Huffman Coding Presentation
| Introduction to Huffman Coding | ||
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| Huffman coding is a lossless data compression algorithm. It was developed by David Huffman in 1952. This algorithm is widely used in applications that require efficient data compression. | ||
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| Basic Concepts of Huffman Coding | ||
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| Huffman coding uses a frequency-based approach for compression. It assigns shorter codes to frequently occurring symbols and longer codes to less frequent symbols. The codes are constructed based on a binary tree structure. | ||
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| Steps in Huffman Coding | ||
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| Step 1: Determine the frequency of each symbol in the input data. Step 2: Create a priority queue or a min-heap based on the frequencies. Step 3: Build a Huffman tree by repeatedly merging the two lowest frequency nodes. | ||
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| Example - Step 1 | ||
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| Input data: "ABBCCCDDDDEEEEE" Frequency of symbols: - A: 1 - B: 2 - C: 3 - D: 4 - E: 5 Your third bullet | ||
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| Example - Step 2 | ||
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| Priority queue based on frequencies:
- A: 1
- B: 2
- C: 3
- D: 4
- E: 5 Your second bullet Your third bullet | ||
| 5 | ||
| Example - Step 3 | ||
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| Huffman tree construction process:
- Merge nodes with the lowest frequencies.
- Update the frequencies of merged nodes.
- Repeat until a single node is left. Your second bullet Your third bullet | ||
| 6 | ||
| Example - Step 4 | ||
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| Assigning binary codes to symbols:
- A: 111
- B: 10
- C: 01
- D: 00
- E: 11 Your second bullet Your third bullet | ||
| 7 | ||
| Compression Ratio | ||
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| Huffman coding achieves variable-length encoding, resulting in a smaller output size. The compression ratio depends on the frequency distribution of symbols. Symbols with higher frequencies have shorter codes, leading to better compression. | ||
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| Decoding Huffman Codes | ||
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| Decoding Huffman codes involves traversing the Huffman tree. Start from the root and follow the path based on the received code. Once a leaf node is reached, output the corresponding symbol and continue from the root. | ||
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| Conclusion | ||
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| Huffman coding is an efficient method for lossless data compression. It reduces the size of data by assigning shorter codes to frequently occurring symbols. Huffman coding is widely used in applications like file compression, image compression, and data transmission. | ||
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