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• W2899504191 abstract "The digital medical workflow faces many circumstances in which the images can be manipulated during viewing, extracting and exchanging. Reversible and imperceptible watermarking approaches have the potential to enhance trust within the medical imaging pipeline through ensuring the authenticity and integrity of the images to confirm that the changes can be detected and tracked. This study concentrates on the imperceptibility issue. Unlike reversibility, for which an objective assessment can be easily made, imperceptibility is a factor of human cognition that needs to be evaluated within the human context. By defining a perceptual boundary of detecting the modification, this study enables the formation of objective guidelines for the method of data encoding and level of image/pixel modification that translates to a specific watermark magnitude. This study implements a relative Visual Grading Analysis (VGA) evaluation of 117 brain MR images (8 original and 109 watermarked), modified by varying techniques and magnitude of image/pixel modification to determine where this perceptual boundary exists and relate the point at which change becomes noticeable to the objective measures of the image fidelity evaluation. The outcomes of the visual assessment were linked to the images Peak Signal to Noise Ratio (PSNR) values, thereby identifying the visual degradation threshold. The results suggest that, for watermarking applications, if a watermark is applied to the 512x512 pixel (16 bpp grayscale) images used in the study, a subsequent assessment of PSNR=82dB or greater would mean that there would be no reason to suspect that the watermark would be visually detectable. Keywords: Medical imaging; DICOM; Reversible Watermarking; Imperceptibility; Image Quality; Visual Grading Analysis." @default.
• W2899504191 created "2018-11-09" @default.
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• W2899504191 date "2019-02-01" @default.
• W2899504191 modified "2023-10-03" @default.
• W2899504191 title "Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images" @default.
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• W2899504191 doi "https://doi.org/10.1016/j.image.2018.10.007" @default.
• W2899504191 hasPublicationYear "2019" @default.
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