Lossless Data Compression Using Arithmetic Encoding in Python and Its Applications in Deep Learning

The blog post delves into arithmetic encoding (AE), a lossless data compression algorithm that represents data using fewer bits than the original, without any loss of information. AE works by assigning a probability-based sub-interval for each symbol within the range of 0.0 to 1.0, producing a single number that encodes the entire message. The post provides a detailed explanation of AE's encoding and decoding processes, supported by examples and a Python implementation using the 'decimal' module for high precision. Additionally, AE's applications in deep learning, particularly in image and video compression via autoencoders, are highlighted. The post concludes by emphasizing the promise of AE in achieving high-quality compression with minimal bits per pixel and hints at further exploration and enhancement of the algorithm for various data types.