空间相关性约束下激光束干扰图像数据存储研究

Research on image data storage of laser beam interference in spatial correlation

当前图像数据存储算法在空间相关性约束条件下,数据存储速度慢、可靠性不足,尤其是在受到激光束的干扰时,图像数据存储普遍存在丢帧问题。提出一种基于自适应小波变换与稀疏矩阵算法相结合的图像数据存储技术研究,首先基于灰度图像阈值分割,最小化激光束条纹的干扰;依据图像的局部特征分块处理图像数据,采用自适应小波算法预判图像的纹理,并获取分数像素值,分别对方向信息和变化系数进行编码,完成图像的压缩;最后应用稀疏矩阵存储算法,实现对压缩后图像的高效存储。实验证明提出的综合算法具有更快的图像数据存储速度、在图像检索性能和系统可靠性方面同样具有优势。

In the current image data storage method, the storage speed is slow and the reliability is insufficient. Especially under the interference of laser beam, there is frame loss in the image data storage. This paper proposes an adaptive wavelet transform and sparse matrix algorithm based on image data storage technology research. Removing the interference fringes of the laser beam based on gray image threshold segmentation. Processing image data according to the local characteristics of the image block. Using adaptive wavelet algorithm to predict the texture of the image and obtain the fractional pixel values. Encoding direction information and variation coefficient respectively to complete the compression of image data. Finally realizing high efficient storage of compressed image through the application of sparse matrix algorithm. Experimental results show that the proposed algorithm has the advantages of fast image data storage speed, image retrieval performance and system reliability.