Hybrid Sharpening Transformation Approach for Multifocus Image Fusion Using Medical and Nonmedical Images
Table 1
Measurements to evaluate the experimental results.
Quality metrics
Description
Formula
What value to look for best fusion
Reference
RMSE
The RMSE is generally used to calculate the difference among the true image and resultant image by directly calculating the variations in pixel values. RMSE is highly indicating the spectral quality of the resultant image.
PSNR is one of the significant metrics and most commonly used in fusion. PSNR is specifically used for the measurement of spatial quality in the image. The computation is performed by the value of grey levels divided by the identical pixels in the true and the resultant images.
The CORR is a quantitative metric that demonstrates the correlation among the true image and the resultant image. When the true and resultant images look the same, the value will be near to one. If the true and resultant images are dissimilar, then the value will be near zero.
ERGAS is used to calculate the quality of the resultant image in terms of the normalization average error of each channel (band) of the processed image.