The Experts below are selected from a list of 14778 Experts worldwide ranked by ideXlab platform

Yan Guo - One of the best experts on this subject based on the ideXlab platform.

Lei Wu - One of the best experts on this subject based on the ideXlab platform.

  • hydrodynamic limit with Geometric Correction of stationary boltzmann equation
    Journal of Differential Equations, 2016
    Co-Authors: Lei Wu
    Abstract:

    Abstract We consider the hydrodynamic limit of a stationary Boltzmann equation in a unit plate with in-flow boundary. The classical theory claims that the solution can be approximated by the sum of interior solution which satisfies steady incompressible Navier–Stokes–Fourier system, and boundary layer derived from Milne problem. In this paper, we construct counterexamples to disprove such formulation in L ∞ both for its proof and result. Also, we show the hydrodynamic limit with a different boundary layer expansion with Geometric Correction.

  • hydrodynamic limit with Geometric Correction of stationary boltzmann equation
    arXiv: Analysis of PDEs, 2014
    Co-Authors: Lei Wu
    Abstract:

    We consider the hydrodynamic limit of a stationary Boltzmann equation in a unit plate with in-flow boundary. We prove the solution can be approximated in $L^{\infty}$ by the sum of interior solution which satisfies steady incompressible Navier-Stokes-Fourier system, and boundary layer with Geometric Correction. Also, we construct a counterexample to the classical theory which states the behavior of solution near boundary can be described by the Knudsen layer derived from the Milne problem.

D L Chen - One of the best experts on this subject based on the ideXlab platform.

Luis Cortereal - One of the best experts on this subject based on the ideXlab platform.

  • measures for an objective evaluation of the Geometric Correction process quality
    IEEE Geoscience and Remote Sensing Letters, 2009
    Co-Authors: Hernâni Goncalves, J A Goncalves, Luis Cortereal
    Abstract:

    The Geometric Correction process is a crucial step in remote sensing applications. This process is frequently manually performed-which is a laborious task in many situations-as automatic image registration methods are still far from being broadly applied. One of the reasons that justify the absence of a broad application of automatic image registration methods is the lack of measures for an objective and automated analysis of the image registration process quality. The root mean square (RMS) of the residuals is the only quantitative evaluation which is generally used in this process, with the final validation of the Geometric Correction process being a qualitative analysis. Therefore, in both ldquohumanrdquo and automatic image registration processes, an objective evaluation of its quality is required. In this letter, we propose several measures for an objective evaluation of the Geometric Correction process, as a complement to the traditional RMS of the residuals and visual inspection. Two scenarios of control point distribution and the most common residual distributions were considered. With the proposed measures, we intend to cover the most common qualitative analysis aspects. This has particular importance under the scope of automatic image registration methods, where an automatic evaluation of the results is also required.

Mikio Takagi - One of the best experts on this subject based on the ideXlab platform.

  • precise Geometric Correction for noaa and gms images considering elevation effects using gcp template matching and affine transform
    Remote Sensing, 2004
    Co-Authors: Mikio Takagi
    Abstract:

    This paper describes a precise Geometric Correction method considering elevation effects for NOAA/AVHRR of GMS images, which is mandatory for long-term global environmental monitoring studies. First, using the so-called systematic Geometric Correction, the correspondences of sub-sampled image pixels to their map coordinates are calculated. And, the correspondences of sub-sampled map locations, which are the corner points of blocks, to image pixels are calculated to speed up the inverse transform to find for a pixel on the map coordinates to the corresponding pixel in the image coordinates using the bilinear interpolation of the four corner points of a block. For precise Geometric Correction, the residual errors of the systematic Correction are measured using many GCP templates. GCP templates in the map coordinates are provide using DCW. Templates in the image coordinates are generated using the bilinear Interpolation. Also, the templates of high elevation areas are modified to include the elevation effects, using the height from GTOPO30 and satellite sensor geometry. Then, the residual errors are acquired by template matching and affine transform coefficients are calculated to remove the residual errors. And if the difference between the average error and each GCP is more than one pixel, these GCP’s are removed and new affine transform coefficients are recalculated iteratively until all errors reach within one pixel. Then, mapping of each pixel is done using the correspondence of four corner block points and image coordinates modified by affine transform, but for high elevation areas blocks are divided into pixels according to their elevation. The accuracy of within one pixel; i.e. 0.01 degree for NOAA/AVHRR and GMS/VIS and 0.04 degrees for GMS/IR is obtained for NOAA images received at Tokyo and the stitched ones received at Tokyo and Bangkok and also GMS full disk images.