Image Fusion in Remote Sensing and Quality Evaluation of Fused Images

In remote sensing, acquired optical images of high spectral resolution have usually a lower spatial resolution than images of lower spectral resolution. This is due to physical, cost and complexity constraints. To make the most of the available imagery, many image fusion techniques have been developed to address this problem. Image fusion is an ill-posed inverse problem where an image of low spatial resolution and high spectral resolution is enhanced in spatial-resolution by using an auxiliary image of high spatial resolution and low spectral resolution. It is assumed that both images display the same scene and are properly co-registered. Thus, the problem is essentially to transfer details from the higher spatial resolution auxiliary image to the upscaled lower resolution image in a manner that minimizes the spatial and spectral distortion of the fused image. The most common image fusion problem is pansharpening, where a multispectral (MS) image is enhanced using wide-band panchromatic (PAN) image. A similar problem is the enhancement of a hyperspectral (HS) image by either a PAN image or an MS image. As there is no reference image available, the reliable quantitative evaluation of the quality of the fused image is a difficult problem. This thesis addresses the image fusion problem in three different ways and also addresses the problem of quantitative quality evaluation.Í fjarkönnun hafa myndir með háa rófsupplausn lægri rúmupplausn en myndir með lægri rófsupplausn vegna eðlisfræðilegra og kostnaðarlegra takmarkana. Til að auka upplýsingamagn slíkra mynda hafa verið þróaðar fjölmargar sambræðsluaðferðir á síðustu tveimur áratugum. Myndsambræðsla er illa framsett andhverft vandmál (e. inverse problem) þar sem rúmupplausn myndar af hárri rófsupplausn er aukin með því að nota upplýsingar frá mynd af hárri rúmupplausn og lægri rófsupplausn. Það er gert ráð fyrir að báðar myndir sýni nákvæmlega sama landsvæði. Þannig er vandamálið í eðli sínu að flytja fíngerða eiginleika myndar af hærri rúmupplausn yfir á mynd af lægri rúmupplausn sem hefur verið brúuð upp í stærð hinnar myndarinnar, án þess að skerða gæði rófsupplýsinga upphaflegu myndarinnar. Algengasta myndbræðsluvandamálið í fjarkönnun er svokölluð panskerpun (e. pansharpening) þar sem fjölrásamynd (e. multispectral image) er endurbætt í rúmi með svokallaðri víðbandsmynd (e. panchromatic image) sem hefur aðeins eina rás af hárri upplausn. Annað svipað vandamál er sambræðsla háfjölrásamyndar (e. hyperspectral image) og annaðhvort fjölrásamyndar eða víðbandsmyndar. Þar sem myndsambræðsla er andhverft vandmál er engin háupplausnar samanburðarmynd tiltæk, sem gerir mat á gæðum sambræddu myndarinnar að erfiðu vandamáli. Í þessari ritgerð eru kynntar þrjár aðferðir sem taka á myndsambræðlsu og einnig er fjallað um mat á gæðum sambræddra mynda, þá sérstaklega panskerptra mynda

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data(1,2). Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank(3). This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation

Sentinel-2 Image Fusion Using a Deep Residual Network

Single sensor fusion is the fusion of two or more spectrally disjoint reflectance bands that have different spatial resolution and have been acquired by the same sensor. An example is Sentinel-2, a constellation of two satellites, which can acquire multispectral bands of 10 m, 20 m and 60 m resolution for visible, near infrared (NIR) and shortwave infrared (SWIR). In this paper, we present a method to fuse the fine and coarse spatial resolution bands to obtain finer spatial resolution versions of the coarse bands. It is based on a deep convolutional neural network which has a residual design that models the fusion problem. The residual architecture helps the network to converge faster and allows for deeper networks by relieving the network of having to learn the coarse spatial resolution part of the inputs, enabling it to focus on constructing the missing fine spatial details. Using several real Sentinel-2 datasets, we study the effects of the most important hyperparameters on the quantitative quality of the fused image, compare the method to several state-of-the-art methods and demonstrate that it outperforms the comparison methods in experiments

Humoral Immune Response to SARS-CoV-2 in Iceland.

To access publisher's full text version of this article click on the hyperlink belowBackground: Little is known about the nature and durability of the humoral immune response to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: We measured antibodies in serum samples from 30,576 persons in Iceland, using six assays (including two pan-immunoglobulin [pan-Ig] assays), and we determined that the appropriate measure of seropositivity was a positive result with both pan-Ig assays. We tested 2102 samples collected from 1237 persons up to 4 months after diagnosis by a quantitative polymerase-chain-reaction (qPCR) assay. We measured antibodies in 4222 quarantined persons who had been exposed to SARS-CoV-2 and in 23,452 persons not known to have been exposed. Results: Of the 1797 persons who had recovered from SARS-CoV-2 infection, 1107 of the 1215 who were tested (91.1%) were seropositive; antiviral antibody titers assayed by two pan-Ig assays increased during 2 months after diagnosis by qPCR and remained on a plateau for the remainder of the study. Of quarantined persons, 2.3% were seropositive; of those with unknown exposure, 0.3% were positive. We estimate that 0.9% of Icelanders were infected with SARS-CoV-2 and that the infection was fatal in 0.3%. We also estimate that 56% of all SARS-CoV-2 infections in Iceland had been diagnosed with qPCR, 14% had occurred in quarantined persons who had not been tested with qPCR (or who had not received a positive result, if tested), and 30% had occurred in persons outside quarantine and not tested with qPCR. Conclusions: Our results indicate that antiviral antibodies against SARS-CoV-2 did not decline within 4 months after diagnosis. We estimate that the risk of death from infection was 0.3% and that 44% of persons infected with SARS-CoV-2 in Iceland were not diagnosed by qPCR