Lossless Compression: Shannon-Fano and Huffman

This lecture covers the principles of lossless compression, focusing on exploiting data redundancy to shorten sequences efficiently. It introduces the Shannon-Fano algorithm, which divides letters based on their frequency, and the Huffman algorithm, which assigns variable-length codes to optimize compression. By comparing the two methods, the instructor demonstrates how Huffman coding outperforms Shannon-Fano in terms of efficiency and speed. The lecture also delves into the concept of entropy, calculating the entropy of a given sequence to highlight the effectiveness of Huffman coding in minimizing the average number of bits per letter.