Psychovisual approach to digital picture watermarking

Delaigle, Jean-François; Vleeschouwer, Christophe De; Macq, Benoı̂t

doi:10.1117/1.482616

Cited by 23 publications

(8 citation statements)

References 15 publications

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“…A variety of HVS models developed from image compression and quality assessment [3,4,5], have been applied to the design and optimization of digital watermarking since the late 1990's [6,7]. Generally, most of HVS models create a perceptual mask or a JND mask using a multi-channel visual decomposition suggested by psychophysics experiments.…”

Section: Introductionmentioning

confidence: 99%

Improved Content-Based Watermarking Using Scale-Invariant Feature Points

Hancock

Zheng

et al. 2011

Image Analysis and Processing – ICIAP 2011

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Abstract. For most HVS(Human Visual System) perceptual models, the JND(Just Noticeable Difference) values in highly-textured image regions have little difference with those in edge areas. This is not consistent with the characteristics of human vision. In this paper, an improved method is introduced to give a better content-based perceptual mask than traditional ones using the arrangement of scale-invariant feature points. It could decrease the JND values in edge areas of those traditional masks so that they have an obvious difference with values in highly textured areas. Experimental results show the advantages of this improved approach visually, and the enhancement of the invisibility of watermarks.

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Section: Introductionmentioning

confidence: 99%

Improved Content-Based Watermarking Using Scale-Invariant Feature Points

Hancock

Zheng

et al. 2011

Image Analysis and Processing – ICIAP 2011

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“…This algorithm is described in [25], and is similar to the authors' earlier work in [71]. An original image, X, is first passed through a Gabor filter bank [72]; other perceptually tuned filter banks could be used.…”

Section: Sub-band Watermarkingmentioning

confidence: 99%

“…The development of the TEL is further described in [2,23]. A third model, which is based on contrast masking is described in [25,26].…”

Section: Just-noticeable Difference Thresholdsmentioning

confidence: 99%

Perceptual watermarks for digital images and video

Podilchuk²,

1999

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The growth of new imaging technologies has created a need for techniques that can be used for copyright protection of digital images. Copyright protection involves the authentication of image content and/or ownership and can be used to identify illegal copies of a (possibly forged) image. One approach for copyright protection is to introduce an invisible signal known as a digital watermark in the image.In this paper, we describe digital image watermarking techniques, known as perceptually based watermarks, that are designed to exploit aspects of the human visual system. In the most general sense, any watermarking technique that attempts to incorporate an invisible mark into an image is perceptually based. However, in order to provide transparency (invisibility of the watermark) and robustness to attack, more sophisticated use of perceptual information in the watermarking process is required. Several techniques have been introduced that incorporate a simple visual model in the marking procedure. Such techniques usually take advantage of frequency selectivity and weighing to provide some perceptual criteria in the watermarking process. Even more elaborate visual models are used to develop schemes that not only take advantage of frequency characteristics but also adapt to the local image characteristics, providing extremely robust as well as transparent schemes. We present examples from each category -from the simple schemes that guarantee transparency to the more elaborate schemes that use visual models to provide robustness as well as transparency.3

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“…The amount of deterioration caused by the transmitted images is determined by the embedded fragile watermark. Delaigle et al [11] proposed a unique watermarking scheme based on the Human Visual System. Binary m-sequences were produced and then modulated on a random carrier.…”

Section: Introductionmentioning

confidence: 99%

Variance Based Block Selective Digital Image Watermarking Scheme

Sharma¹

2016

IOSR

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Psychovisual approach to digital picture watermarking

Cited by 23 publications

References 15 publications

Improved Content-Based Watermarking Using Scale-Invariant Feature Points

Improved Content-Based Watermarking Using Scale-Invariant Feature Points

Perceptual watermarks for digital images and video

Variance Based Block Selective Digital Image Watermarking Scheme

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