This work is an extension of a previous paper (presented at the Cyberworlds 2019 conference) introducing a new method for fractal compression of bitmap binary images. That work is now extended and enhanced through three new valuable features: (1) the bat algorithm is replaced by an improved version based on optimal forage strategy (OFS) and random disturbance strategy (RDS); (2) the inclusion of new similarity metrics; and (3) the consideration of a variable number of contractive maps, whose value can change dynamically over the population and over the iterations. The first feature improves the search capability of the method, the second one improves the reconstruction accuracy, and the third one computes the optimal number of contractive maps automatically. This new scheme is applied to a benchmark of two binary fractal images exhibiting a complex and irregular fractal shape. The graphical and numerical results show that the method performs very well, being able to reconstruct the input images with high accuracy. It also computes the optimal number of contractive maps in a fully automatic way. A comparative work with other alternative methods described in the literature is also carried out. It shows that the presented method outperforms the previous approaches significantly.

这项工作是对先前论文（在Cyber​​worlds 2019大会上发表的论文）的扩展，该论文介绍了一种用于位图二进制图像的分形压缩的新方法。现在，这项工作通过三个新的有价值的功能得到扩展和增强：（1）蝙蝠算法被基于最佳饲喂策略（OFS）和随机干扰策略（RDS）的改进版本所取代；（2）包含新的相似性指标；（3）考虑可变数量的收缩图，其值可以在总体和迭代过程中动态变化。第一个功能提高了该方法的搜索能力，第二个功能提高了重建精度，第三个功能自动计算了最优的收缩图数量。此新方案适用于显示复杂和不规则分形形状的两个二进制分形图像的基准。图形和数值结果表明，该方法性能很好，能够以较高的精度重建输入图像。它还以全自动方式计算最佳的收缩图数量。还进行了与文献中描述的其他替代方法的比较工作。结果表明，所提出的方法明显优于以前的方法。还进行了与文献中描述的其他替代方法的比较工作。结果表明，所提出的方法明显优于以前的方法。还进行了与文献中描述的其他替代方法的比较工作。结果表明，所提出的方法明显优于以前的方法。