Advances in network communications have necessitated secure local-storage and transmission of multimedia content. In particular, military networks need to securely store sensitive imagery which at a later stage may be...
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Advances in network communications have necessitated secure local-storage and transmission of multimedia content. In particular, military networks need to securely store sensitive imagery which at a later stage may be transmitted over bandwidth-constrained wireless networks. This work investigates compression efficiency of JPEG and JPEG 2000 standards for encrypted images. An encryption technique proposed by Kuo et al. in [4] is employed. The technique scrambles the phase spectrum of an image by addition of the phase of an all-pass pre-filter. The post-filter inverts the encryption process, provided the correct pseudo-random filter coefficients are available at the receiver. Additional benefits of pre/post-filter encryption include the prevention of blocking effects and better robustness to channel noise [4]. Since both JPEG and JPEG 2000 exploit spatial and perceptual redundancies for compression, pre/post-filtered (encrypted) images are susceptible to compression inefficiencies. The PSNR difference between the unencrypted and pre/post-filtered images after decompression is determined for various compression rates. compression efficiency decreases with an increase in compression rate. For JPEG and JPEG 2000 compression rates between 0.5 to 2.5 bpp, the difference in PSNR is negligible. Partial encryption is proposed wherein a subset of image phase coefficients are scrambled. Due to the phase sensitivity of images, even partial scrambling of the phase information results in unintelligible data. The effect of compression on partially encrypted images is observed for various bit-rates. When 25% of image phase coefficients are scrambled, the JPEG and JPEG 2000 compression performance of encrypted images is almost similar to that of unencrypted images for compression rates in the 0.5 to 3.5 bpp range.
A number of methods have been recently proposed in the literature for the encryption of 2-D information using linear optical systems. In particular the double random phase encoding system has received widespread atten...
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A number of methods have been recently proposed in the literature for the encryption of 2-D information using linear optical systems. In particular the double random phase encoding system has received widespread attention. This system uses two Random Phase Keys (RPK) positioned in the input spatial domain and the spatial frequency domain and if these random phases are described by statistically independent white noises then the encrypted image can be shown to be a white noise. Decryption only requires knowledge of the RPK in the frequency domain. The RPK may be implemented using a Spatial Light Modulators (SLM). In this paper we propose and investigate the use of SLMs for secure optical multiplexing. We show that in this case it is possible to encrypt multiple images in parallel and multiplex them for transmission or storage. The signal energy is effectively spread in the spatial frequency domain. As expected the number of images that can be multiplexed together and recovered without loss is proportional to the ratio of the input image and the SLM resolution. Many more images may be multiplexed with some loss in recovery. Furthermore each individual encryption is more robust than traditional double random phase encoding since decryption requires knowledge of both RPK and a lowpass filter in order to despread the spectrum and decrypt the image. Numerical simulations are presented and discussed.
The aim of this research is to develop efficient algorithms for fractal imagecoding, which can be applied in digital image compression, image magnification and image denoising. Fractal imagecoding can provide a high...
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The aim of this research is to develop efficient algorithms for fractal imagecoding, which can be applied in digital image compression, image magnification and image denoising. Fractal imagecoding can provide a highly reconstructed image quality with a high compression ratio, is independent of resolution, and has a fast decoding process. The problem with fractal coding is its high computational complexity in the encoding process. Most of the encoding time is spent finding the best-matched domain block from a large domain pool to represent an input range block with respect to contrast and intensity offset, as well as the isometry transformations. The objectives of this research are to investigate and develop efficient techniques for fractal imagecoding, fractal-based image magnification and denoising. In this thesis, four efficient fractal image-coding algorithms have been proposed. The first algorithm is based on new feature vectors and the property of zero contrast. The proposed feature vectors can provide a better representation of image blocks, and thus result in a more efficient search of the domain block. The second algorithm is an efficient windowing scheme for fractal imagecoding based on the local variances method. In our method, windows covering those domain blocks whose variances are higher than that of the range block are considered according to a mathematical model. The exhaustive search algorithm can obtain the optimal result by searching all the blocks within the domain pool, but this process requires a high computational cost, which limits its practical application. A single kick-out condition is proposed which can avoid a large number of range-domain block matches when finding the best-matched domain block. An efficient method for zero contrast prediction is also proposed, which can determine whether the contrast factor for a domain block is zero or not, and compute the corresponding difference between the range block and the transformed domain b
The proceedings contain 16 papers from the Proceedings of SPIE - mathematics of data/image coding, compression, and encryption VII, with applications. The topics discussed include: autosophy data/image compression and...
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The proceedings contain 16 papers from the Proceedings of SPIE - mathematics of data/image coding, compression, and encryption VII, with applications. The topics discussed include: autosophy data/image compression and encryption;region segmentation techniques for object-based image compression: a review;data compression trade-offs in sensor networks;the relationship between shape under similarly transformations and shape under affine transformations;sparsity prediction and application to a new steganographic technique;phase signature-based image authentication watermark robust to compression and coding;texture-based steganalysis: results for color images;and combined dataencryption and compression using chaos functions.
The proceedings contains 22 papers of SPIE : mathematics of data/image coding, compression, and encryption VI, with applications. The topics discussed include: natural language insensitive short textual string compres...
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The proceedings contains 22 papers of SPIE : mathematics of data/image coding, compression, and encryption VI, with applications. The topics discussed include: natural language insensitive short textual string compression;techniques for region coding in object-based image compression;boundary representation techniques for object-based image compression;meitei coding for subband image compression;standards-compatible compression for automated image recognition in sensor networks and surveillance systems and non-MSE data compression for emitter location for radar pulse trains.
Past research in the field of cryptography has not given much consideration to arithmetic coding as a feasible encryption technique, with studies proving compression-specific arithmetic. coding to be largely unsuitabl...
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ISBN:
(纸本)0819454990
Past research in the field of cryptography has not given much consideration to arithmetic coding as a feasible encryption technique, with studies proving compression-specific arithmetic. coding to be largely unsuitable for encryption. Nevertheless, adaptive modelling, which offers a huge model, variable in structure, and as completely as possible a function of the entire text that has been transmitted since the time the model was initialised, is a suitable candidate for a possible encryption-compression combine. The focus of the work presented in this paper has been to incorporate recent results of chaos theory, proven to be cryptographically secure, into arithmetic coding, to devise a convenient method to make the structure of the model unpredictable and variable in nature, and yet to retain, as far as is possible, statistical harmony, so that compression is possible. A chaos-based adaptive arithmetic coding-encryption technique has been designed, developed and tested and its implementation has been discussed. For typical text files, the proposed encoder gives compression between 67.5% and 70.5%, the zero-order compression suffering by about 6% due to encryption, and is not susceptible to previously carried out attacks on arithmetic coding algorithms.
Multimedia data may be transmitted or stored either according to the classical Shannon information theory or according to the newer Autosophy information theory. Autosophy algorithms combine very high "lossless&q...
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ISBN:
(纸本)0819454990
Multimedia data may be transmitted or stored either according to the classical Shannon information theory or according to the newer Autosophy information theory. Autosophy algorithms combine very high "lossless" data and image compression with virtually unbreakable "codebook" encryption. Shannon's theory treats all data items as "quantities", which are converted into binary digits (bit), for transmission in meaningless bit streams. Only "lossy" data compression is possible. A new "Autosophy" theory was developed by Klaus Holtz in 1974 to explain the functioning of natural self-assembling structures, such as chemical crystals or living trees. The same processes can also be used for growing self-assembling data structures, which grow like data crystals or data trees in electronic memories. This provides true mathematical learning algorithms, according to a new Autosophy information theory. Information in essence is only that which can be perceived and which is not already known by the receiver. The transmission bit rates are dependent on the data content only. applications already include the V.42bis compression standard in modems, the gif and tif formats for lossless image compression, and Autosophy Internet television. A new 64bit data format could make all future communications compatible and solve the Internet's Quality of Service (QoS) problems.
The proceedings contain 27 papers from the conference on mathematics of data/image coding, compression, and encryption iv, with applications. The topics discussed include: improving wireless video communication withou...
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The proceedings contain 27 papers from the conference on mathematics of data/image coding, compression, and encryption iv, with applications. The topics discussed include: improving wireless video communication without feedback information;analysis of digital chaotic optical signals;lossless data compression in space amplifications;security analysis of public key watermarking schemes;dataencryption scheme with arithmetic coding and robust digital watermarking using random casting method.
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