基于视觉传达技术的激光光斑图像超分辨率重建方法

Super-resolution reconstruction method for laser spot images based on visual communication technology

激光光斑图像在成像过程中易受到成像条件和成像方式的限制,导致激光光斑图像的分辨率比较低,难以满足实际需求。为此,提出基于视觉传达技术的激光光斑图像超分辨率重建方法。采用视觉传达技术采集激光光斑图像,并使用双树复小波阈值方法对激光光斑图像去噪处理,通过改进稠密神经网络提取激光光斑图像特征,基于奇异值分解方法降低字典中原子的数目,改进稀疏表达正则化方法,实现激光光斑图像的超分辨率重建。实验结果表明,所提方法的低分辨率图像重建结果与原始图像更加接近,重建图像的结构相似度均在0.9以上,证明该方法的重建效果好、更适合实际应用。

Laser spot images are easily limited by imaging conditions and imaging methods during the imaging process,resulting in low resolution of laser spot images and difficulty in meeting practical needs.Therefore,a superresolution reconstruction method for laser spot images based on visual communication technology is proposed.The visual communication technology is used to collect the laser spot image,and the dual tree complex wavelet threshold method is used to denoise the laser spot image.The dense neural network is improved to extract the characteristics of the laser spot image,the number of atoms in the dictionary is reduced based on the singular value decomposition method,and the sparse expression regularization method is improved to achieve the super-resolution reconstruction of the laser spot image.The experimental results show that the low resolution image reconstruction results of the proposed method are closer to the original image,and the structural similarity of the reconstructed images is above 0.9,proving that the reconstruction effect of this method is good and more suitable for practical applications.