KEYWORDS: High dynamic range imaging, Visualization, Image compression, Visual process modeling, Visual system, Distortion, High dynamic range image sensors, Light sources and illumination, Image processing, Video
High Dynamic Range (HDR) images capture the full range of luminance present in real world scenes, and unlike
Low Dynamic Range (LDR) images, can simultaneously contain detailed information in the deepest of shadows
and the brightest of light sources. In order to render HDR image on LDR displayers, it is often necessary to create
LDR depictions of HDR images at the cost of contrast information loss. To reduce the loss, this paper enables
to render HDRI (High Dynamic Range Image) with multiple low-bit images periodically. From the viewpoint of
a human, the pixel value is fractural. It does not adjust the tones but can reconstruct HDR images.
This paper presents a collusion attack to a fingerprinting scheme. To this end, it creates a pirated copy by adaptively separating the traitors into groups and then applying either LCCA or majority attack. Since the pirated copy discloses no watermarks of the traitors, the fingerprinting scheme fails to trace the traitors. Our experiments demonstrate that the attack is effective.
This paper presents a pay-video scheme that manages video stream, key stream and payment stream efficiently. In our scheme, the owner segments a video into fragments and encrypts them with independent keys. The keys are generated with a novel concept called as hash interval, where each hash interval discloses a range of numbers without disclosing any information on numbers outside of the range. The video fragments are then broadcast on one or more channels. A buyer can purchase the keys to decrypt any fragments and, within each fragment, any desired quality level. The accompanying payment protocol is integrated with the key management protocol seamlessly and hence the computation cost is very low.
This paper describes an attack on semi-fragile image authentication schemes proposed in papers. In this attack, the adversary manipulates an authentic image and queries a verifier with the corrupted image. According to the answers from the verifier, the adversary can disclose the secret relationship graphs used to produce a signature. With the disclosed relationship graphs, the adversary can impersonate an innocent person to forge authentic images easily. A
countermeasure to this attack is to change scheme parameters with the relationship edges so that the relationship graphs reconstructed by the attacker are different from the original one. Sequentially, the attacker is hard to forge an authentic image without correct relationship graphs.
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