Steerable Pyramid Transform 控向塔型变换
median pyramid transform 中值金字塔变换
Laplacian pyramid transform 拉普拉斯塔式变换
steerable pyramid frame transform 方向金字塔框架变换
Firstly, the source images are decomposed into sub-images at different scales through Laplacian pyramid transform.
首先，通过拉普拉斯金字塔变换将源图像分解为各级分辨率的子图像。
To solve this problem we have implemented the texture progressive transmission with the classic Laplacian pyramid algorithm and the Haar transform algorithm.
为解决这个问题用拉普拉斯金字塔算法和哈尔变换算法实现了纹理递进传输。
The experimental results demonstrate that the MSE (mean square error) reduced by this proposed approach decreases 30% - 60% than that by Laplacian pyramid and discrete wavelet transform approaches.
实验表明该方法融合结果的均方误差比拉普拉斯金字塔算法和小波变换方法降低约30% - 60%。
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