seminarDataCompression.ppt

8/14/2019 seminarDataCompression.ppt

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DATA COMPRESSION

$ITS TECHNIQUES

Presented By:

Gursheen Kaur Kohli

Roll No.- 133517

M.Tech CSE


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DATA COMPRESSION

The process of reducing the volume ofdata by applying a compression technique iscalled compression.The resulting data is

called compressed data. The reverse process of reproducing the

original data from compressed data is called

decompression.The resulting data is calleddecompressed data.


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REASONS TO COMPRESS

Make optimal use of limited storage space

Save time and help to optimize resources

If compression and decompression are done in I/O

processor, less time is required to move data to orfrom storage subsystem, freeing I/O bus for other

work

In sending data over communication line: less timeto transmit and less storage to host


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TYPES OF COMPRESSION TECHNIQUES

Compression techniques can be

categorized based on following

consideration: Lossless or lossy

Symmetrical or asymmetrical

Software or hardware


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TYPES OF COMPRESSION TECHNIQUES

1. Lossless or lossy

If the decompressed data is the same as the original data, it isreferred to as lossless compression, otherwise the compression islossy.

2. Symmetrical or asymmetrical

In symmetrical compression, the time required to compress and todecompress are roughly the same.

In asymmetrical compression, the time taken for compression is

usually much longer than decompression.3. Software or hardware

A compression technique may be implemented either in hardwareor software. As compared to software codecs (coder and decoder),

hardware codecs offer better quality and performance.


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DATA COMPRESSION METHODS

Data compression is about storing and sending a smaller

number of bits.

Therere two major categories for methods to compress

data: lossless and lossy methods


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LOSSLESS COMPRESSION

METHODS

In lossless methods, original data and the data after

compression and decompression are exactly the same.

Redundant data is removed in compression and addedduring decompression.

Lossless methods are used when we cant afford to loseany data: legal and medical documents, computer

programs.


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RUN-LENGTH ENCODING

Simplest method of compression.

How: replace consecutive repeating occurrences of a symbol by 1 occurrence of

the symbol itself, then followed by the number of occurrences.

Example: Consider string Xtmprsqzntwlfb

After RLE encoding, this string becomes:

1X1t1m1p1r1s1q1z1n1t1w1l1f1bRLE schemes are simple and fast, but their compression efficiency depends on the type of data being

encoded.

Example:A black-and-white image that is mostly white, such as the page of a book, will encode very

well, due to the large amount of contiguous data that is all the same color. An image with many colors

that is very busy in appearance, however, such as a photograph, will not encode very well. This is

because the complexity of the image is expressed as a large number of different colors. And because of

this complexity there will be relatively few runs of the same color.


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HUFFMAN CODING

Assign fewer bits to symbols that occur more frequently and morebits to symbols appear less often.

Theres no unique Huffman code and every Huffman code has thesame average code length.

Algorithm:1. Make a leaf node for each code symbol

Add the generation probability of each symbol to the leaf node

2. Take the two leaf nodes with the smallest probability and connect them into a newnode

Add 1 or 0 to each of the two branches

The probability of the new node is the sum of the probabilities of the twoconnecting nodes

3. If there is only one node left, the code construction is completed. If not, go back to(2)


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HUFFMAN CODING

Example


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HUFFMAN CODING

Encoding

Decoding


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LEMPEL ZIV ENCODING

It is dictionary-basedencoding

Dictionary coding techniques rely upon the observation that there arecorrelations between parts of data (recurring patterns). The basic idea is to

replace those repetitions by (shorter) references to a "dictionary" containing the

original.

The dictionary based method may be static or dynamic depending upon the

creation and use of dictionary.

Static dictionary is prepared before the communication of the encoded message

to the receivers end. All possible chars/words/phrases are inserted into the

dictionary and indexed.

The main drawback of static method is that performance depends upon the text

to be encoded and is highly dependent on the organization of thechars/words/phrases in the dictionary.

Secondly, if there is any word not in the dictionary, it fails.

The solution to the problem is dynamic dictionary compression. In this method,

the dictionary is prepared at the time of encoding of text.

LZ77, LZ78 AND LZW techniques use dynamic dictionary compressiontechni ue.


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LZ77 (LEMPEL-ZIV) COMPRESSION

TECHNIQUE

The dictionary used is actually a portion of the input text, which has beenrecently encoded.

The text that needs to be encoded is compared with the strings of symbols in the

dictionary.

The longest matched string in the dictionary is characterized by a pointer

(sometimes called a token), which is represented by a triple of data items.

Note that this triple functions as an index to the dictionary.

In this way,a variable-length string of symbols is mapped to a fixed-length

pointer.

There is a sliding window in the LZ77 algorithms. The window consists of two

parts: a search buffer and a look-ahead buffer.

The search buffer contains: the portion of the text stream that has recently beenencoded ---the dictionary.

The look-ahead buffer contains: the text to be encoded next.

The window slides through the input text stream from beginning to end during

the entire encoding process.


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TECHNIQUE

3. Once the longest match has been found, the encoder encodes it with a

triple where o is the offset, l is the length of the match and c isthe code-word corresponding to the symbol in the look-ahead bufferthat follows the match.

In the diagram, the longest match is the first a of the search buffer.The offset o in this case is 2, l is 4, and the symbol in the look-ahead

buffer following the match is r.

The reason for sending the third element in the triple is to take care ofthe situation where no match for the symbol in the look-ahead buffer can

be found in the search buffer. In this case, the offset and the matchlength values are set to 0, and the third element of the triple is the codefor the symbol itself.

For the decoding process, it is basically a table look-up procedure andcan be done by reversing the encoding procedure.

The limitation of the approach is that if the distance between therepeated patterns in the input text stream is larger than the size of thesearch buffer, then the approach cannot utilize the structure to compressthe text. The longest match possible is roughly the size of the look-ahead

buffer.


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TECHNIQUE

No use of the sliding window.

Use encoded text as a dictionary which, potentially, does not have a fixed

size.

Each time a pointer (token) is issued, the encoded string is included in thedictionary.

Once a preset limit to the dictionary size has been reached, either the

dictionary is fixed for the future (if the coding efficiency is good), or it is

reset to zero,i.e., it must be restarted.

Instead of the triples used in the LZ77,only pairs are used in the LZ78.

Specifically, only the position of the pointer to the matched string and the

symbol following the matched string need to be encoded.


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Example: The string S =001212121021012101221011 is to be encoded.Figure shows the encoding process.


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DECODING PROCESS


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LZW COMPRESSION

TECHNIQUE

Improved version of the original LZ78 algorithm is perhaps the

most famous modification and is sometimes even mistakenly

referred to as theLempel Ziv algorithm.

It basically applies the principle of not explicitly transmitting the

next non-matching symbol to the LZ78 algorithm. The onlyremaining output of this improved algorithm are fixed-length

references to the dictionary (indexes).

The dictionary has to be initialized with all the symbols of the

input alphabet and this initial dictionary needs to be made knownto the decoder.

LOSSY COMPRESSION


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LOSSY COMPRESSION

METHODS

Used for compressing images and video files (our eyes

cannot distinguish subtle changes, so lossy data is

acceptable).

These methods are cheaper, less time and space. Several methods:

JPEG: compress pictures and graphics

MPEG: compress video

MP3: compress audio


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THE JPEG STANDARD

Joint Photographic Experts Group Jpeg is the standard compression techniques for still images

Lossy compression

Employs a transform coding method using the DCT (Discrete

Cosine Transform) Main Steps in JPEG Image Compression

1. Transform RGB to YIQ or YUV and subsample color.

2. DCT on image blocks.

3. Quantization.4. Zig-zag ordering and run-length encoding.

5. Entropy coding.


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BLOCK DIAGRAM FOR JPEG

ENCODER


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DCT ON IMAGE BLOCKS

Each image is divided into 8 8 blocks. The 2D

DCT is applied to each block imagef(i, j), with

output being the DCT coefficientsF(u, v) for

each block.

By applying Discrete Cosine Transform (DCT),

the data in time (spatial) domain can be

transformed into frequency domain.


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QUANTIZATION IN JPEG

^F(u, v) = round(F(u, v)/Q(u, v)) F(u, v) represents a DCT coefficient, Q(u, v) is a

quantization matrix entry, and F(u, v)

represents the quantized DCT coefficients whichJPEG will use in the succeeding entropy coding.

The quantization step is the main source for loss

in JPEG compression.

MPEG


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MPEG

ENCODING

Used to compress video.

Basic idea: Each video is a rapid sequence of a set of frames. Each

frame is a spatial combination of pixels, or a picture.

Compressing video =

spatially compressing each frame

+

temporally compressing a set of frames.

MPEG


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MPEG

ENCODING

Spatial Compression Each frame is spatially compressed by JPEG.

Temporal Compression Redundant frames are removed.

For example, in a static scene in which someone is talking, most framesare the same except for the segment around the speakers lips, which

changes from one frame to the next.


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THREE TYPES OF FRAMES

Intra frames (same as JPEG)

Self contained frames

Predictive frames

encode from previous I or P reference frame

Bi-directional frames

encode from previous and future I or P frames

I P IP PB B B B B B B B

3 D SCALABLE MEDICAL IMAGE


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The method employs the 3-D integer wavelet

transform and EBCOT(Embedded block

coding with optimized truncation) to create

bit stream.

Provides random access.

Provides resolution and quality scalability.

High reconstruction quality.

Optimized VOI coding.

3-D SCALABLE MEDICAL IMAGE

COMPRESSION WITH OPTIMIZED VOLUME

OF INTEREST CODING

3 D SCALABLE MEDICAL IMAGE


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3-D SCALABLE MEDICAL IMAGE

COMPRESSION WITH OPTIMIZED VOLUME

OF INTEREST CODING

Block Diagram


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Based on combination of five techniques:

1. Fast 2-D wavelet transform.

2. Rearrangement of wavelet coefficients for efficient

processing.

3. Zerotree coding of correlated coefficients.4. Gradual successive approximation of the wavelet

coefficients.

5. Lossless entropy coding of the quantized coefficients

using either adaptive arithmetic coding,which is slow andgives better compression rate,or adaptive run-length

coding which is faster and has less performance we get

from arithmetic coding.

LOW BIT-RATE EFFICIENT COMPRESSIONFOR SEISMIC DATA


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Wavelet

coefficients

Setthreshold

Classify pass

Coding pass

Arithmetic

coder

The quantization

loop

output

Fig:Compression Algorithm

LOW BIT-RATE EFFICIENT COMPRESSIONFOR SEISMIC DATA


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THANK YOU

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seminarDataCompression.ppt