2.2 Data Compression

Cards (53)

  • Data compression is the process of reducing the size of data to save storage space or reduce
  • Steps in lossy compression for multimedia data
    1️⃣ Convert data to frequency domain
    2️⃣ Discard high-frequency components
    3️⃣ Encode remaining data
    4️⃣ Reconstruct data partially
  • The need for data compression arises from the ever-increasing amount of digital data being generated and stored
  • Match the benefit of data compression with its description:
    Reduced Storage Space ↔️ Allows more data to be stored
    Faster Transmission ↔️ Enables quicker data transfer
    Efficient Bandwidth Usage ↔️ Lowers bandwidth consumption
    Improved Application Performance ↔️ Speeds up loading times
  • Steps in transform coding for lossy compression
    1️⃣ Convert data into frequency domain
    2️⃣ Discard high-frequency components
    3️⃣ Encode remaining components
  • What does a video codec like H.264 achieve?
    Reduces file size
  • Match the lossy compression technique with its example:
    Transform Coding ↔️ JPEG image compression
    Predictive Coding ↔️ MP3 audio compression
    Vector Quantization ↔️ H.264 video codecs
  • What does Vector Quantization represent a group of similar data points with?
    A single code
  • There are two main types of data compression: lossless and lossy
  • Data compression is essential for applications with bandwidth or storage constraints
  • Order the benefits of data compression from a user perspective:
    1️⃣ Reduced Storage Space
    2️⃣ Faster Transmission
    3️⃣ Efficient Bandwidth Usage
    4️⃣ Improved Application Performance
  • Run-Length Encoding is effective for data with long repeating sequences.

    True
  • Which compression type permanently loses some data during compression?
    Lossy
  • Data compression is essential for applications with bandwidth or storage constraints.

    True
  • Which lossless compression technique assigns shorter codes to more frequent symbols?
    Huffman Coding
  • Predictive Coding encodes only the difference between the current and predicted values
  • Lossy compression techniques permanently discard some data to achieve greater file size reduction.
    True
  • Predictive Coding in MP3 compression encodes only the difference between current and predicted values.
    True
  • What is the primary goal of data compression?
    Reduce file size
  • Match the compression type with its example:
    Lossless ↔️ ZIP files
    Lossy ↔️ JPEG images
  • Decreased file sizes enable faster transmission over networks.

    True
  • Run-Length Encoding (RLE) replaces repeating sequences with the count of the repetition
  • Lempel-Ziv Welch (LZW) builds a codebook of frequently occurring phrases
  • Predictive Coding reduces file size in MP3 audio compression but may degrade audio quality.

    True
  • Lossless compression allows the original data to be perfectly reconstructed, while lossy compression permanently discards some data.

    True
  • What are the two main categories of data compression techniques?
    Lossless and lossy
  • What is the key difference between lossless and lossy compression in terms of data fidelity?
    Data fidelity is preserved in lossless compression
  • The Lempel-Ziv Welch (LZW) algorithm builds a codebook of frequently occurring phrases
  • Lossless compression is preferred for applications where data fidelity must be preserved.

    True
  • Match the lossy compression technique with its description:
    Transform Coding ↔️ Discards high-frequency components
    Predictive Coding ↔️ Encodes differences between values
    Vector Quantization ↔️ Represents data with a single code
  • Vector Quantization in video codecs like H.264 can introduce blurriness or blockiness
  • The MP3 audio compression encodes only the difference between the current and predicted values
  • Lossless compression provides higher compression ratios compared to lossy compression.
    False
  • Run-Length Encoding (RLE) replaces repeating sequences with a count of the repetition.

    True
  • What type of data is commonly compressed using transform coding, and what is a potential drawback?
    Images; visual artifacts
  • In lossless compression, the original data can be perfectly reconstructed from the compressed data.

    True
  • Lossless compression reduces file size by removing redundant data.

    True
  • What is an example of a file format commonly associated with lossless compression?
    ZIP
  • Run-Length Encoding (RLE) replaces repeating sequences with the count of the repetition
  • Lossy compression always results in reduced data quality compared to the original.

    True