平均梯度 Resources

Showing items tagged with "平均梯度"

To objectively and quantitatively evaluate the performance of various fusion methods in multi-focus image fusion, this study analyzes images based on their statistical characteristics. Without reference standard images, four key parameters are selected for comprehensive assessment: average gradient (sharpness), spatial frequency, information entropy, and standard deviation, which collectively measure fusion method performance and can be implemented through computational algorithms.

MATLAB 235 views Tagged

This is a comprehensive collection of 13 image fusion performance metrics gathered from online sources, including Average Gradient, Edge Intensity, Information Entropy, Gray Mean Value, Standard Deviation (Mean Square Error MSE), Root Mean Square Error, Peak Signal-to-Noise Ratio (PSNR), Spatial Frequency (SF), Image Definition, Mutual Information (MI), Structural Similarity (SSIM), Cross Entropy, and Relative Standard Deviation. Let's share and discuss implementation approaches together!

MATLAB 226 views Tagged

Image quality assessment using entropy, average gradient, edge strength, variance, and other metrics with implementation insights

MATLAB 199 views Tagged