118,897 research outputs found
A Novel Metric Approach Evaluation For The Spatial Enhancement Of Pan-Sharpened Images
Various and different methods can be used to produce high-resolution
multispectral images from high-resolution panchromatic image (PAN) and
low-resolution multispectral images (MS), mostly on the pixel level. The
Quality of image fusion is an essential determinant of the value of processing
images fusion for many applications. Spatial and spectral qualities are the two
important indexes that used to evaluate the quality of any fused image.
However, the jury is still out of fused image's benefits if it compared with
its original images. In addition, there is a lack of measures for assessing the
objective quality of the spatial resolution for the fusion methods. So, an
objective quality of the spatial resolution assessment for fusion images is
required. Therefore, this paper describes a new approach proposed to estimate
the spatial resolution improve by High Past Division Index (HPDI) upon
calculating the spatial-frequency of the edge regions of the image and it deals
with a comparison of various analytical techniques for evaluating the Spatial
quality, and estimating the colour distortion added by image fusion including:
MG, SG, FCC, SD, En, SNR, CC and NRMSE. In addition, this paper devotes to
concentrate on the comparison of various image fusion techniques based on pixel
and feature fusion technique.Comment: arXiv admin note: substantial text overlap with arXiv:1110.497
Guided patch-wise nonlocal SAR despeckling
We propose a new method for SAR image despeckling which leverages information
drawn from co-registered optical imagery. Filtering is performed by plain
patch-wise nonlocal means, operating exclusively on SAR data. However, the
filtering weights are computed by taking into account also the optical guide,
which is much cleaner than the SAR data, and hence more discriminative. To
avoid injecting optical-domain information into the filtered image, a
SAR-domain statistical test is preliminarily performed to reject right away any
risky predictor. Experiments on two SAR-optical datasets prove the proposed
method to suppress very effectively the speckle, preserving structural details,
and without introducing visible filtering artifacts. Overall, the proposed
method compares favourably with all state-of-the-art despeckling filters, and
also with our own previous optical-guided filter
Target-adaptive CNN-based pansharpening
We recently proposed a convolutional neural network (CNN) for remote sensing
image pansharpening obtaining a significant performance gain over the state of
the art. In this paper, we explore a number of architectural and training
variations to this baseline, achieving further performance gains with a
lightweight network which trains very fast. Leveraging on this latter property,
we propose a target-adaptive usage modality which ensures a very good
performance also in the presence of a mismatch w.r.t. the training set, and
even across different sensors. The proposed method, published online as an
off-the-shelf software tool, allows users to perform fast and high-quality
CNN-based pansharpening of their own target images on general-purpose hardware
Multimodal person recognition for human-vehicle interaction
Next-generation vehicles will undoubtedly feature biometric person recognition as part of an effort to improve the driving experience. Today's technology prevents such systems from operating satisfactorily under adverse conditions. A proposed framework for achieving person recognition successfully combines different biometric modalities, borne out in two case studies
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