Vimal Gupta presents on data compression. Data compression reduces the size of files through encoding to use fewer bits. It is beneficial for storage space, transmission time, and speed. There are different types of redundancies like spatial and temporal that compression exploits. Lossless compression preserves all data while lossy compression results in some loss of quality but higher compression ratios. Common lossless methods are run-length coding and Huffman coding, while lossy uses JPEG, MP3, and MPEG. Textbooks on the topic are also listed.

1. Data Compression
Presented By:
Vimal Gupta
Mail id: vimalgupta09@gmail.com
JSS Academy of Technical Education ,Noida.
Student ID . 90e6edaee52a11e98640cff850d558d4
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2. Acknowledgement
• I would like to express my special thanks of gratitude to my teacher Ajay Semalty and Mona
Semalty who gave me the golden opportunity to do this wonderful course “Academic writing
Course” , which also helped me in doing a lot of Research and i came to know about so many
new things I am really thankful to them.
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3. Table of contents
• What is data compression?
• The need of data compression.
• What factors lead to data compression?
• Methods of data compression.
• Text book
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4. What is data compression?
• Data compression is the process of encoding
data more efficiently to achieve a reduction
in file size.
• Data compression is a reduction in the
number of bits needed to represent data.
• Data compression is also called compaction.
• Data may be Text, Image, Audio and Video
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5. The need of data compression
• Storage Space
– Less storage space as size of file get reduced.
• Transmission time
– Less time taken as smaller size file transferred
from source to destination.
• Transmission speed.
– Uploading and downloading of file take less
time due to smaller size.
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6. What factors lead to data
compression?
Redundancy refers to the amount of wasted space consumed by
storage media to record picture information in a digital image.
Image compression is achieved by exploiting redundancies in the
image.
These redundancies could be spatial, spectral, or temporal
redundancy.
Spatial redundancy: elements that are duplicated within a
structure, such as neighboring pixels in a still image.
Spectral redundancy is due to correlation between different color planes.
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7. What factors lead to data
compression?(Cont..)
• Temporal redundancy: pixels in two video
frames that have the same values in the
same location.
• Exploiting temporal redundancy is one of
the primary techniques in video
compression.
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8. Methods of data compression.
• There are two kinds of compression: Lossless and
Lossy.
• Lossless:
– No Loss of Information
• When we encode/decode, we get back original data.
– Most widely used in text compression.
– Compression ratio is very less.(3:1)
• Compression ratio=uncompressed size(in bytes)/
compressed size(in bytes)
– E.g. Run-length coding, Huffman coding, Arithmetic
coding, Lempel-Zev-Welch(LZW)
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9. Methods of data compression.
• Lossy
– Always loss of information.
• When we encode/decode, we get back an
approximation of the original data.
– Most widely used in Image, Audio and Video
compression.
– Compression ratio is very high.(10:1)
– E.g. JPEG(Joint photographic expert group):
compressed image
– MP3: compressed audio
– MPEG(Motion picture expert group): compressed
video
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10. Textbook for data compression
• The Data Compression Book
• Authors: Mark Nelson and Jean-loup Gailly
Publisher: M&T Books, New York, United States of America, 2nd
edition, 1995
ISBN: 1-55851-434-1
• Text Compression
– Authors: Timothy Bell, John Cleary and Ian Witten
Publisher: Prentice-Hall, Englewood, United States of America, 1990
ISBN: 0-13-911991-4
• Introduction to Data Compression
– Author: Khalid Sayood
Publisher: Morgan Kaufmann Publishers, Burlington, United States of America, 2nd edition,
2000
ISBN: 1-55860-558-4
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11. Feedback
• ACADEMIC WRITING COURSE IS AWESOME.
• COURSE IS BENEFICIAL FOR UG,PG AND
DOCTRAL STUDENT
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