Description: 基于视觉特性的多尺度对比度塔图像融合及性能评价-Based on the visual characteristics of Multiscale Contrast Pyramid Image Fusion and Its Performance Evaluation Platform: |
Size: 98304 |
Author:威尔浮 |
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Description: 给出了一种基于小波变换的图像融合方法，对小波分解后的低频分量通过度量其图像块空间频率和对比度来确定融合图
像的低频分量，对分解后得到的高频分量，选择高频系数时，基于绝对值最大的原则，并对选择结果进行一致性验证，最后重构得
到融合图像。从仿真结果可以看出，给出的方法很好地保留了多幅原图像的有用信息，融合图像清晰度和对比度都较好，是一种有
效的图像融合算法-This paper presents a wavelet-based image fusion method, after the wavelet decomposition of the low frequency components through the measurement of its image block spatial frequency and contrast to determine the integration of low-frequency component images of decomposition after the high-frequency component, select the high-frequency coefficient and, based on the principle of the absolute value of the largest, and choose to verify consistency of results, and finally remodeling be fused image. From the simulation results can be seen that the method gives a good number of the original image to retain the useful information, integration of image sharpness and contrast are better, is an effective image fusion algorithm Platform: |
Size: 169984 |
Author:wd |
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Description: 本程序实现了基于对比金字塔的图像融合算法，效果还不错，可以参考一下。-This procedure contrast pyramid based on the implementation of image fusion algorithms, the effect was not bad, you can reference. Platform: |
Size: 1024 |
Author:WSH |
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Description: 种基于图像质量因子的图像融合客观评价方法。该方法利用熵加权和均方根图像融合质量因子对融合图像与源图像间的相关性、 亮度失真和对比度失真进行综合评价,因而在不同融合方法和不同源图像的条件下,可获得标准的评估统计量。采用加权平均、 拉普拉斯塔形分解及基于小波变换的图像融合法为例,通过对多传感器图像进行融合评价实验,证明了该方法的有效性和鲁棒性。-Factor based on image quality of the image fusion method of objective evaluation. This method is the use of entropy and the weighted root-mean-square image fusion quality factor of the fused image and the source of the correlation between image brightness and contrast distortion of a comprehensive evaluation of distortion, which fusion in different ways and different sources of image conditions, the availability of standards assessment statistics. Using the weighted average, Laplacian pyramid and wavelet transform-based image fusion method as an example of multi-sensor image fusion evaluation experiments show that the method is effective and robust. Platform: |
Size: 730112 |
Author:storm |
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Description: 图像融合。通过小波变换对图像进行分解，滤波，然后图像重构，对比前后图像的变化-Image fusion. Through the wavelet transform image decomposition, filtering, and image reconstruction, image contrast before and after the change Platform: |
Size: 1024 |
Author:yanhaifeixue |
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Description: 文中的方法是把图像分块，小波分解得到低频分量、高频分量，然后计算每一块的对比度，把图像块划分为清晰块、模糊块，把清晰块和模糊块相邻的区域定义为边界区域，融合时，直接选取清晰块作为融合后的相应块，对于边界区域，在小波分解的基础上采用基于对比度的像素选取的方法进行处理。-Paper, the method is to image segmentation, wavelet decomposition are low frequency, high frequency components, then calculate the contrast of each piece, the image block is divided into clear blocks, fuzzy block, to clear blocks and fuzzy block is defined as the border region adjacent to area, integration time, a clear block directly select the corresponding block as a fusion, for the border region, the wavelet decomposition on the basis of the pixel-based contrast method selected for processing. Platform: |
Size: 338944 |
Author:许国柱 |
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Description: 基于对比度的多分辨图像融合和CMAC的图像融合快速算法-Multi-resolution image based on contrast fusion and fast algorithm for image fusion CMAC Platform: |
Size: 678912 |
Author:烦渴 |
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Description: 本文阐述了基于主元分析的拉普拉斯金字塔图像融合的原理和方法:首先对原图像分别进行拉普拉斯
金字塔分解,然后分别对高频部分采用主元分析（PCA）法融合,对低频部分采用平均梯度法进行融合,最后对
拉普拉斯金字塔做反变换得到最终的融合图像。通过对可见光与红外图像的融合，以及对不同焦距图像融合
的结果分析，该算法比单纯的PCA和拉普拉斯图像融合能得到具有更多有用信息的高对比度的融合图像-In this paper, principal component analysis based on the Laplacian pyramid image fusion of theory and method: First, the original image, respectively Laplacian pyramid decomposition, and then were used for high-frequency part of the principal component analysis (PCA) fusion method for The average gradient method using low-frequency part of the fusion, the last of the Laplacian pyramid to do the inverse transform to get the final fused image. Through the integration of visual and infrared images, as well as the results of image fusion of different focal length of the algorithm than the simple PCA and Laplacian image fusion can get more useful information with the integration of high-contrast images Platform: |
Size: 81920 |
Author:redxuech |
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Description: A fusion method for visible and infrared images based on contrast
pyramid with teaching learning based optimization Platform: |
Size: 2316288 |
Author:刘国华 |
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Description: Abstract—To overcome the difficulties of sub-band coefficients
selection in multiscale transform domain-based image fusion
and solve the problem of block effects suffered by spatial
domain-based image fusion, this paper presents a novel hybrid
multifocus image fusion method. First, the source multifocus
images are decomposed using the nonsubsampled contourlet
transform (NSCT). The low-frequency sub-band coefficients are
fused by the sum-modified-Laplacian-based local visual contrast,
whereas the high-frequency sub-band coefficients are fused by
the local Log-Gabor energy. The initial fused image is subsequently
reconstructed based on the inverse NSCT with the fused
coefficients. Second, after analyzing the similarity between the
previous fused image and the source images, the initial focus
area detection map is obtained, which is used for achieving the
decision map obtained by employing a mathematical morphology
postprocessing technique. Finally, based on the decision Platform: |
Size: 2480128 |
Author:senthil |
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Description: There has been a growing interest in image fusion
technologies, but how to objectively uate the quality of fused
images has not been fully understood. Here, we propose a method
for objective quality assessment of multiexposure multifocus
image fusion based on the uation of three key factors of
fused image quality: 1) contrast preservation 2) sharpness and
3) structure preservation. Subjective-There has been a growing interest in image fusion
technologies, but how to objectively uate the quality of fused
images has not been fully understood. Here, we propose a method
for objective quality assessment of multiexposure multifocus
image fusion based on the uation of three key factors of
fused image quality: 1) contrast preservation 2) sharpness and
3) structure preservation. Subjective Platform: |
Size: 9906176 |
Author:widy |
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Description: There are both multiple-scale and single scale exposure fusion
schemes. Three quality measures of proper exposure, good contrast,
and high saturation were used to determine how much a
given pixel will contribute to the final synthesized image(hat transitions between regions where different images contribute more heavily are difficult to perceive.The exposure fusion scheme was based on an observation that gradient magnitude becomes larger when a pixel gets a state of better exposed and it) Platform: |
Size: 406528 |
Author:song86 |
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Search - Contrast-based fusion