Weighted Fuzzy-Based PSNR for Watermarking

TL;DR

This paper introduces a weighted fuzzy-based PSNR criterion that aligns better with human visual perception for evaluating image quality in watermarking, improving upon traditional PSNR measures.

Contribution

It proposes a novel weighted fuzzy-based PSNR that emphasizes perceptually important image regions based on the HVS, enhancing watermarking quality assessment.

Findings

The proposed method outperforms standard PSNR in correlating with perceived image quality.

Experiments demonstrate significant improvements in watermarking evaluation accuracy.

The approach effectively identifies and weights critical image regions based on HVS.

Abstract

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.