Data Compression Algorithms

Question 1

What is lossless compression?

Answer 1

A data compression method that allows the original data to be perfectly reconstructed from the compressed data (e.g., ZIP, PNG). Ideal for text or data where accuracy is critical.

Question 2

You need to compress a high-resolution image for a website while maintaining a small file size. Which compression method should you use: Lossy or Lossless?

Answer 2

Lossy compression (e.g., JPEG), as it significantly reduces file size by discarding some data, which is acceptable for images viewed online.

Question 3

Describe how Huffman Coding compresses data.

Answer 3

Huffman Coding assigns shorter binary codes to more frequently used characters, creating an optimized prefix tree to reduce file size.

Question 4

What is a trade-off of using lossy compression for audio files?

Answer 4

Reduces file size significantly but results in a loss of sound quality, which may affect the listening experience.

Question 5

What is Run-Length Encoding (RLE)?

Answer 5

A compression method that replaces consecutive repeated characters with a single character and a count (e.g., “AAAA” becomes “A4”).

Question 6

Lossy vs. Lossless: Which is better for compressing a document? Why?

Answer 6

Lossless, because documents require exact data recovery, and lossy compression would result in data loss.

Question 7

What is a key drawback of lossy compression?

Answer 7

The original data cannot be perfectly restored, leading to a potential loss in quality (e.g., audio fidelity).