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Questions and Answers
What is the first byte of a run-length encoded packet used for?
What is the first byte of a run-length encoded packet used for?
Why might run-length encoding (RLE) increase data size when applied inappropriately?
Why might run-length encoding (RLE) increase data size when applied inappropriately?
What is a significant limitation of run-length encoding?
What is a significant limitation of run-length encoding?
In which order is bitmap data typically encoded in normal RLE?
In which order is bitmap data typically encoded in normal RLE?
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What characterizes diatomic encoding in relation to run-length encoding?
What characterizes diatomic encoding in relation to run-length encoding?
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What happens when a run of less than two characters is encountered in RLE?
What happens when a run of less than two characters is encountered in RLE?
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How does the compression ratio of RLE vary across different types of data?
How does the compression ratio of RLE vary across different types of data?
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Which variant of RLE involves scanning the image diagonally?
Which variant of RLE involves scanning the image diagonally?
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What is the primary purpose of vertical replication packets?
What is the primary purpose of vertical replication packets?
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Using run-length encoding (RLE), how many bytes are required to encode 100 identical scan lines with vertical replication packets?
Using run-length encoding (RLE), how many bytes are required to encode 100 identical scan lines with vertical replication packets?
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What is the first step in applying the Shannon-Fano algorithm?
What is the first step in applying the Shannon-Fano algorithm?
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In a scenario where symbols A, B, C, D, and E have frequencies of 15, 7, 6, 6, and 5 respectively, what is the general approach of the Shannon-Fano encoding algorithm?
In a scenario where symbols A, B, C, D, and E have frequencies of 15, 7, 6, 6, and 5 respectively, what is the general approach of the Shannon-Fano encoding algorithm?
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How does the use of frequent pairs in data encoding affect the overall data size?
How does the use of frequent pairs in data encoding affect the overall data size?
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What defines a fundamental principle of entropy as it relates to information theory?
What defines a fundamental principle of entropy as it relates to information theory?
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Which is NOT a feature of run-length encoding (RLE)?
Which is NOT a feature of run-length encoding (RLE)?
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What is the expected result of applying a count byte in vertical replication packets for run-length encoding?
What is the expected result of applying a count byte in vertical replication packets for run-length encoding?
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What is the significance of a character string 'nnn' requiring 15 bits when each 'n' has a probability of 1/32?
What is the significance of a character string 'nnn' requiring 15 bits when each 'n' has a probability of 1/32?
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Which of the following best describes pixel packing?
Which of the following best describes pixel packing?
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In pattern substitution, what is the primary objective?
In pattern substitution, what is the primary objective?
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What does repetition suppression replace in a data sequence?
What does repetition suppression replace in a data sequence?
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Which of the following is not an application of repetition suppression?
Which of the following is not an application of repetition suppression?
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What defines the effectiveness of Run-Length Encoding (RLE)?
What defines the effectiveness of Run-Length Encoding (RLE)?
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Which bitmap formats typically support Run-Length Encoding (RLE)?
Which bitmap formats typically support Run-Length Encoding (RLE)?
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What is one drawback of using lossless data compression techniques like pixel packing?
What is one drawback of using lossless data compression techniques like pixel packing?
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Study Notes
Data Compression
- Data compression is a method of reducing the size of information.
- It's used to reduce storage needs and speed up communication.
- Key reasons for data compression include storage requirements, memory requirements and communication speed.
- Compression reduces the physical size of information.
- It uses simple, efficient digital representation.
Data Compression/Decompression Tradeoff
- Compressor reduces the size of the data.
- Decompressor reconstructs the original data.
Data Compression Schemes
- Common schemes include pattern substitution, run-length encoding (RLE), Lempel-Ziv-Welch (LZW), Huffman encoding, and Discrete Cosine Transform (DCT).
- Motion Picture Experts Group (MPEG) is used frequently.
- Bitmap files only compress the bitmap data; headers, palette, and footer remain unchanged.
- Vector file image data is already compressed. Compressing vector files usually compresses the whole file.
Data Compression Terminology
- Raw data is data before any compression.
- Compressed data is data after compression.
- Compression Ratio measures the ratio of uncompressed to compressed data.
Types of Compression
- Symmetric Methods use similar algorithms in both directions with the same amount of work.
- Asymmetric Methods use more work in one direction than the other.
Encoder Schemes
- Dictionary-based encoders may be adaptive or non-adaptive.
- Non-adaptive encoders use static dictionaries and need prior statistics.
- Adaptive encoders adjust to any type of data.
- Semi-adaptive encoders build a dictionary in an initial pass and then perform encoding in a second pass.
Lossy and Lossless Compression
- Lossless compression preserves all original information. -Lossy compression discards some information (typically high-frequency components) resulting in decreased file size.
Classification of Compression Techniques
- Entropy coding (lossless): Used regardless of media characteristics
- Source coding (lossy): considers semantics of data, variable compression ratio and uses extensive use of specific medium characteristics
- Hybrid coding: combination of entropy coding and source coding
Information Theory
- Information theory provides a lower limit on the size to which information can be reduced.
- Based on the distribution of actual values.
- Entropy (H): The number of bits needed to code each symbol.
- Shannon's entropy formula determines the theoretical compression limit.
Pixel Packing
- Pixel packing is used to reduce the memory requirement of image data
- Bit-oriented representation reduces the storage requirement of image data from 4096 bytes to 2048 bytes.
Lossless Data Compression
- Statistical Encoding: Form of encoding involves substituting a repeating pattern to predefined codes.
- Codes are usually smaller than the repeating symbols.
- Count occurrences, sort in descending order and assign symbols to the highest patterns.
- Use symbol table to assign codes.
Run-Length Encoding (RLE)
- Suitable for encoding repeating strings.
- Encodes repeating strings of characters using two bytes
- The first byte represents the number of characters in the run.
- The second byte identifies the character.
- RLE is limited to encoding sequences of identical characters.
Run Length Encoding (RLE) - Variants
- Encoding may be along the X axis, Y axis, or diagnally along a zigzag path.
- Encoding may be different depending on the file format, e.g. BMP, PCX, TIFF, or PDF.
- Variant implementations of RLE are used in specific and specialized applications.
Vertical Replication Packets
- A method to reduce storing repeated scanline data.
- Reduces storage by storing only the count, rather than the data for each scanline.
Huffman Coding
- A popular lossless data compression method.
- It builds a binary tree based on symbol probabilities to assign variable-length codes.
- Symbols with higher probabilities get shorter codes.
- Huffman coding assigns codes to symbols for efficient encoding.
- Works effectively when certain symbols occur more frequently than others.
Huffman Coding (Binary Tree Construction)
- Leaves represent symbols in a sorted list.
- Nodes represent the sum of the children's frequencies.
- Codes are assigned recursively to the left and right subtree depending on whether the bit is 0 or 1.
Huffman Decoding
- It involves using the Huffman tree to traverse through the binary code.
- If a 0 is encountered, it moves to the left node.
- If a 1 is encountered, it moves to a right node.
- The decoding process stops at a leaf node.
- The character assigned to this leaf is then output.
Lempel-Ziv-Welch (LZW) Compression
- An adaptive dictionary-based compression technique.
- Codes are assigned to repetitive patterns and substituted with shorter codes.
- As codes are created, they are added to the dictionary.
- LZW codes are variable length.
JPEG Compression
- Lossy compression technique used for images and graphics.
- Achieves compression by discarding less significant information.
- Works by using a series of transformations followed by quantization.
JPEG Compression - Variations
- Compression quality and compression choices can be tuned to control the amount of information retained in the image.
Video and Animation Compression
- Reduces video data by discarding less visually important information.
- Strategies used to reduce data include reducing frame rate, using spatial and temporal redundancy.
- Types of frames include I-frames, P-frames and B-frames, which are coded differently depending on the content to optimize compression.
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Description
Explore the fundamentals of run-length encoding (RLE) and the Shannon-Fano algorithm through this quiz. Test your understanding of data encoding, limitations, and practical applications. Perfect for students interested in data compression methods in computer science.
