KEYWORDS: Data hiding, Near field diffraction, Transform theory, Digital watermarking, Modulation, Steganography, Multimedia, Diffraction gratings, Matrices, Chaos
In this paper, we present a new copyright information hide method for digital images in Moiré fringe formats. The
copyright information is embedded into the protected image and the detecting image based on Fresnel phase matrix.
Firstly, using Fresnel diffraction transform, the random phase matrix of copyright information is generated. Then,
according to Moiré fringe principle, the protected image and the detecting image are modulated respectively based on the
random phase matrix, and the copyright information is embedded into them. When the protected image and the detecting
image are overlapped, the copyright information can reappear. Experiment results show that our method has good
concealment performance, and is a new way for copyright protection.
This paper describes a novel approach to multisensor image fusion using a new mathematical transform: the curvelet
transform. The transform has shown promising results over wavelet transform for 2-D signals. Wavelets, though well
suited to point singularities have limitation with orientation selectivity, and therefore, do not represent two-dimensional
singularities (e.g. smooth curves) effectively. Curvelet improves wavelet by incorporating a directional component. This
paper employs the curvelet transform for image fusion. Based on the local energy of direction curvelet subbands, we give
the definition of local band-limited contrast and use it as one of the fusion rules. The local band-limited contrast can
reflect the response of local image features in human visual system truly. When used to image fusion in noiseless
circumstance, it is effective. But in noisy circumstance, it is not always robust. According to the different characteristics
between image features and noise, the local directional energy entropy is proposed. It can distinguish the noise and local
image features. In this paper, the combination of local band-limited contrast and local directional energy entropy is used
as image fusion. Experimental results show that it is robust in noisy and noiseless image fusion system.
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