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In this paper, we present a blind image restoration algorithm to reconstruct a high resolution (HR) color image from multiple, low resolution (LR), degraded and noisy images captured by thin (< 1mm) TOMBO imaging systems. The proposed algorithm is an extension of our grayscale algorithm reported in [1] to the case of color images. In this color extension, each Point Spread Function (PSF) of each captured image is assumed to be different from one color component to another and from one imaging unit to the other. For the task of image restoration, we use all spectral information in each captured image to restore each output pixel in the reconstructed HR image, i.e., we use the most efficient global category of point operations. First, the composite RGB color components of each captured image are extracted. A blind estimation technique is then applied to estimate the spectra of each color component and its associated blurring PSF. The estimation process is formed in a way that minimizes significantly the interchannel cross-correlations and additive noise. The estimated PSFs together with advanced interpolation techniques are then combined to compensate for blur and reconstruct a HR color image of the original scene. Finally, a histogram normalization process adjusts the balance between image color components, brightness and contrast. Simulated and experimental results reveal that the proposed algorithm is capable of restoring HR color images from degraded, LR and noisy observations even at low Signal-to-Noise Energy ratios (SNERs). The proposed algorithm uses FFT and only two fundamental image restoration constraints, making it suitable for silicon integration with the TOMBO imager. [ABSTRACT FROM AUTHOR]

The matrix assisted pulsed laser evaporation (MAPLE) technique has been used for the deposition of metal dioxide (TiO2, SnO2) nanoparticle thin films for gas sensor applications. For this purpose, colloidal metal dioxide nanoparticles were diluted in volatile solvents, the solution was frozen at the liquid nitrogen temperature and irradiated with a pulsed excimer laser. The dioxide nanoparticles were deposited on Si and Al2O3 substrates. A rather uniform distribution of TiO2 nanoparticles with an average size of about 10 nm and of SnO2 nanoparticles with an average size of about 3 nm was obtained, as demonstrated by high resolution scanning electron microscopy (SEM-FEG) inspections. Gas-sensing devices based on the resistive transduction mechanism were fabricated by depositing the nanoparticle thin films onto suitable rough alumina substrates equipped with interdigitated electrical contacts and heating elements. Electrical characterization measurements were carried out in controlled environment. The results of the gas-sensing tests towards low concentrations of ethanol and acetone vapors are reported. Typical gas sensor parameters (gas responses, response/recovery time, sensitivity, and low detection limit) towards ethanol and acetone are presented. [ABSTRACT FROM AUTHOR]

Controllable growth of wafer-scale in-plane nanowires (NWs) is a prerequisite for achieving addressable and scalable NW-based quantum devices. Here, by introducing molecular beam epitaxy on patterned Si structures, we demonstrate the wafer-scale epitaxial growth of site-controlled in-plane Si, SiGe, and Ge/Si core/shell NW arrays on Si (001) substrate. The epitaxially grown Si, SiGe, and Ge/Si core/shell NW are highly homogeneous with well-defined facets. Suspended Si NWs with four {111} facets and a side width of about 25 nm are observed. Characterizations including high resolution transmission electron microscopy (HRTEM) confirm the high quality of these epitaxial NWs. [ABSTRACT FROM AUTHOR]