The data produced in today’s Internet and computer world are expanding their wings day by day. With the passage of time, storage and archiving of this data are becoming a significant problem. To overcome this problem, attempts have been made to reduce data sizes using compression methods. Therefore, compression algorithms have received great attention. In this study, two efficient encoding algorithms are presented and explained in a crystal-clear manner. In all compression algorithms, frequency modulation is used. In this way, the characters with the highest frequency after each character are determined and the Huffman encoding algorithm is applied to them. In this study, the compression ratio (CR) is 49.44%. Moreover, 30 randomly selected images in three different datasets consisting of USC-SIPI, UCID, and STARE databases have been used to evaluate the performance of the algorithms. Consequently, excellent results have been obtained in all test images according to well-known comparison algorithms such as the Huffman encoding algorithm, arithmetic coding algorithm, and LPHEA.

中文翻译：

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基于霍夫曼的无损图像编码方案

当今互联网和计算机世界中产生的数据正在一天天张开翅膀。随着时间的推移，这些数据的存储和归档正成为一个重要的问题。为了克服这个问题，已经尝试使用压缩方法来减小数据大小。因此，压缩算法受到了极大的关注。在这项研究中，两种有效的编码算法以一种非常清晰的方式被提出和解释。在所有压缩算法中，都使用频率调制。这样就确定了每个字符后出现频率最高的字符，并对其应用霍夫曼编码算法。在本研究中，压缩比 (CR) 为 49.44%。此外，在 USC-SIPI、UCID、和 STARE 数据库已被用于评估算法的性能。因此，根据著名的比较算法，如霍夫曼编码算法、算术编码算法和 LPHEA，在所有测试图像中都获得了优异的结果。