We propose a new image quality degradation assessment method based on the dual-tree complex discrete wavelet transform (DT-CDWT) for evaluating the image quality of watermarked images. The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are widely used to evaluate image quality degradation resulting from embedding a digital watermark. The majority of digital image watermarking methods embed a digital watermark in the spatial or frequency domain of an original image. They evaluate image quality degradation using only the spatial domain in spite of the fact that the majority of digital image watermarking methods embed a digital watermark in the spatial or frequency domain. As a result, they do not always fairly evaluate the image quality degradation. Therefore, our method evaluates image quality degradation of the watermarked images using features in the spatial and frequency domains. To extract the features, we defined three indices: 1-norm estimation using bit-planes in the spatial domain, the sharpness, and 1-norm estimation based on the DT-CDWT domains. We describe our image quality assessment method in detail and present experimental results demonstrating that there is a strong positive correlation between the result obtained by our method and a subjective evaluation, in comparison with PSNR and SSIM.
Digital Image Watermarking Scheme Using Discrete Wavelet Transform Domain, Quantization, and Genetic Algorithm
