一种声图像局部自适应增强方法

声图像具有分辨率较低、混响干扰强、物体区域面积小、边界轮廓模糊不清等特点，因此采用全局的增强算法不能取得满意的结果。根据声图像特点，定义了局部增强函数，以边缘数目、边缘强度和熵定义了评价函数，通过采用PSO算法对增强函数中的参数进行了优化选取。最后与已实现的迭代自适应增强算法和直方图均衡化算法进行了对比分析，结果表明，该算法在保持了原图的灰度级的基础上，不但明显改善图像视觉效果，而且有效地增强和保留图像细节，改善图像质量，利于后续图像检测，是一种适合于声图像的增强方法。

A method of sonar image enhancement

Sonar Images have some characteristics such as low resolution, strong echo disturbance ,small object regions and obscure object edges, so the satisfied results can＇t be obtained by the global enhancement algorithm. An adaptive local enhancement algorithm is proposed in this paper, and the evaluation function is defined by edge numbers, edge intensity and the entropy. Due to the high complexity of the algorithm proposed, the particle swarm optimization algorithm is used to search the optimal parameters for the best enhancement. The presented algorithm was compared with other automatic contrast enhancement techniques-histogram equalization and iterative enhancement, the results obtained show the superiority of the presented method. This method can not only improve the vision effect obviously,but also enhance the image contrast and hold the details simultaneously. The qualities of images treated are more suitable for the detection algorithm.