\alpha,\beta,\gamma分别代表了不同特征在SSIM衡量中的占比,当都为1时,有: $$ SSIM(x,y) = \frac{(2\mu_x\mu_y+C_1)(2\sigma_{xy}+C_2)}{(\mu_x^2+\mu_y^2+C_1)(\sigma_x^2+\sigma_y^2+C_2)} $$ SSIM的实践常用方法MSSIM (Mean SSIM) 实际上,当需要衡量一整张图片的质量,...
结构相似指标（SSIM）是一种衡量图片失真程度或相似度的感知模型，它与MSE（均方误差）和PSNR（峰值信噪比）不同，更符合人眼的直观感受。在MSE下，不同SSIM值会呈现出不同的图片效果。SSIM值范围在[-1, 1]之间，具有对称性、边界性以及唯一最大性。当且仅当x和y相等时，SSIM等于1。SSIM主要考虑图片...
penalizes results that are not perceptually similar to labels by defining a distance measure between activation maps of a pre-trained network 其中,\Phi _i表示预训练网络第i层的 activation map ,对应于 relu1_1, relu2_1, relu3 1, relu41 and relu5_1 of the VGG-19 network pre-trained on...
In the objective assessment, the structural similarity index measure (SSIM) generated various SSIM index values based on these parameters. After the IQA assessment, it is found that the average percentage similarly obtained from the traditional seam carving technique is 64.03% while in the case of ...
If people tend to preferentially encounter ingroup members, then surprisingly even an unbiased estimator of sample variance will yield an outgroup homogeneity effect, assuming the dependent measure is the probability that the ingroup has higher variance than the out-group. This arises due to the ...
. A widely used drought index, the Standardized Precipitation-Evapotranspiration Index (SPEI; Vicente-Serrano et al., 2010, Beguería et al., 2014) was applied in order to measure drought severity. SPEI integrates both the multi-scalar character of the standardized precipitation index (SPI) and ...
Image structure subspaceSubspace learningSSIM kernelSSIM indexStructural similarityLiterature has shown that Mean Squared Error is not a promising measure for image fidelity and similarity assessment, and Structural Similarity Index (SSIM) can properly handle this aspect. The......
], namely, mean absolute error (MAE), mean squared error (MSE), normalized mean squared error (NMSE), peak-signal-to-noise ratio (PSNR), and the structural similarity index measure (SSIM) are used to quantitatively evaluate different methods. These metrics are outlined below:...
To thoroughly assess the effectiveness of the proposed image inpainting framework, this study utilizes two commonly employed metrics in the field of image inpainting: pixel similarity and structural similarity index measure (SSIM). These metrics are pivotal for evaluating the accuracy with which the in...
Central to our sequential loss function is the structural similarity index measure (SSIM). The SSIM measures nonstructural distortions (luminance and contrast changes) as well as structural changes, by computing similarity metrics between local image patches taken from the same location across three main...