Lossless compression is a data compression algorithm that allows the original data to be perfectly reconstructed from the compressed data. In other words, when a file is compressed using lossless compression and then decompressed, the resulting file will be identical to the original. Here are some key characteristics: 1. **Data Integrity**: Lossless compression ensures that all original data can be recovered when the file is uncompressed. 2. **Compression Ratio**: Typically achieves lower compression ratios compared to lossy compression, meaning the compressed file might not be as small. 3. **Reversibility**: The process is reversible, allowing the original file to be recreated without any loss of information. 4. **Algorithms**: Common algorithms include Huffman coding, Lempel-Ziv-Welch (LZW), and Burrows-Wheeler Transform (BWT). 5. **File Types**: Commonly used for compressing text files, data files, and bitmap images (e.g., PNG, BMP, and TIFF). 6. **Applications**: Suitable for situations where the integrity of the original data is crucial, such as medical imaging, archival storage, and scientific computing. 7. **CPU Usage**: Generally requires less computational power compared to most lossy algorithms. 8. **File Extensions**: Often seen with extensions like .zip, .tar.gz, .flac, and .png. 9. **Real-Time Capability**: May not be ideal for real-time applications where high compression and fast processing are needed. References: - ["A Comparative Study of Lossless Compression Algorithms"](https://ieeexplore.ieee.org/document/6578193) - ["The Data Compression Book"](https://www.amazon.com/Data-Compression-Book-Mark-Nelson/dp/1558514341)