This document discusses various methods of data compression. It begins by defining compression as reducing the size of data while retaining its meaning. There are two main types of compression: lossless and lossy. Lossless compression allows for perfect reconstruction of the original data by removing redundant data. Common lossless methods include run-length encoding and Huffman coding. Lossy compression is used for images and video, and results in some loss of information. Popular lossy schemes are JPEG, MPEG, and MP3. The document then proceeds to describe several specific compression algorithms and their encoding and decoding processes.
Types of Data compression, Lossy Compression, Lossless compression and many more. How data is compressed etc. A little extensive than CIE O level Syllabus
In computer science and information theory, data compression, source coding,[1] or bit-rate reduction involves encoding information using fewer bits than the original representation.[2] Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression.
Comparison of various data compression techniques and it perfectly differentiates different techniques of data compression. Its likely to be precise and focused on techniques rather than the topic itself.
This is the subject slides for the module MMS2401 - Multimedia System and Communication taught in Shepherd College of Media Technology, Affiliated with Purbanchal University.
Types of Data compression, Lossy Compression, Lossless compression and many more. How data is compressed etc. A little extensive than CIE O level Syllabus
In computer science and information theory, data compression, source coding,[1] or bit-rate reduction involves encoding information using fewer bits than the original representation.[2] Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression.
Comparison of various data compression techniques and it perfectly differentiates different techniques of data compression. Its likely to be precise and focused on techniques rather than the topic itself.
This is the subject slides for the module MMS2401 - Multimedia System and Communication taught in Shepherd College of Media Technology, Affiliated with Purbanchal University.
Computer Science/ICT - Data Compression
This presentation covers all aspects of data compression you'll need to know such as definition, reasons, types of compression (lossy and lossless) and the types of compression within those sections (JPEG, MPEG, MP3, Run Length and Dictionary Based encoding)
This presentation is about JPEG compression algorithm. It briefly describes all the underlying steps in JPEG compression like picture preparation, DCT, Quantization, Rendering and Encoding.
Presentation given in the Seminar of B.Tech 6th Semester during session 2009-10 By Paramjeet Singh Jamwal, Poonam Kanyal, Rittitka Mittal and Surabhi Tyagi.
What is Video Compression?, Introduction of Video Compression. Motivation, Working Methodology of Video Compression., Example, Applications, Needs of Video Compression, Advantages & Disadvantages
Computer Science/ICT - Data Compression
This presentation covers all aspects of data compression you'll need to know such as definition, reasons, types of compression (lossy and lossless) and the types of compression within those sections (JPEG, MPEG, MP3, Run Length and Dictionary Based encoding)
This presentation is about JPEG compression algorithm. It briefly describes all the underlying steps in JPEG compression like picture preparation, DCT, Quantization, Rendering and Encoding.
Presentation given in the Seminar of B.Tech 6th Semester during session 2009-10 By Paramjeet Singh Jamwal, Poonam Kanyal, Rittitka Mittal and Surabhi Tyagi.
What is Video Compression?, Introduction of Video Compression. Motivation, Working Methodology of Video Compression., Example, Applications, Needs of Video Compression, Advantages & Disadvantages
A description about image Compression. What are types of redundancies, which are there in images. Two classes compression techniques. Four different lossless image compression techiques with proper diagrams(Huffman, Lempel Ziv, Run Length coding, Arithmetic coding).
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This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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2. What is Compression?
• Reduce the size of data.
• Also, Compression is a way to reduce the number of bits in a
frame but retaining its meaning.
• Advantages:
» Reduce storage needed
» Reduce transmission cost/latency/bandwidth.
.
4. Lossless compression
• Lossless compression is a class of data compression that
allows the original data to be perfectly reconstructed from
the compressed data.
• Redundant data is removed in compression and added
during decompression.
• Most lossless compression programs do two things in
sequence: the first step generates a statistical model for the
input data, and the second step uses this model to map input
data to bit sequences in such a way that "probable" (e.g.
frequently encountered) data will produce shorter output
than "improbable" data.
5. Method 1: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.
• The method can be more efficient if the data uses only 2
symbols (0s and 1s) in bit patterns and 1 symbol is more
frequent than another.
6. Method 2:Huffman Coding
Assign fewer bits to symbols that occur more frequently and
more bits to symbols appear less often.
There’s no unique Huffman code and every Huffman code has
the same average code length.
Algorithm:
①
②
③
Make a leaf node for each code symbol
Add the generation probability of each symbol to the leaf node
Take the two leaf nodes with the smallest probability and connect them into
a new node
Add 1 or 0 to each of the two branches
The probability of the new node is the sum of the probabilities of the
two connecting nodes
If there is only one node left, the code construction is completed. If not, go
back to (2)
8. How the encoding and decoding process
takes place?
• Encoding:
• Decoding:
9. Method 3:Lempel Ziv Encoding
• It is dictionary-based encoding
• Basic idea:
Create a dictionary(a table) of strings used during
communication.
If both sender and receiver have a copy of the
dictionary, then previously-encountered strings can be
substituted by their index in the dictionary.
10. Contd...,
This compression has 2 phases:
Building an indexed dictionary
Compressing a string of symbols
• Algorithm for lempel ziv encoding:
Extract the smallest substring that cannot be found in the
remaining uncompressed string.
Store that substring in the dictionary as a new entry and
assign it an index value
Substring is replaced with the index found in the
dictionary
Insert the index and the last character of the substring
into the compressed string
12. Lossy Compression
• Lossy compression is the converse of lossless data
compression.
• It is Used for compressing images and video files.
• Methods of lossy compression:
JPEG: compress pictures and graphics
MPEG:compress video
MP3: compress audio
13. Method 1:JPEG Encoding
• Used to compress pictures and graphics.
• In JPEG, a grayscale picture is divided into 8x8 pixel
blocks to decrease the number of calculations.
• Basic idea:
Change the picture into a linear (vector) sets of numbers that
reveals the redundancies.
The redundancies is then removed by one of lossless.
14. JPEG Encoding- DCT
• DCT: Discrete Concise Transform
• DCT transforms the 64 values in 8x8 pixel block in a way that
the relative relationships between pixels are kept but the
redundancies are revealed.
• Example:
A gradient grayscale
15. Quantization & Compression
Quantization:
After T table is created, the values are quantized to
reduce the number of bits needed for encoding.
Quantization divides the number of bits by a constant,
then drops the fraction. This is done to optimize the
number of bits and the number of 0s for each particular
application.
• Compression:
Quantized values are read from the table and redundant
0s are removed.
To cluster the 0s together, the table is read diagonally in
an zigzag fashion. The reason is if the table doesn’t have
fine changes, the bottom right corner of the table is all 0s.
JPEG usually uses lossless run-length encoding at the
compression phase.
17. Method 2: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.
18. Types of MPEG compression
• 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
frames are the same except for the segment around the speaker’s
lips, which changes from one frame to the next.
19. Method 3:Audio(or)Mp3 Encoding
• Used for speech or music
Speech: compress a 64 kHz digitized signal
Music: compress a 1.411 MHz signal
• Two categories of techniques:
Predictive encoding
Perceptual encoding
20. Categories:
Predictive Encoding
Only the differences between samples are encoded, not
the whole sample values.
Several standards: GSM (13 kbps), G.729 (8 kbps), and
G.723.3 (6.4 or 5.3 kbps)
• Perceptual Encoding: MP3
CD-quality audio needs at least 1.411 Mbps and cannot
be sent over the Internet without compression.
MP3 (MPEG audio layer 3) uses perceptual encoding
technique to compress audio.