be very small during

transportation then in full text when it is recoded at the end [1,8].

Additionally there is spatial compression . In this file the redundant data

contained in a file is taken advantage. Data that is constantly repeated within a file is

replaced with a message that can accurately describe its contents. This is often used in

the compression of image files. For example, run-length encoding is commonly used to

compress redundant color pixels.

Finally, but no less important there is temporal compression. This is most

commonly used in the compression of video or audio files. This process excludes

redundant information in video and audio samples. It stores only the information

necessary and eliminates all other “useless” information. During cuts, wipes, dissolves,

and transitions the only thing transferred is the “key frame.” The key frame is the

information common in all the original data. That way unnecessary information does

not have to be transferred in all the transfers [5].

1-1-The Need For Compression

In the past, storing documents were stored on paper and kept in filing cabinets

have been very inefficient in terms of storage space and also the time taken to locate and

retrieve information when required. This traditional method of storing documents is

now being replaced by storing and accessing documents electronically through

computers.

This has enabled us to manage things more efficiently and effectively, so that

items can be located and information extracted without undue expense or inconvenience.

In terms of storage, the capacity of a storage device can be effectively increased with a

method that compresses a body of data on its way to a storage device and decompresses

it when it is retrieved [4].

In terms of communications, the bandwidth of a digital communication link can be

effectively increased by compressing data at the sending end and decompressing data at

the receiving end [7].

At any given time, the ability of the Internet to transfer data is fixed. Thus, if data

can effectively be compressed wherever possible, significant improvements of data

throughput can be achieved. Many files can be combined into one compressed document

making sending easier. In computer graphics, we are interested in reducing the size of a

block of graphics data so we can fit more information in a given physical storage space.

1-2-Data compression classification

Data compression can be divided into two main types [2,10]:

A-Lossless data compression:-

The data which have been compressed by the lossless compression methods can

be returned to the original form exactly. Lossless compression methods used for task

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data such as texts, some kinds of pictures, signals from earthquakes and volcanoes, and

medical tomography images.

B-Lossy data compression:-

Lossy compression methods cause the loss of some information (non-task),

which normally can not be retrieved or restructure but it can get higher compression

ratio than those we get using lossless compression methods[9]. In many applications, the

shortfall when restructuring unimportant, for example when storing a talk, the exact

value of each sample of the talk is not necessary[3].

2-System design

Three algorithms (RLE , Huffman , LZW) has been used to write three

programs using visual basic language and then develop a system includes three

programs. This system can be load the different files in order to compression by one of

each method (Huffman ,LZW , RLE) and then saved.

Also it can be load the compression files in order to decompression and then saved . The

system also allow to present file content before and after compression or decompression

2-1Selected file extensions

In this research have been selected eight file extensions which is common used .

These selected file extensions listed below :-

1- txt. (Text file)

2- doc. (Text file)

3- bmp. (Image file)

4- jpg. (Image file)

5- mp3. (Audio file)

6- mpeg. (Video file)

7- ppt . ( Data file)

8-html. (Web file)

2-2Experimental results

For each file extension have been selected ten different size files and compressed

these files by using three methods (Huffman, LZW, RLE) and have been calculated the

compression ratio .Compression ratio is the ratio of the size of the original data to the

size of the compressed data.

Compression Ratio (CR) =size of original file / size of compressed file.

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Results of compression using three methods for each ten files from the same

extension has been put in the table also contains the compression ratios calculated.

The scheme was designed to clarify the relationship between file size and the

compression ratio for each compression method.

Table(1) txt files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffman

1.0024 1.9594 1.564586 46076 23571 29519 46185 Txt1

1.0114 1.97607 1.524984 103050 52742 68343 104222 Txt2

0.9999 2.10342 1.610484 167544 79646 104024 167529 Txt3

0.9999 2.06291 1.62187 207899 100774 128178 207888 Txt4

1.0002 2.12644 1.621255 255069 119977 157362 255124 Txt5

1.0002 2.05488 1.620862 315180 153414 194494 315248 Txt6

1.0002 2.06669 1.623715 382058 184893 235335 382117 Txt7

1.0002 2.09032 1.615578 412503 197374 255373 412575 Txt8

1.0007 1.84023 1.482511 471943 256626 318548 472251 Txt9

1.0054 2.45268 1.608797 519803 213070 324834 522592 Txt10

Fig(1) txt files curves

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Table(2) doc files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffman

1.6019 1.47488 1.603497 30683 33326 30653 49152 Doc1

1.3912 2.45552 1.800769 94586 53587 73071 131584 Doc2

1.4071 2.70128 1.891521 138268 72025 102859 194560 Doc3

1.472 2.27969 1.94604 188746 121876 142772 277840 Doc4

1.3921 2.22338 1.725003 276393 173053 223050 384762 Doc5

1.2798 2.22409 1.616443 363667 209258 287921 465408 Doc6

1.2683 2.31147 1.630573 450120 246981 350115 570888 Doc7

1.25 2.32253 1.57236 560726 301795 445781 700928 Doc8

1.2399 2.20516 1.565969 621477 349435 492066 770560 Doc9

1.2417 2.255 1.572892 699729 385305 552399 868864 Doc10

Fig(2) doc files curves

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Table(3) bmp files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffman

1.00008 0.97229 1.183345 36915 37970 31198 36918 Bmp1

0.99981 0.94307 1.033767 102794 108978 99417 102774 Bmp2

1.01933 1.68259 1.04319 244393 148056 238804 249118 Bmp3

0.99996 0.91756 1.017805 332996 362901 327157 332982 Bmp4

0.99971 1.12376 1.111846 411372 365964 369884 411254 Bmp5

1.07708 1.03523 1.051168 512801 533535 525444 552330 Bmp6

1.00024 1.32035 1.374772 677888 513540 493212 678054 Bmp7

1.0012 1.86793 1.14966 714914 383189 622593 715770 Bmp8

1.01838 1.25657 1.046276 831488 673875 809322 846774 Bmp9

1.03518 2.00549 1.295362 890334 459566 711503 921654 Bmp10

Fig(3) bmp files curves

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Table(4) jpg files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffman

1.00839 0.71413 0.9853 12629 17833 12925 12735 Jpg1

1.00072 0.65822 0.993771 104590 159012 105321 104665 Jpg2

1.00045 0.68117 1.001412 226802 333108 226584 226904 Jpg3

1.08069 0.66781 1.00061 308195 498742 332860 333063 Jpg4

1.00006 0.65719 0.999104 473850 721065 474303 473878 Jpg5

1.00011 0.66605 1.002589 555678 834383 554302 555737 Jpg6

1.0178 0.66387 0.999898 609447 934364 620356 620293 Jpg7

1.00003 0.69727 1.015257 716434 1027511 705690 716457 Jpg8

1.00548 0.65252 1.000228 830602 1279887 834960 835150 Jpg9

1.00485 0.65527 1.000065 935151 1434038 939625 939686 Jpg10

Fig(4) jpg files curves

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Table(5) mp3 files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffma

n

1.00825 0.66628 0.99493 53701 81263 54420 54144 Mp3 1

1.03652 0.67626 1.0343 112746 172809 112989 116864 Mp3 2

1.02023 0.66857 1.02073 208392 318003 208291 212608 Mp3 3

1.01351 0.65739 1.01295 304243 469056 304409 308352 Mp3 4

1.03571 0.67684 1.01704 405982 621242 413434 420480 Mp3 5

1.01292 0.66722 1.01529 510143 774465 508955 516736 Mp3 6

1.00708 0.65758 1.00849 624441 956337 623568 628864 Mp3 7

1.02169 0.67005 0.96506 709727 1082195 751373 725120 Mp3 8

1.06563 0.69517 1.02249 817498 1253151 851987 871152 Mp3 9

1.00645 0.66662 1.01212 927016 1399593 921817 932992 Mp3 10

Fig(5) mp3 files curves

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Table(6) mpeg files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffm

an

1.22377 0.85374 1.08046 18412 26392 20854 22532 Mpeg1

1.04126 0.71247 1.01493 118015 172477 121076 122884 Mpeg2

1.02509 0.70395 1.01236 197793 288026 200280 202756 Mpeg3

1.01728 0.71252 1.02234 348288 497258 346567 354308 Mpeg4

1.00961 0.70198 1.0177 411791 592253 408516 415748 Mpeg5

1.00792 0.69263 1.01293 627861 913670 624759 632836 Mpeg6

1.00794 0.69257 1.01301 692824 1008310 689356 698327 Mpeg7

1.00977 0.69393 1.01354 720008 1047717 717329 727044 Mpeg8

1.00859 0.69307 1.01343 800043 1164261 796224 806916 Mpeg9

1.00788 0.69618 1.01519 910334 1317925 903776 917508 Mpeg10

Fig(6) mpeg files curves

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Table(7) ppt files results

Compression ratio

Size of files after compression (Bytes)

Size of original

Files

File Name

RLE LZW Huffman RLE LZW Huffman

1.40637 2.19636 1.977122 19295 12355 13725 27136 Ppt1

1.32314 1.41355 1.552881 47983 44914 40884 63488 Ppt2

1.32715 1.42735 1.343308 93361 86807 92238 123904 Ppt3

1.13517 1.24904 1.31108 166432 151258 144101 188928 Ppt4

1.12393 1.42655 1.121005 257839 203142 258511 289792 Ppt5

1.05784 0.8734 1.083528 335900 406832 327936 355328 Ppt6

1.04319 0.83137 1.060261 430925 540715 423986 449536 Ppt7

1.08336 0.98012 1.148319 516556 570969 487335 559616 Ppt8

1.06075 1.07727 1.207403 583076 574135 512253 618496 Ppt9

1.04702 0.82773 1.069384 676296 855469 662153 708096 Ppt10

Fig(7) ppt files curves

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Table(8) html files results

Compression ratio

Size of files after compression (Bytes)

Size of original

files

File Name

RLE LZW Huffman RLE LZW Huffman

1.05545 0.9064 1.115152 523 609 495 552 html1

1.01027 1.53753 1.400998 9448 6208 6813 9545 html2

1.13826 2.68568 1.527689 26393 11186 19665 30042 html3

1.00078 2.30099 1.420273 52279 22738 36838 52320 html4

1.04082 2.23278 1.471803 70260 32752 49686 73128 html5

1.02106 1.95386 1.361606 94897 49592 71163 96896 html6

1.0641 2.08627 1.421844 112111 57182 83903 119297 html7

1.00144 2.3192 1.317899 144182 62258 109560 144389 html8

1.00855 1.87637 1.336452 170530 91660 128690 171988 html9

0.99998 3.63339 1.476389 193630 53291 131149 193627 html10

Fig(8) html files curves

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Table(9)

The best compression method for each extension of files

web files

data files

video files

audio files

files image files text

html ppt mpeg mp3 jpg bmp doc txt type of files

LZW Huffma

n RLE RLE RLE LZW LZW LZW

best compressio

n method

Table(10)

Total sizes of files

total size of all original

files (Bytes)

total size of all compression files(Bytes)

total size of all files

compression by the best

method(Bytes)

total size of all files

compression by WinRAR

(Bytes) Huffman LZW RLE

30840347 27319941 31994898 29820060 24019640 18806048

Results discussion

1- Compression results of the text files for the type (txt)and (doc) showed that these files

responded to the compression by LZW method more than the other methods.

2- When RLE compression method is used the compression ratio of the image files of

type (bmp) equal to one. It means that above files neither responds to the

compression nor bigger size at the same time. These files responded slightly to the

compression using Huffman method while, the compression ratio to LZW method is

the biggest, but this ratio varied greatly.

3- The image files of type (jpg) maintained on their sizes using Huffman method, That

means the sizes of these files did not increase or decrease When LZW method is

used, the compression ratio is less than one this means that the sizes of these files

were increased .These files slightly responded to compression using RLE method.

4- The audio files of type (mp3) maintained their sizes when Huffman and RLE methods

were used, but the sizes of these files increased when LZW method was used. This

means that these files do not respond to all lossless compression methods.

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5- The video Files of type (mpeg) responded slightly to the compression when Huffman

and RLE methods were used while sizes increased when these files compressed by

LZW method.

6- The data files of type (ppt) responded to all compression methods, but these files have

responded more to compression when Huffman method was used.

7- The web files of type (html ) responded more to the compression by using the method

of LZW, but they responded less by using the Huffman method , while, maintained

their sizes using RLE method .

8- The web files html 3 and html 10 responded to compression by using LZW method

more than the rest of the files of the same extension because these files contain texts

more than pictures .

9- The image files Bmp 3, Bmp8 and Bmp10 responded to the compression by using

LZW method more than the rest of files of the same extension because of contain

these images on large similar tracts .

3-Conclusions

It could be concluded from the results that :-

1- The change in file size does not affect the compression ratio when using all methods

which were studied. 2- Results showed that LZW was the best method to compress the files with the

extensions of ( txt.doc.bmp.html) while, RLE was the best method to compress the

files with the extensions of (jpg.mp3.mpeg). Huffman was the best method to

compress files with the extension(ppt).

3-Possible future work to complete the program , which was practically implemented in

this research so as to adopt practical results recommended in the table (9) where the

program will choose the best compression method depending on the file extension

required to compress .

4-It is possible in the future to change in the program, which was implemented in this

research to compress file using three methods at the same time, and then compared

sizes of files resulted from the compression of these methods in the selection of the

smallest and adopt it as a result of the compression

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