An Integrated Message Hiding and Message Extraction Technique for Multimedia Content Using Invisible Watermarking Technique

The protection of multimedia data is becoming very important. The protection can be done with encryption. Involving both encryption and compression side-by-side needs more complex algorithms for content retrieval. Reconstructing the compressed encrypted content without much information loss is important. This work improves the ratio-distortion performance and also embedded message in the source image can be extracted for the source image authentication by using invisible watermarking technique. The message can be embedded into and extracted from the source image using watermarking techniques. The watermarked image is compressed by using quantization method to improve the compression ratio. The compressed image is encrypted and decrypted using modulo-256 addition by adding pseudo-random numbers into the image pixels. The encrypted image is splitted into number of files and in the user side using the auxiliary information (AI), file is merged using file adaptive wrapper method to decrypt the source image. Finally, with the use of verification key the embedded message is extracted and the source image is verified. It is shown that this method improves the ratio-distortion performance in compressing a watermarked image and better quality of reconstructed image. In order to further improve the distortion performance and quality of the reconstructed image other compression methods can be used. DOI: 10.17762/ijritcc2321-8169.15054

Estudi de la coautoria de publicacions científiques entre UPC i nou universitats dels Estats Units: Brown University, University of Chicago, Northwestern University, Stanford University, Columbia University, Cornell University, Harvard University, Princeton University i Duke University

S'analitza la coautoria de la UPC amb autors vinculats a institucions acadèmiques dels Estats Units, per totes les àrees temàtiques i sense considerar límits cronològics o documentals.Postprint (published version

Estimation of Dynamical Systems in Noisy Conditions and with Constraints

When measurements from dynamical systems are noisy, it is useful to have estimation algorithms that have low sensitivity to measurement noises and outliers. In the first set of results described in this paper we obtain optimal estimators for linear dynamical systems with $\epsilon$ insensitive loss functions. The $\epsilon$ insensitive loss function, which is often used in Support Vector Machines, provides greater robustness when the measurements are biased and very noisy as the algorithm tolerates small errors in prediction which in turn makes the estimates less sensitive to measurement noises. Apart from $\epsilon$ insensitive quadratic loss function, estimation algorithms are also derived for $\epsilon$ insensitive Huber M loss function which provides robustness in presence of both small noises as well as outliers. Robustness in presence of outliers is achieved with Huber cost function based estimator as the error penalty function switches from quadratic to linear for errors beyond certain threshold. The second set of results in the paper describe algorithms for estimation when apart from general description of dynamics of the system, one also has additional information about states and exogenous signals such as known range of some states or prior information about the maximum magnitude of noises/disturbances. While the proposed approaches have similarities to Kalman-Bucy or $\mathcal{H}_2$ smoothing algorithm, the algorithms are not linear in measurements but are easily implemented as optimal estimates are obtained by solving a standard quadratic optimization problem with linear constraints. For all cases, algorithms are proposed not only for filtering and smoothing but also for prediction of future states.Comment: Some typos corrected and added Huber M cost function result

Modeling and Compensation of Transceiver Non-Reciprocity in TDD Multi-Antenna Base-Station

Due to the increasing demands for higher system capacity, higher data rates and better quality of service in wireless networks, advanced techniques that improve wireless link reliability and spectral efficiency are introduced. This includes different multi-antenna technologies, in particular multi-user (MU) MIMO-OFDM. In MU MIMO-OFDM systems, base-station with multiple antennas communicates simultaneously with multiple users over a given time-frequency resource. In downlink transmission, base-station transmits multiple data streams through its antennas towards the user devices. In uplink transmission, the user equipment send in parallel multiple data streams towards the base-station. In general, channel non-reciprocity is a very important factor in cellular communications, in particular in precoded MU MIMO-OFDM systems adopting time division duplexing (TDD). Based on the channel reciprocity principle, the channel state information at base-station for the downlink transmission can be determined through estimating the uplink channels. In practice, however, there are always unavoidable frequency mismatch characteristics between transmitter and receiver. Frequency response mismatch can thus change the reciprocal nature of downlink and uplink channels. The impact of transceiver non-reciprocity at equipment on user side causes inter-stream interference which can be compensated using detection processing. The impact of transceiver non-reciprocity at base-station causes inter-user interference and degrades the system performance of MU MIMO-OFDM systems. To ensure the system reliability and high performance in case of transceiver non-reciprocity, some non-reciprocity estimation and compensation methods are required. The previous work has proposed the estimation-compensation framework that gives a flexible solution to restore the channel reciprocity. But there is a need to validate the findings and performance of the proposed estimation-compensation framework. The modeling of transceiver frequency response mismatch characteristics using actual measurement data has been carried out in this thesis research work. The actual measurement data comprises of one base-station with two antennas and two user equipment devices with single antenna. The estimated uplink and downlink channels from measurement data are used to compute the non-reciprocity matrix at base-station and at the equipment on user side after mathematical calculations. The normalized parameters for transceiver non-reciprocity matrices are extracted subcarrier-wise. The frequency-domain normalized non-reciprocity parameters are modeled as a FIR filter in the time-domain and the most energy concentrates then on few time-domain taps. The extracted parameters are mildly frequency-selective. The impact of extracted transceiver non-reciprocity is then analyzed by implementing a simulator of TDD precoded MU MIMO-OFDM system. In general, the frequency-selectivity implies that the reciprocity estimation and compensation is needed subcarrier-wise. The pilot-based estimation of non-reciprocity parameters at base-station is carried out in order to enhance the system performance. To estimate channel non-reciprocity parameters, a link between base-station and one of user equipment devices is assumed. The right choice of selecting the user is also important for noise reduction in estimation. For estimation, the DL transmission channel is modeled as a Rayleigh fading multipath channel with a given 7-tap channel power delay profile. The downlink data including sparsely located pilots at selected subcarriers is transmitted to the user through downlink channel without precoding. The downlink channel is then estimated at the user equipment side. This provides estimates only at the pilot subcarriers. Therefore, linear interpolation is used to obtain channel response estimates at the actual data subcarriers. The uplink pilot data is transmitted to base-station from user equipment through uplink channel. The uplink channel is obtained by estimated downlink channel in case of non-reciprocity parameters. Then, estimate of non-reciprocity at base-station is computed by using inverse processing and an interpolator. The estimated parameters are used as a compensator filter in order to compensate the channel non-reciprocity in the system. The simulated results show that the performance deviates from the ideal linear precoded MU MIMO-OFDM system because of non-reciprocity in case of both error control coded and uncoded channels. The compensated results in terms of coded and uncoded channel schemes have been evaluated which are closer to ideal linear precoded MU-MIMO OFDM system. These results show that the impact of non-reciprocity on system performance is less severe when a coded channel is deployed as compared to uncoded channel. The modeling of transceiver frequency response mismatch characteristics using actual measurement data proves that the proposed non-reciprocity model in the previous research work is close to reality

Novel implementation technique for a wavelet-based broadband signal detection system

This thesis reports on the design, simulation and implementation of a novel Implementation for a Wavelet-based Broadband Signal Detection System. There is a strong interest in methods of increasing the resolution of sonar systems for the detection of targets at sea. A novel implementation of a wideband active sonar signal detection system is proposed in this project. In the system the Continuous Wavelet Transform is used for target motion estimation and an Adaptive-Network-based Fuzzy inference System (ANFIS) is adopted to minimize the noise effect on target detection. A local optimum search algorithm is introduced in this project to reduce the computation load of the Continuous Wavelet Transform and make it suitable for practical applications. The proposed system is realized on a Xilinx University Program Virtex-II Pro Development System which contains a Virtex II pro XC2VP30 FPGA chip with 2 powerPC 405 cores. Testing for single target detection and multiple target detection shows the proposed system is able to accurately locate targets under reverberation-limited underwater environment with a Signal-Noise-Ratio of up to -30db, with location error less than 10 meters and velocity estimation error less than 1 knot. In the proposed system the combination of CWT and local optimum search algorithm significantly saves the computation time for CWT and make it more practical to real applications. Also the implementation of ANFIS on the FPGA board indicates in the future a real-time ANFIS operation with VLSI implementation would be possible

Development of Low Power Image Compression Techniques

Digital camera is the main medium for digital photography. The basic operation performed by a simple digital camera is, to convert the light energy to electrical energy, then the energy is converted to digital format and a compression algorithm is used to reduce memory requirement for storing the image. This compression algorithm is frequently called for capturing and storing the images. This leads us to develop an efficient compression algorithm which will give the same result as that of the existing algorithms with low power consumption. As a result the new algorithm implemented camera can be used for capturing more images then the previous one. 1) Discrete Cosine Transform (DCT) based JPEG is an accepted standard for lossy compression of still image. Quantisation is mainly responsible for the amount loss in the image quality in the process of lossy compression. A new Energy Quantisation (EQ) method proposed for speeding up the coding and decoding procedure while preserving image qu..

COMPOSITE KERNEL FEATURE ANALYSIS FOR CANCER CLASSIFICATION

Computed tomographic (CT) colonography, or virtual colonoscopy, is a promising technique for screening colorectal cancers by use of CT scans of the colon. Current CT technology allows a single image set of the colon to be acquired in 10-20 seconds, which translates into an easier, more comfortable examination than is available with other screening tests. Currently, however, interpretation of an entire CT colonography examination is time-consuming, and the reader performance for polyp detection varies substantially. To overcome these difficulties while providing a high detection performance of polyps, researchers are developing computer-aided detection (CAD) schemes that automatically detect suspicious lesions in CT colonography images. The overall goal of this study is to achieve a high performance in the detection of polyps on CT colonographic images by effectively incorporating an appearance-based object recognition approaches into a model-based CAD scheme. Our studies are focused in developing a fast kernel feature analysis that can efficiently differentiate polyps from false positives and thus improve the detection performance of polyps. We have developed a novel method of selecting kernel functions that are appropriate for the given data set and then use their linear combination in the construction of Kernel Gram matrix which can then used for efficient reconstruction of feature space. The main contribution of this work lies in providing a Composite kernel Matrix that involves appearance-based approach to improve kernel feature analysis for the classification of texture-based features. We evaluated our proposed kernel feature analysis on texture-based features that were extracted from the polyp candidates generated by our shape-based CAD scheme

Novel implementation technique for a wavelet-based broadband signal detection system

This thesis reports on the design, simulation and implementation of a novel Implementation for a Wavelet-based Broadband Signal Detection System. There is a strong interest in methods of increasing the resolution of sonar systems for the detection of targets at sea. A novel implementation of a wideband active sonar signal detection system is proposed in this project. In the system the Continuous Wavelet Transform is used for target motion estimation and an Adaptive-Network-based Fuzzy inference System (ANFIS) is adopted to minimize the noise effect on target detection. A local optimum search algorithm is introduced in this project to reduce the computation load of the Continuous Wavelet Transform and make it suitable for practical applications. The proposed system is realized on a Xilinx University Program Virtex-II Pro Development System which contains a Virtex II pro XC2VP30 FPGA chip with 2 powerPC 405 cores. Testing for single target detection and multiple target detection shows the proposed system is able to accurately locate targets under reverberation-limited underwater environment with a Signal-Noise-Ratio of up to -30db, with location error less than 10 meters and velocity estimation error less than 1 knot. In the proposed system the combination of CWT and local optimum search algorithm significantly saves the computation time for CWT and make it more practical to real applications. Also the implementation of ANFIS on the FPGA board indicates in the future a real-time ANFIS operation with VLSI implementation would be possible.EThOS - Electronic Theses Online ServiceGBUnited Kingdo