光照不均下图像明暗区域关键目标增强仿真

Simulation of Key Target Enhancement in Light and Dark Area Under Uneven Illumination

对光照不均图像的关键区域进行目标增强,能够有效提高明暗不均图像的处理效率以及处理精度。对图像明暗反差较大区域的关键目标的增强,需要先计算聚类的目标函数,进而确定聚类中心和隶属矩阵,完成图像关键目标的高效增强C传统方法通过图像特征点在RGB颜色空间中的分布规律,利用统计直方图理论模型对关键目标进行初步分割,但忽略了对目标隶属矩阵的确定,导致目标增强效果不理想。提出基于K-means聚类的光照不均图像明暗区域关键目标增强方法,首先获取目标轮廓并恢复其对应像素点,在灰度共生矩阵构建的基础之上,分别对能量、熵、相关性以及对比度进行计算,使得反差较大特征提取效果更好;以以上步骤为依据,对聚类目标函数进行计算,并根据对聚类中心和隶属矩阵的确定,完成图像明暗反差较大区域关键目标的增强。实验结果表明,所提方法在目标增强方面均优于当前方法,同时提高了光照不均对境下图像处理的准确性。

This paper focuses on a method for enhancing key objectives in light and dark area of image with une- ven illumination based on K-means clustering. Firstly, this method obtained the object contour and restored its corre- sponding pixels. On the basis of the gray co-occurrence matrix, our research calculated energy, entropy, correlation and contrast, the feature extraction effect with sharp contrast could be better. According to above steps, this research calculated the clustering objective function. After determining the cluster centers and membership matrix, we comple- ted the enhancement of key objectives in light and dark areas of image with uneven illumination. Simulation results prove that the proposed method is better than the current method in target enhancement, which improves the accuracy of image processing in environment of uneven illumination.