A Mask-Based Enhancement Method for Historical Documents

This paper proposes a novel method for document enhancement. The method is based on the combination of two state-of-the-art filters through the construction of a mask. The mask is applied to a TV (Total Variation) -regularized image where background noise has been reduced. The masked image is then filtered by NLmeans (Non-Local Means) which reduces the noise in the text areas located by the mask. The document images to be enhanced are real historical documents from several periods which include several defects in their background. These defects result from scanning, paper aging and bleed-through. We observe the improvement of this enhancement method through OCR accuracy

Enhancement of Historical Printed Document Images by Combining Total Variation Regularization and Non-Local Means Filtering

This paper proposes a novel method for document enhancement which combines two recent powerful noise-reduction steps. The first step is based on the total variation framework. It flattens background grey-levels and produces an intermediate image where background noise is considerably reduced. This image is used as a mask to produce an image with a cleaner background while keeping character details. The second step is applied to the cleaner image and consists of a filter based on non-local means: character edges are smoothed by searching for similar patch images in pixel neighborhoods. The document images to be enhanced are real historical printed documents from several periods which include several defects in their background and on character edges. These defects result from scanning, paper aging and bleed- through. The proposed method enhances document images by combining the total variation and the non-local means techniques in order to improve OCR recognition. The method is shown to be more powerful than when these techniques are used alone and than other enhancement methods

The Photophysics of the Carrier of Extended Red Emission

Interstellar dust contains a component which reveals its presence by emitting a broad, unstructured band of light in the 540 to 950 nm wavelength range, referred to as Extended Red Emission (ERE). The presence of interstellar dust and ultraviolet photons are two necessary conditions for ERE to occur. This is the basis for suggestions which attribute ERE to an interstellar dust component capable of photoluminescence. In this study, we have collected all published ERE observations with absolute-calibrated spectra for interstellar environments, where the density of ultraviolet photons can be estimated reliably. In each case, we determined the band-integrated ERE intensity, the wavelength of peak emission in the ERE band, and the efficiency with which absorbed ultraviolet photons are contributing to the ERE. The data show that radiation is not only driving the ERE, as expected for a photoluminescence process, but is modifying the ERE carrier as manifested by a systematic increase in the ERE band's peak wavelength and a general decrease in the photon conversion efficiency with increasing densities of the prevailing exciting radiation. The overall spectral characteristics of the ERE and the observed high quantum efficiency of the ERE process are currently best matched by the recently proposed silicon nanoparticle (SNP) model. Using the experimentally established fact that ionization of semiconductor nanoparticles quenches their photoluminescence, we proceeded to test the SNP model by developing a quantitative model for the excitation and ionization equilibrium of SNPs under interstellar conditions for a wide range of radiation field densities.Comment: 42 p., incl. 8 fig. Accepted for publication by Ap

The Excitation of Extended Red Emission: New Constraints on its Carrier From HST Observations of NGC 7023

The carrier of the dust-associated photoluminescence process causing the extended red emission (ERE) in many dusty interstellar environments remains unidentified. Several competing models are more or less able to match the observed broad, unstructured ERE band. We now constrain the character of the ERE carrier further by determining the wavelengths of the radiation that initiates the ERE. Using the imaging capabilities of the Hubble Space Telescope, we have resolved the width of narrow ERE filaments appearing on the surfaces of externally illuminated molecular clouds in the bright reflection nebula NGC 7023 and compared them with the depth of penetration of radiation of known wavelengths into the same cloud surfaces. We identify photons with wavelengths shortward of 118 nm as the source of ERE initiation, not to be confused with ERE excitation, however. There are strong indications from the well-studied ERE in the Red Rectangle nebula and in the high-|b| Galactic cirrus that the photon flux with wavelengths shortward of 118 nm is too small to actually excite the observed ERE, even with 100% quantum efficiency. We conclude, therefore, that ERE excitation results from a two-step process. While none of the previously proposed ERE models can match these new constraints, we note that under interstellar conditions most polycyclic aromatic hydrocarbon (PAH) molecules are ionized to the di-cation stage by photons with E > 10.5 eV and that the electronic energy level structure of PAH di-cations is consistent with fluorescence in the wavelength band of the ERE. Therefore, PAH di-cations deserve further study as potential carriers of the ERE. (abridged)Comment: Accepted for Publication in the Ap

Implementation of an Optimal First-Order Method for Strongly Convex Total Variation Regularization

We present a practical implementation of an optimal first-order method, due to Nesterov, for large-scale total variation regularization in tomographic reconstruction, image deblurring, etc. The algorithm applies to $\mu$-strongly convex objective functions with $L$-Lipschitz continuous gradient. In the framework of Nesterov both $\mu$ and $L$ are assumed known -- an assumption that is seldom satisfied in practice. We propose to incorporate mechanisms to estimate locally sufficient $\mu$ and $L$ during the iterations. The mechanisms also allow for the application to non-strongly convex functions. We discuss the iteration complexity of several first-order methods, including the proposed algorithm, and we use a 3D tomography problem to compare the performance of these methods. The results show that for ill-conditioned problems solved to high accuracy, the proposed method significantly outperforms state-of-the-art first-order methods, as also suggested by theoretical results.Comment: 23 pages, 4 figure

Preservation of Piecewise Constancy under TV Regularization with Rectilinear Anisotropy

A recent result by Lasica, Moll and Mucha about the $\ell^1$-anisotropic Rudin-Osher-Fatemi model in $\mathbb{R}^2$ asserts that the solution is piecewise constant on a rectilinear grid, if the datum is. By means of a new proof we extend this result to $\mathbb{R}^n$. The core of our proof consists in showing that averaging operators associated to certain rectilinear grids map subgradients of the $\ell^1$-anisotropic total variation seminorm to subgradients

Application of holistic liquid chromatography-high resolution mass spectrometry based urinary metabolomics for prostate cancer detection and biomarker discovery

Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (