基于视觉传达技术的光照变化强烈图像优化处理研究

Research on optimization of image processing with strong illumination change based on visual communication technology

当前方法进行对光照变化强烈图像进行优化时,会造成一定程度的梯度变化,导致后续光照变化强烈图像识别率低,为此,提出了基于视觉传达技术的光照变化强烈图像优化处理方法。以多尺度理论分解强烈光照图像频率,异向扩散方程计算光影图像梯度,视觉传达技术建立反投影优化光照变化强烈图像。对比实验结果表明,相比其他三种传统方法,本方法对光照变化强烈图像的识别率更高、误识率更低,且识别效率更高。说明本方法的光照变化强烈图像优化效果优势明显。

When the current method optimizes the image with strong illumination change,it will cause a certain degree of gradient change,resulting in the subsequent strong illumination change and low image recognition rate.Therefore,an optimization processing method of image with strong illumination change based on visual communication technology is proposed.The multi-scale theory is used to decompose the frequency of strong illumination image,the anisotropic diffusion equation is used to calculate the gradient of light and shadow image,and the visual communication technology is used to establish back projection to optimize the image with strong illumination change.The comparative experimental results show that compared with the other three traditional methods,this method has higher recognition rate,lower false recognition rate and higher recognition efficiency for images with strong illumination changes.It reveals that the illumination change of this method is strong,and the image optimization effect has obvious advantages.