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In this paper, a new no-reference image quality metric is proposed to estimate the quality of watermarked images automatically based on combining objective metrics using neural network. The aim is to predict the subjective quality scores, known as the mean opinion score (MOS) obtained from human observers. In practice, our metric consists of three stages: first, filtering process is applied to watermarked...
A new no-reference image quality metric is proposed to estimate the quality of watermarked images automatically based on fuzzy neural network. The aim is to use fuzzy neural network to learn the highly nonlinear relationship between the fuzzy similarity measures and the subjective quality rating, known as the mean opinion score (MOS) obtained from human viewers. In fact, our metric consists of four...
In this paper, we propose new watermarking method for image copyright protection in spatial domain based on fuzzy image segmentation technique. The fuzzy image approach is employed to determine appropriate locations to hiding watermark by identifying the features map (edges regions) which are less sensitive to the human visual system. Our method optimizes robustness and imperceptibility which are...
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