论文标题
图像分割的基于OTSU的差分进化方法
Otsu based Differential Evolution Method for Image Segmentation
论文作者
论文摘要
本文提出了一种基于OTSU的差异进化方法，用于卫星图像分割，并将其与其他四种方法进行比较，例如改进的人造蜜蜂菌落优化器（MABC），人工蜜蜂菌落（ABC），遗传算法（GA）（GA）和使用OTSU的目标功能提出的优化目标功能。进行的实验及其结果表明，我们提出的DE和OTSU算法分割可以有效，精确地分割输入图像，接近其他方法获得的结果。在拟议的DE和OTSU算法中，在获得OTSU算法中输入级别的级别级别的阈值之后，整个图像被作为输入DE算法的输入传递。图像分割结果是在了解图像后而不是了解健身变量后获得的。与研究的其他分割方法相比，与某些算法相比，提出的DE和OTSU算法可产生有希望的结果，计算时间最小。
This paper proposes an OTSU based differential evolution method for satellite image segmentation and compares it with four other methods such as Modified Artificial Bee Colony Optimizer (MABC), Artificial Bee Colony (ABC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) using the objective function proposed by Otsu for optimal multilevel thresholding. The experiments conducted and their results illustrate that our proposed DE and OTSU algorithm segmentation can effectively and precisely segment the input image, close to results obtained by the other methods. In the proposed DE and OTSU algorithm, instead of passing the fitness function variables, the entire image is passed as an input to the DE algorithm after obtaining the threshold values for the input number of levels in the OTSU algorithm. The image segmentation results are obtained after learning about the image instead of learning about the fitness variables. In comparison to other segmentation methods examined, the proposed DE and OTSU algorithm yields promising results with minimized computational time compared to some algorithms.
