Introduces data compression, exploring how redundancy in data can be reduced to achieve smaller file sizes without losing information.
Explores image compression principles, focusing on JPEG 2000, covering transform-based coding, quantization, entropy coding, region of interest, error resilience, and software implementations.
Explores entropy theory, compression without loss, and the efficiency of the Shannon-Fano algorithm in data compression.
Explores data compression through entropy definition, types, and practical examples, illustrating its role in efficient information storage and transmission.
