基于视觉传达技术的激光图像多级融合方法研究

Research on laser image multilevel fusion method based on visual communication technology

设计了基于视觉传达技术的激光图像多级融合方法,以获得突出的视觉传达效果。首先采用改进单尺度Retinex算法提取原始激光图的反射图像,并通过高斯-拉普拉斯算法的重构获得的多尺度彩色图像,实现原始激光图像的增强,然后采用深度堆叠卷积神经网络对获得高、低频图像,并依据最大局部方差融高频图像,根据匹配度与阈值的对比融合低频图像,最后实验结果表明:堆叠CNN数量为4时,融合后的激光图像视觉传达效果最优,该方法增强后的激光图像局部细节信息丰富、色彩饱满度好,融合图像的图像最大灰度值频率仅为0.015。

A multi-level fusion method for laser images based on visual communication technology was designed to achieve outstanding visual communication effects.Firstly,the improved single scale Retinex algorithm is used to ex-tract the reflection image of the original laser image,and the multi-scale color image obtained through reconstruction using the Gaussian Laplace algorithm is used to enhance the original laser image.Then,a deep stacked convolutional neural network is used to obtain high and low frequency images,and high-frequency images are fused based on the maximum local variance.Low frequency images are fused based on the comparison between matching degree and threshold,The final experimental results show that when the number of stacked CNN is 4,the visual communication effect of the fused laser image is the best.The enhanced laser image has rich local detail information and good color fullness,and the maximum grayscale frequency of the fused image is only 0.015.