Weighted Fuzzy-Based PSNR for Watermarking
This addresses the need for more accurate quality evaluation in image watermarking, though it appears incremental as it modifies an existing metric rather than introducing a new paradigm.
The paper tackles the problem of conventional visual quality metrics like PSNR not aligning with the human visual system in watermarking applications, proposing a weighted fuzzy-based criterion that assigns larger weights to essential image parts based on HVS, with experiments showing considerable improvements over standard PSNR.
One of the problems of conventional visual quality evaluation criteria such as PSNR and MSE is the lack of appropriate standards based on the human visual system (HVS). They are calculated based on the difference of the corresponding pixels in the original and manipulated image. Hence, they practically do not provide a correct understanding of the image quality. Watermarking is an image processing application in which the image's visual quality is an essential criterion for its evaluation. Watermarking requires a criterion based on the HVS that provides more accurate values than conventional measures such as PSNR. This paper proposes a weighted fuzzy-based criterion that tries to find essential parts of an image based on the HVS. Then these parts will have larger weights in computing the final value of PSNR. We compare our results against standard PSNR, and our experiments show considerable consequences.