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Compressed sensing (CS), due to its superior performances that very few amounts of coefficients are capable of reconstructing the image with reasonable quality, is an effective means in data compression in recent years. For the transmission of image compressed with CS, due to the channel errors that may be experienced, data protection would be required. We employ multiple description coding (MDC)...
Visual cryptography is an effective means for ownership protection of multimedia contents. Due to the massive amount of multimedia contents, compression is an inevitable part before transmission over channels. Recently, compressed sensing has attracted much attention with its superior performance in data compression. With compressed sensing, few amounts of coefficients are able to obtain reconstructed...
Compressive sensing is a potential technology for lossy image compression. With a given quality, we may represent an image with a few significant coefficients in the transform domain. When the number of the significant coefficients is much less than the number of the pixels, the assumption of sparse representation is satisfied. Based on the sparse modeling theories, an image could be sensed with a...
Compressed sensing has attracted much attention in researches due to its new thoughts and superior performances in data compression. For the delivery of compressed information, because it is vulnerable to channel errors during transmission, error control for compressed information has long been a practical topic for researches and applications. In this paper, we aim at the error control of compressed...
Compressive sensing is a signal processing technique that takes advantage of signal sparseness in some domain. To use compressive sensing, a domain in which the signal is represented as a few significant coefficients should be defined. If the proper domain is identified as a set of basis vectors, the coefficients are the projections of the signal on the basis vectors. This is typically a transformation...
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