云计算环境下大数据视频图像的尺度空间融合算法研究

针对传统算法融合图像质量差、清晰度低、损失图像包含信息的弊端,提出一种新的云计算环境下大数据视频图像的尺度空间融合算法,介绍了尺度空间理论。通过具有平移不变性特征的提升静态小波变换算法对云计算环境下大数据视频图像进行尺度空间融合,对待融合图像进行提升小波变换分解处理,获取不同尺度空间下的低频子带系数与高频子带系数。针对低频子带系数与高频子带系数给出各自的融合方案,获取融合图像的提升静态小波变换系数。通过提升静态小波逆变换获取最终的融合图像。从主观和客观两个方面对所提算法的融合效果进行测试。结果表明,所提算法主观融合效果好,通过客观评价指标对融合图像进行评价,发现所提算法得到的融合图像清晰度、质量佳,不会损失图像包含信息。

Research on scale space fusion algorithm of large data video images in cloud computing environment

in view of the disadvantages of the traditional algorithms, such as poor image quality, low definition and loss of image information, a new scale space fusion algorithm for large data video images in cloud computing environment is proposed. Scale space theory is introduced. With the shift invariance characteristic of static wavelet transform algorithm for large data video image scale space environment integration of cloud computing, image fusion to lifting wavelet decomposition, obtain low-frequency subspace under different scale coefficients and high frequency sub-band coefficient. The fusion scheme of low frequency sub-band coefficients and high-frequency sub-band coefficients is given to obtain the lifting static wavelet transform coefficients of fused images. The final fused image is obtained by lifting the static wavelet transform. From the test, the fusion effect of subjective and objective two aspects of the proposed algorithm. The results show that the proposed algorithm of subjective good fusion effect evaluation of fusion image by objective evaluation index, found the quality of image clarity, fusion algorithm is good, without loss of image information.