PROJECT TITLE :

Nodal sampling: a new image reconstruction Algorithm for smos. - 2016

ABSTRACT:

Soil moisture and ocean salinity (SMOS) brightness temperature (TB) pictures and calibrated visibilities are related by the so-known as G-matrix. Because of the unfinished sampling at some spatial frequencies, sharp transitions in the TB scenes generate a Gibbs-like contamination ringing and unfold sidelobes. In this SMOS image reconstruction strategy, a Blackman window is applied to the Fourier elements of the TBs to diminish the amplitude of artifacts like ripples, as well as alternative Gibbs-like effects. In this paper, a completely unique image reconstruction algorithm centered on the reduction of Gibbs-like contamination in TB images is proposed. It's based on sampling the TB images at the nodal points, that's, at those points at which the oscillating interference causes the minimum distortion to the geophysical signal. Results show a important reduction of ripples and sidelobes in strongly radio-frequency interference contaminated images. This system has been totally validated using snapshots over the ocean, by comparing TBs reconstructed in the quality means or using the nodal sampling (NS) with modeled TBs. Tests have revealed that the standard deviation of the distinction between the measurement and the model is reduced around one K over clean and stable zones when using NS technique with respect to the SMOS image reconstruction baseline. The reduction is approximately 0.seven K when considering the global ocean. This represents a crucial improvement in TB quality, that will translate in an enhancement of the retrieved geophysical parameters, particularly the sea surface salinity.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Depth Reconstruction From Sparse Samples: Representation, Algorithm, and Sampling - 2015 ABSTRACT: The fast development of 3D technology and computer vision applications has motivated a thrust of methodologies
PROJECT TITLE :Depth Reconstruction From Sparse Samples: Representation, Algorithm, and SamplingABSTRACT:The rapid development of 3D technology and pc vision applications has motivated a thrust of methodologies for depth acquisition
PROJECT TITLE :Robust SCUC With Multi-Band Nodal Load Uncertainty SetABSTRACT:This letter discusses a multi-band robust security- constrained unit commitment (SCUC) model for addressing spatial/temporal relationship of nodal load
PROJECT TITLE :On the Properties of Nodal Price Response Matrix in Electricity MarketsABSTRACT:We have a tendency to establish an optical path difference (OPD) distribution model in a spatial scanned polarized low-coherence interferometry
PROJECT TITLE : Video Dissemination over Hybrid Cellular and Ad Hoc Networks - 2014 ABSTRACT: We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry