Image Quality Assessment for Performance Evaluation of Focus Measure Operators
This work addresses the problem of selecting effective focus measures for image quality assessment, but it is incremental as it compares existing methods without introducing new ones.
The paper evaluated eight focus measure operators using statistical metrics and full-reference image quality assessment, finding that the LAPD method performed better than the others under typical imaging conditions.
This paper presents the performance evaluation of eight focus measure operators namely Image CURV (Curvature), GRAE (Gradient Energy), HISE (Histogram Entropy), LAPM (Modified Laplacian), LAPV (Variance of Laplacian), LAPD (Diagonal Laplacian), LAP3 (Laplacian in 3D Window) and WAVS (Sum of Wavelet Coefficients). Statistical matrics such as MSE (Mean Squared Error), PNSR (Peak Signal to Noise Ratio), SC (Structural Content), NCC (Normalized Cross Correlation), MD (Maximum Difference) and NAE (Normalized Absolute Error) are used to evaluate stated focus measures in this research. . FR (Full Reference) method of the image quality assessment is utilized in this paper. Results indicate that LAPD method is comparatively better than other seven focus operators at typical imaging conditions.