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Image contrast enhancement using an artificial bee colony algorithm

机译:使用人工蜂菌落算法的图像对比度增强

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摘要

The objective of image contrast enhancement is to improve the contrast level of images, which are degraded during image acquisition. Image contrast enhancement is considered as an optimization problem in this paper and the artificial bee colony (ABC) algorithm is utilized to find the optimal solution for this optimization problem. The contribution of the proposed approach is two-fold. First, in view of that the fitness function is indispensable to evaluate the quality of the enhanced image, a new objective fitness function is proposed in this paper. Second, the image transformation function is critical to generate new pixel intensities for the enhanced image from the original input image; more importantly, it guides the searching movements of the artificial bees. For that, a parametric image transformation function is utilized in this paper so that only the optimal parameters used in the transformation function need to be searched by the ABC algorithm. This is in contrast to that the whole space of image intensity levels is used in the conventional ABC-based image enhancement approaches. Extensive experiments are conducted to demonstrate that the proposed approach outperforms conventional image contrast enhancement approaches to achieve both better visual image quality and higher objective performance measures.
机译:图像对比度增强的目的是改善图像采集期间降低的图像的对比度水平。图像对比度增强被认为是本文中的优化问题,并且人造蜂菌落(ABC)算法用于找到该优化问题的最佳解决方案。所提出的方法的贡献是两倍。首先,鉴于对增强图像的质量不可或缺的健身功能,本文提出了新的客观健身功能。其次,图像转换功能对于从原始输入图像生成增强图像的新像素强度至关重要;更重要的是,它引导了人造蜜蜂的搜索运动。为此,本文利用了参数图像变换功能,以便仅需要通过ABC算法搜索变换功能中使用的最佳参数。与传统的ABC的图像增强方法相比,这与图像强度水平的整个空间相反。进行了广泛的实验以证明所提出的方法优于传统的图像对比增强方法,以实现更好的视觉图像质量和更高的客观性能措施。

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