计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (2): 185-187.

• 图形、图像、模式识别 • 上一篇    下一篇

人工鱼群算法在自适应图像增强中的应用

丁生荣，马 苗，郭 敏   

  1. 陕西师范大学 计算机科学学院，西安 710062
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2012-01-11 发布日期:2012-01-11

Application of artificial fish swarm algorithm in self-adaptive image enhancement

DING Shengrong, MA Miao, GUO Min   

  1. College of Computer Science, Shaanxi Normal University, Xi’an 710062, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2012-01-11 Published:2012-01-11

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摘要： 图像增强是图像处理中的一个经典问题，以传统的分段线性变换为基础，利用人工鱼群算法和二维Otsu阈值法，提出了一种自适应的图像对比度增强算法。该方法利用优化后的人工鱼群算法自动选取双阈值，依据图像的对比度自动搜索灰度变换斜率，得到最优的分段线性变换曲线，并用之对图像进行增强处理。实验表明，该方法可有效提高图像对比度，且优于直方图均衡化、反锐化掩模等传统的对比度增强方法。

关键词: 图像增强, 人工鱼群算法, Otsu法, 分段线性变换

Abstract: Image enhancement is a typical problem in image processing. Based on the traditional piecewise linear transformation, this paper makes use of Artificial Fish Swarm（AFS） algorithm and two-dimensional Otsu threshold method, and puts forward a self-adaptive image enhancement algorithm. In the algorithm, dual thresholds are selected via an improved AFS algorithm. According to the quality of image contrast, transformative slopes are decided automatically. The image is enhanced with the best piecewise linear transformation curve. Experimental results show the suggested algorithm not only can improve image contrast efficiently, but also is superior to traditional contrast enhancement methods such as histogram equalization method and un-sharp mask method.

Key words: image enhancement, artificial fish swarm algorithm, Otsu method, piecewise linear transformation

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