title of on the implementation of a information hiding design based on saliency map a.basu, t. s....
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Title of On the Implementation of a Information Hiding Design based on Saliency MapA.Basu, T. S. Das and S. K. Sarkar/ Jadavpur University/ Kolkata/ India/ [email protected], [email protected], [email protected]
Swanirbhar Majumder/NERIST (Deemed University)/ Itanagar/ India/ [email protected]
In this paper, an adaptive spatial domain image watermarking scheme is proposed which embeds watermark information to the uneven bit depth salient image pixels. Watermarked image thus produced has better visual transparency with respect to human visual system (HVS) with high payload capacity. In proposed scheme, salient pixels are determined using the bottom-up Graph-Based Visual Saliency (GBVS) model. Experimental results reveal that proposed scheme has less perceptual error as well as improved robustness than existing spatial domain embedding scheme.
The visual attention model consists of two steps: first forming activation maps on certain feature channels, and then normalizing them in a way which highlights conspicuity and admits combination with other maps. The model is simple and biologically plausible insofar as it is naturally parallelized
The Performance Results with Comparisons: In this paper, a new spatial domain adaptive image watermarking scheme is proposed which embeds watermark information in the least significant bit depth pixels with respect to a well known selective visual attention model GBVS. It is experimentally shown for a significant percentage of images the saliency distribution of pixels remain same even after embedding in multiple bit plane LSB embedding. Experimental result also reveals that the perceptual transparency error due to embedding in proposed scheme is less than that of normal LSB embedding scheme. In the attacked environment, this blind proposed scheme can be easily used to make the method visually more robust.
INTRODUCTION RESULT CONCLUSIONS
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WATERMARK ENCODER & DECODER
Sl.No.
Method TPE PSNRCapacity
(bpp)Salient Watermarking Model1 Sur et. al [6] 14.88x10-5 N.A 0.00172 Our Method 0.0485 42.6287 4Non Salient Watermarking Model
1LSB substitution [7]
N.A 38.3425 3
2 GA[8] N.A 38.3220 33 IP LSB [9] N.A 35.0751 44 Optimal LSB [9] N.A 34.9065 45 PWLC [10] N.A 48.3500 0.68
Sl. Parameter Result1 SNR 32.4235 dB2 MSE 10.05393 PSNR 42.6287 dB4 IF 0.999435 MD 76 AD 2.34187 AVD 0.0431988 NAD 0.0189519 NMSE 0.00057234
10 LMSE 0.05160711 SER 11.05812 KLD 0.8017913 UIQI 0.997914 SSIM 0.955715 MSSIM 0.990416 VSNR 32.206117 VIF 0.823518 PVIF 0.782119 IFC 7.601220 NQM 26.199721 WSNR 37.061322 SC 0.99998623 PQS 3.66233824 TPE 0.0485
Performance analysis results for imperceptibility:
CONTACT:Name: S. MajumderEMAIL: [email protected]