File compression is a crucial technique in data processing for reducing file size without sacrificing data quality. Effective compression algorithms not only reduce file size but also maintain data integrity. This study compares the performance of two compression algorithms, Golomb Code and Taboo Code, in the context of MP4 file compression. Golomb Code is an efficient compression algorithm for data with geometric distribution, commonly used in lossless compression. Taboo Code is a newer compression algorithm designed to address some limitations of traditional compression methods by using more adaptive and flexible encoding techniques. The study evaluates the performance of both algorithms based on several metrics, including compression ratio, compression speed, and quality of the compressed file. Experiments were conducted on a range of MP4 files with varying sizes and content to achieve comprehensive results and better generalization. The findings indicate that each algorithm has its own strengths and weaknesses. Golomb Code performs better with files that have more regular data patterns and data distributions that align with the algorithm's assumptions. In contrast, Taboo Code excels in flexibility and adaptability with files that have more complex and irregular data patterns.
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