机场跑道图像去雾增强算法及其实现

机场跑道场景下，由于雾、霾等恶劣天气以及大气散射的作用，使拍摄的图像对比度降低，颜色退化，物体特征难以辨认，影响机场跑道图像的异物检测与识别，带来一些安全隐患。针对上述问题，提出基于双线性插值和中值滤波的改进的引导滤波算法，提高图像对比度和处理速度，利于机场跑道异物检测与识别。仿真结果表明，改进的引导滤波算法与已有算法相比，处理速度提高了2~3倍，且图像彩色值分布更广，直方图更均匀。该算法拥有良好的边缘保持性，在细节增强方面有很好的指导意义。随后将改进的引导滤波算法移植到数字信号处理器( DSP)平台上，以满足实际工程应用对小型化的需求。

An airport runway images defogging algorithm and its implementation

Due to the atmospheric scattering, images obtained under bad weather conditions like fog and haze have low contrast,degraded color,and blurring object features. Low quality images directly affect the detection and recognition of foreign objects and debris,thus result in potential security risks. To solve a-bove problems,the improved guided filtering based on the bilinear interpolation and median filtering is pro-posed. This method enhances the image contrast and improves processing speed,and it is beneficial for the detection and recognition of foreign object and debris. The simulation results show that the processing speed of the improved guided filtering algorithm is improved by 2~3 times compared with the existing algo-rithms,and the color distribution graph of the image is wider and the color histogram of the image is more uniform. The proposed algorithm has good edge preserving and good guidance in detail enhancement. Sub-sequently,the improved guided filtering is transplanted to digital signal processor( DSP) to meet the re-quirements of practical engineering applications.