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An approach for the combined image authentication and compression of color images by making use of digital watermarking and data hiding framework is presented. The digital watermark is comprised of two components that include a soft-authenticator watermark for authentication and tamper assessment of the given image, and a chrominance watermark employed to improve the efficiency of compression.

A study of the performance analysis and design of robust watermark embedding strategies in the presence of block-based lossy compression is presented. A novel hybrid watermarking algorithm that exploits the best of robust digital watermarking techniques is developed for greater resilience to JPEG compression through analytical comparisons.

Hardware implementation aspects of the digital watermarking problem are investigated and discussed.

Communication theory principles of diversity and channel estimation are used with the aim of strengthening the robustness of digital watermarking procedures.

Robust classification of blurred imagery using two novel approaches that involve data fusion is discussed. The problem addressed is called blind image fusion and techniques used the nonnegativity and support constraints recursive inverse filtering algorithm for blind image restoration and the Markov random field-based fusion method for classification. Simulations results on synthetic and real photographic data show the potential the approaches have.

A general framework based on Lyapunov's direct technique for studying the behavior of nonlinear blind deconvolution algorithms was analyzed. The framework was applied to the blind deconvolution scheme such as the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) algorithm for blind image restoration. The method was effective in generating adequate conditions for the distinct global convergence of an iterative blind deconvolution algorithm and offered a unique solution to the NAS-RIF algorithm.

A study was conducted on a novel blind deconvolution approach for the restoration of linearly degraded images using recursive filtering. The method is applicable to situations in which the scene consists of a finite support object against a uniformly black, grey or white background. The findings indicate that the new technique is more reliable and has a faster convergence than existing nonparametric finite support blind deconvolution methods.

Visual sensor networks (VSNs) provide surveillance images/video which must be protected from eavesdropping and tampering en route to the base station. In the spirit of sensor networks, we propose a novel paradigm for securing privacy and confidentiality in a distributed manner. Our paradigm is based on the control of dynamical systems, which we show is well suited for VSNs due to its low complexity in terms of processing and communication, while achieving robustness to both unintentional noise and intentional attacks as long as a small subset of nodes are affected. We also present a low complexity algorithm called TANGRAM to demonstrate the feasibility of applying our novel paradigm to VSNs. We present and discuss simulation results of TANGRAM.

Traditionally, data hiding and compression have had contradictory goals. The former problem adds perceptually irrelevant information in order to embed data, while the latter removes this irrelevancy and redundancy to reduce storage requirements. In this paper, we use data hiding to help improve signal compression. We take an unconventional approach and consider "piggy-backing" the color information on the luminance component of an image for improved color image coding. Our new technique essentially transforms a given color image into the YIQ color space where the chrominance information is subsampled and embedded in the wavelet domain of the luminance component. Our technique can be used as preprocessing to improve the performance of popular image compression schemes such as SPIHT that are optimized for grayscale image compression. Simulation results demonstrate the superior performance of the proposed technique in comparison to JPEG and straightforward SPIHT.