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。
Firstly, the source images are decomposed into sub-images at different scales through Laplacian pyramid transform.
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。
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。
To solve this problem we have implemented the texture progressive transmission with the classic Laplacian pyramid.
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%。
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.
利用拉普拉斯金字塔分解算法对图像进行多分辨率分析，对分解后的图像采用基于区域特征量测的方法进行融合。
This paper adopts a Laplacian Pyramidal decomposition method to analyze two images, And the decomposed images are fused with the method based on regional features measurement.
重点分析了高斯金字塔、拉普拉斯金字塔、对比度金字塔和小波金字塔在图像分解与重构中的原理及其融合算法。
The principle of image decomposition and reconstruction based on Gauss-pyramid, Laplacian-pyramid, contrast-pyramid and wavelet-pyramid is emphatically analyzed, as well as the fusion algorithm.
对于边界区域，建立了基于对比度的像素选取方法进行融合处理。实验对比结果表明，该方法明显优于拉普拉斯金字塔融合算法和离散小波变换融合算法。
The part between clear part and blurring one is fused by the choice of the corresponding pixel based on the contrast. The experiments show that the proposed method outperforms them…
对于边界区域，建立了基于对比度的像素选取方法进行融合处理。实验对比结果表明，该方法明显优于拉普拉斯金字塔融合算法和离散小波变换融合算法。
The part between clear part and blurring one is fused by the choice of the corresponding pixel based on the contrast. The experiments show that the proposed method outperforms them…
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