ALBERT

Description: Radar coincidence imaging is an instantaneous imaging technique which does not depend on the relative motion between targets and radars. High-resolution, fine-quality images can be obtained using a single pulse either for stationary targets or for complexly maneuvering ones. There are two image-reconstruction algorithms used for radar coincidence imaging, that is, the correlation method and the parameterized method. In comparison with the former, the parameterized method can achieve much higher resolution but is seriously sensitive to grid mismatch. In the presence of grid mismatch, neither of the two algorithms can obtain recognizable high-resolution images. The above problem largely limits the applicability of radar coincidence imaging in actual imaging scenes where grid mismatch generally exists. This paper proposes a joint correlation-parameterization algorithm, which uses the correlation method to estimate the grid-mismatch error and then iteratively modifies the results of the parameterized method. The proposed algorithm can achieve high resolution with fine imagery quality under the grid mismatch. Examples are provided to illustrate the improvement of the proposed method.

Description: A new log-power domain feature enhancement algorithm named NLPS is developed. It consists of two parts, direct solution of nonlinear system model and log-power subtraction. In contrast to other methods, the proposed algorithm does not need prior speech/noise statistical model. Instead, it works by direct solution of the nonlinear function derived from the speech recognition system. Separate steps are utilized to refine the accuracy of estimated cepstrum by log-power subtraction, which is the second part of the proposed algorithm. The proposed algorithm manages to solve the speech probability distribution function (PDF) discontinuity problem caused by traditional spectral subtraction series algorithms. The effectiveness of the proposed filter is extensively compared using the standard database, AURORA2. The results show that significant improvement can be achieved by incorporating the proposed algorithm. The proposed algorithm reaches a recognition rate of over 86% for noisy speech (average from SNR 0 dB to 20 dB), which means a 48% error reduction over the baseline Mel-frequency Cepstral Coefficient (MFCC) system.

Description: Schemes for spectrum holes sensing for cognitive radio based on the estimation of the Stokes parameters of monochromatic and quasimonochromatic polarized electromagnetic waves are developed. Statistical information that includes the variations of the polarization state in both cases (present and absent) of Primary User (PU) is accounted for. A detector based on the fluctuation of the Stokes parameters is analyzed, and its performance is compared with that of energy detectors, which use only the scalar amplitude information to sense the PU signal. The cooperative spectrum sensing based on the polarization in which the reporting channels are noisy will be investigated. The cluster technique is proposed to reduce the bit error probability due to channel impairment. A closed-form expression for the polarization detection is derived using α-μ generalized fading model, which provides directly an expression for the special cases of Nakagami-m and Weibull models as well as their derivatives. These expressions are verified using simulation. The results show that the polarization spectrum sensing gives superior performance for a wide range of SNR over the conventional energy detection method.

Description: This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions possess neither standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast ICA based analysis fail to extract text from these inscription images. Natural gradient flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%), respectively.

Description: Image quality assessment (IQA) has been a topic of intense research over the last several decades. With each year comes an increasing number of new IQA algorithms, extensions of existing IQA algorithms, and applications of IQA to other disciplines. In this article, I first provide an up-to-date review of research in IQA, and then I highlight several open challenges in this field. The first half of this article provides discuss key properties of visual perception, image quality databases, existing full-reference, no-reference, and reduced-reference IQA algorithms. Yet, despite the remarkable progress that has been made in IQA, many fundamental challenges remain largely unsolved. The second half of this article highlights some of these challenges. I specifically discuss challenges related to lack of complete perceptual models for: natural images, compound and suprathreshold distortions, and multiple distortions, and the interactive effects of these distortions on the images. I also discuss challenges related to IQA of images containing nontraditional, and I discuss challenges related to the computational efficiency. The goal of this article is not only to help practitioners and researchers keep abreast of the recent advances in IQA, but to also raise awareness of the key limitations of current IQA knowledge.

Description: The aim of this survey is to provide a comprehensive overview of the state of the art in the area of image forensics. These techniques have been designed to identify the source of a digital image or to determine whether the content is authentic or modified, without the knowledge of any prior information about the image under analysis (and thus are defined as passive). All these tools work by detecting the presence, the absence, or the incongruence of some traces intrinsically tied to the digital image by the acquisition device and by any other operation after its creation. The paper has been organized by classifying the tools according to the position in the history of the digital image in which the relative footprint is left: acquisition-based methods, coding-based methods, and editing-based schemes.

Description: A blind source separation method is described to extract sources from data mixtures where the underlying sources are sparse and correlated. The approach used is to detect and analyze segments of time where one source exists on its own. The method does not assume independence of sources and probability density functions are not assumed for any of the sources. A comparison is made between the proposed method and the Fast-ICA and Clusterwise PCA methods. It is shown that the proposed method works best for cases where the underlying sources are strongly correlated because Fast-ICA assumes zero correlation between sources and Clusterwise PCA can be sensitive to overlap between sources. However, for cases of sources that are sparse and weakly correlated with each other, there is a tendency for Fast-ICA and Clusterwise PCA to have better performances than the proposed method, the reason being that these methods appear to be more robust to changes in input parameters to the algorithms. In addition, because of the deflationary nature of the proposed method, there is a tendency for estimates to be more affected by noise than Fast-ICA when the number of sources increases. The paper concludes with a discussion concerning potential applications for the proposed method.

Description: We have addressed a novel watermarking algorithm to support the capacity demanded by the multimodal biometric templates. Proposed technique embeds watermark in low frequency AC coefficients of selected 8 × 8 DCT blocks. Selection of blocks accomplishes perceptual transparency by exploiting the masking effects of human visual system (HVS). Embedding is done by modulating the coefficient magnitude as a function of its estimated value. Neighborhood estimation is used for the weighted DC coefficients from eight neighboring DCT blocks. The weights of the DC coefficients are calculated from local image intrinsic property. For our experimentation we have used iris and finger prints as the two templates which are watermarked into standard test images. The robustness of the proposed algorithm is compared with the few state-of-the-art literature when watermarked image is subjected to common channel attacks.

Description: The established statistical analysis, already used to treat overhead transmission power grid networks, is now implemented to examine the factors influencing modal transmission characteristics and modal statistical performance metrics of overhead and underground low-voltage/broadband over power lines (LV/BPL) and medium-voltage/broadband over power lines (MV/BPL) channels associated with power distribution in smart grid (SG) networks. The novelty of this paper is threefold. First, a refined multidimensional chain scattering matrix (TM2) method suitable for overhead and underground LV/BPL and MV/BPL modal channels is evaluated against other relative theoretical and experimental proven models. Second, applying TM2 method, the end-to-end modal channel attenuation of various LV/BPL and MV/BPL multiconductor transmission line (MTL) configurations is determined. The LV/BPL and MV/BPL transmission channels are investigated with regard to their spectral behavior and their end-to-end modal channel attenuation. It is found that the above features depend drastically on the frequency, the type of power grid, the mode considered, the MTL configuration, the physical properties of the cables used, the end-to-end distance, and the number, the electrical length, and the terminations of the branches encountered along the end-to-end BPL signal propagation. Third, the statistical properties of various overhead and underground LV/BPL and MV/BPL modal channels are investigated revealing the correlation between end-to-end modal channel attenuation and modal root-mean-square delay spread (RMS-DS). Already verified in the case of overhead high-voltage (HV) BPL systems, this fundamental property of several wireline systems is also modally validated against relevant sets of field measurements, numerical results, and recently proposed statistical channel models for various overhead and underground LV/BPL and MV/BPL channels. Based on this common inherent attribute of either transmission or distribution BPL networks, new unified regression trend line is proposed giving a further boost towards BPL system intraoperability. A consequence of this paper is that it aids in gaining a better understanding of the range and coverage that BPL solutions can achieve; a preliminary step toward the system symbiosis between BPL systems and other broadband technologies in an SG environment.

Description: The research trends that are available in the area of image compression for various imaging applications are not adequate for some of the applications. These applications require good visual quality in processing. In general the tradeoff between compression efficiency and picture quality is the most important parameter to validate the work. The existing algorithms for still image compression were developed by considering the compression efficiency parameter by giving least importance to the visual quality in processing. Hence, we proposed a novel lossless image compression algorithm based on Golomb-Rice coding which was efficiently suited for various types of digital images. Thus, in this work, we specifically address the following problem that is to maintain the compression ratio for better visual quality in the reconstruction and considerable gain in the values of peak signal-to-noise ratios (PSNR). We considered medical images, satellite extracted images, and natural images for the inspection and proposed a novel technique to increase the visual quality of the reconstructed image.