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The real noise model corrupting the observed images is unknown and usually random statistical model. Consequently, classical SRR (Super Resolution Reconstruction) algorithms using median (L1) and mean (L2) filtering structures may degrade the reconstructed image sequence rather than enhance it. The mathematical analysis [1] demonstrates that the meridian filtering structure exhibits more robust characteristic...
Image reconstruction problems in radio astronomy and other fields like biomedical imaging are often ill-posed and some form of regularization is required. This imposes user specified constraints to the reconstruction process that may produce an undesirable bias to the solution. We propose a data driven model based least squares reconstruction method based on the Karhunen-Loève transform. We show that...
Spatial resolution enhancement is usually required in the remote sensing field. Super-Resolution (SR) is a fusion process for reconstructing a High-Resolution (HR) image from several Low-Resolution (LR) images covering the same region in the world. It is difficult, however, for some satellite remote sensing arrangements to get several images of the same scene in a short time, especially for highly...
Microgrid imaging polarimeters consist of a focal plane array sensor with linear polarization filters of differing orientations overlaid at each pixel, similar in concept to the arrangement of spectral filters in a color CCD Bayer pattern camera. However, unlike spectral color cameras, microgrid systems use polarimetrically modulated intensity measurements to reconstruct the Stokes vector at each...
We propose an objective function to determine the focus step and the drift parameters for HRTEM images. Searching for the maximum value of this objective function, we can determine the focus step and the top-left coordinates of the images' corresponding region. Based on these optimized parameters, exit wave reconstruction can then be performed for experimental images. In this paper, we focus on the...
We report the implementation of a fully on-chip, lensless, sub-pixel resolving optofluidic microscope (SROFM) based on the super resolution algorithm. The device utilizes microfluidic flow to deliver specimens directly across a complementary metal oxide semiconductor (CMOS) sensor to generate a sequence of low-resolution (LR) projection images, where resolution is limited by the sensor's pixel size...
Knife Edge Scanning Microscopy (KESM) is a high-throughput imaging technique used to obtain large-scale anatomical information (≈1cm3) at sub-micrometer resolution. Data acquisition has been fully automated, however significant post-processing and reconstruction must be done manually. KESM is unique in that illumination and tissue sectioning are performed using a diamond knife. Therefore many of the...
Using a set of low resolution images with sub-pixel shifts to reconstruct a high resolution less aliased image requires both interleaving of the image samples at the effectively higher sampling rate and deconvolution of the blur introduced by pixel sensor averaging. When measurement noise is low and knowledge of sub-pixel shift values is accurate, resolution improvement is limited primarily by the...
We demonstrate an optofluidic microscopy scheme which can acquire stereo images, utilizing different angles of illumination for projection imaging with our sub-pixel resolving optofluidic microscope.
The focus of this work is on improving the recognition performance of low-resolution iris video frames acquired under varying illumination. To facilitate this, an image-level fusion scheme with modest computational requirements is proposed. The proposed algorithm uses the evidence of multiple image frames of the same iris to extract discriminatory information via the Principal Components Transform...
In this paper, we propose a robust video super-resolution reconstruction method based on spatial-temporal orientation-adaptive kernel regression. First, we propose a robust registration efficiency model to reflect the temporal information reliability. Second, we propose a spatial-temporal steering kernel considering motions between frames and structures in each low resolution frame. Simulation results...
In this paper we present an almost automatic synthesis of a highly complex, throughput optimized architecture of an adaptive multiresolution filter as used in medical image processing for FPGAs. The filter consists of 16 parallel working modules, where the most computationally intensive module achieves software pipelining of a factor of 85, that is, computations of 85 iterations overlap each other...
In 3D video transmission, the depth map is normally compressed by resolution reduction to save bandwidth. The lost information in resolution reduction is recovered by an appropriate upsampling algorithm in decoding step. Most previous work considers the depth upsampling problem as common 2D map upsampling problem and do not take the intrinsic property of depth map into consideration. In this paper,...
123I-DaTSCAN imaging studies have shown the ability to detect loss of striatal dopamine transporters. Aim of this work is to evaluate whether mathematical approach of striatum imaging data by Matlab program processing can differentiate between parkinsonian syndromes, of various stages, and essential tremor, and thus increase diagnostic accuracy. The extraction of parameters by digitized processing...
Text data in an image present useful information for annotation, indexing and structuring of images. The gathered information from images can be applied for devices for impaired people, navigation, tourist assistance or georeferencing business. In this paper we propose a novel algorithm for text detection and localization from outdoor/indoor images which is robust against different font size, style,...
In novel look-up table (N-LUT) method, the size of LUT is determined by the amount of shift of the principle fringe pattern (PFP). Thus, if the resolution of object is increased or pixel pitch of hologram is decreased, the size of LUT is increased. Therefore, in this paper, we propose the memory reduction method using the relation of pixel pitch of hologram and reconstruction distance. Some experiments...
Super-resolution involves the use of signal processing techniques to estimate the high-resolution (HR) version of a scene from multiple low-resolution (LR) observations. It follows that the quality of the reconstructed HR image would depend on the quality of the LR observations. The latter depends on multiple factors like the image acquisition process, encoding or compression and transmission. However,...
Recently a novel look-up table (N-LUT) method to dramatically reduce the number of pre-calculated interference patterns required for generation of digital holograms was proposed. In this method, principle fringe pattern (PFP) has reflection symmetry in geometry. Thus in this paper, we proposed the memory reduction method using this reflection symmetry of PFP. From some experimental result, the memory...
In this paper, a new approach for fast computation of CGH patterns for the 3-D image by combined use of the DPCM and the N-LUT is proposed. Some experiments with test 3-D images are carried out and the results are compared to those of the conventional methods in terms of the number of the object points and computation time.
In this study, a novel split method was proposed to enlarge low resolution image. Instead of maintaining the grey levels of original pixels and estimating the grey levels for newly added pixels, the proposed approach split the original pixel, into new pixels. Two approaches are proposed to estimate grey levels for the new pixels, namely zero order split approach and 2nd order split approach. Degraded...
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