Halftone image watermarking via optimization

Guo, Yuanfang; Au, Oscar C.; Zhou, Jiantao; Tang, Ketan; Fan, Xiaopeng

doi:10.1016/j.image.2015.12.002

Cited by 10 publications

(21 citation statements)

References 31 publications

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“…After printing, HP ScanJet G2410 is employed for scanning Y 1 and Y 2 with a resolution of 1200 pixel-perinch(PPI). Before the XNOR decoding operation is performed, a series of preprocessing steps [32] including rotation, resizing and 1-bit quantization are performed with the help of Adobe Photoshop CS2, to reverse the print-and-scan distortions. As Fig.…”

Section: E Discussion Of Robustnessmentioning

confidence: 99%

“…Since the size of the possible solutions set increases exponentially as the image size increases, brute force also cannot be applied. Fortunately, by applying a similar optimization method as in [32], we can manage to find a relaxed optimal solution to Eq. 50 as follows.…”

Section: Content Aware Double-sided Embedding Error Diffusionmentioning

confidence: 99%

“…With CaDEED-N&I's parameters determined, CaDEED-EC and CaDEED-N&I are compared to the classical and latest previous EDHVW methods, DHCED [34], DHDCED [38] and DEED(L-2) [32].…”

Section: Comparison Testmentioning

confidence: 99%

“…Similar to [32], the traditional measurements Peak Signalto-Noise Ratio (PSNR) and CDR are employed to measure the performances of the EDHVW methods. Figs.…”

Section: Comparison Testmentioning

confidence: 99%

“…To better illustrate the superiority of CaDEED-N&I, since complex regions in a image can tolerate more noise than the flat regions, we modify the PSNR measurement in [32] to noise tolerant PSNR (NT-PSNR), which is defined in Eq. (67).…”

Section: Comparison Testmentioning

confidence: 99%

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Halftone Image Watermarking by Content Aware Double-Sided Embedding Error Diffusion

Guo

Au²,

Wang

et al. 2018

IEEE Trans. on Image Process.

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In this paper, we carry out a performance analysis from a probabilistic perspective to introduce the error diffusion-based halftone visual watermarking (EDHVW) methods' expected performances and limitations. Then, we propose a new general EDHVW method, content aware double-sided embedding error diffusion (CaDEED), via considering the expected watermark decoding performance with specific content of the cover images and watermark, different noise tolerance abilities of various cover image content, and the different importance levels of every pixel (when being perceived) in the secret pattern (watermark). To demonstrate the effectiveness of CaDEED, we propose CaDEED with expectation constraint (CaDEED-EC) and CaDEED-noise visibility function (NVF) and importance factor (IF) (CaDEED-N&I). Specifically, we build CaDEED-EC by only considering the expected performances of specific cover images and watermark. By adopting the NVF and proposing the IF to assign weights to every embedding location and watermark pixel, respectively, we build the specific method CaDEED-N&I. In the experiments, we select the optimal parameters for NVF and IF via extensive experiments. In both the numerical and visual comparisons, the experimental results demonstrate the superiority of our proposed work.

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Section: E Discussion Of Robustnessmentioning

confidence: 99%

Section: Content Aware Double-sided Embedding Error Diffusionmentioning

confidence: 99%

“…With CaDEED-N&I's parameters determined, CaDEED-EC and CaDEED-N&I are compared to the classical and latest previous EDHVW methods, DHCED [34], DHDCED [38] and DEED(L-2) [32].…”

Section: Comparison Testmentioning

confidence: 99%

“…Similar to [32], the traditional measurements Peak Signalto-Noise Ratio (PSNR) and CDR are employed to measure the performances of the EDHVW methods. Figs.…”

Section: Comparison Testmentioning

confidence: 99%

Section: Comparison Testmentioning

confidence: 99%

See 3 more Smart Citations