An Experimental Study into Objective Quality Assessment of Watermarked Images

In this paper, we study the quality assessment of watermarked and attacked images using extensive experiments and related analysis. The process of watermarking usually leads to loss of visual quality and therefore it is crucial to estimate the extent of quality degradation and its perceived impact. To this end, we have analyzed the performance of 4 image quality assessment (IQA) metrics – Structural Similarity Index (SSIM), Singular Value Decomposition Metric (M-SVD), Image Quality Score (IQS) and PSNR on watermarked and attacked images. The watermarked images are obtained by using three different schemes viz., (1) DCT based random number sequence watermarking, (2) DWT based random number sequence watermarking and (3) RBF Neural Network based watermarking. The signed images are attacked by using five different image processing operations. The similarity parameter SIM (X, X*) is also computed for signed and attacked images after extracting watermarks and its computed values are correlated with other results. We observe that the metrics behave identically in case of all the three watermarking schemes. An important conclusion of our study is that PSNR is not a suitable metric for IQA as it does not correlate well with the human visual system’s (HVS) perception. It is also found that th