The motion blur simulation technique is widely used in remote sensing of an image chain simulation. However, the traditional method, which models the motion blur through a point spread function (PSF), is not precise enough when the imaging area is rugged or the motion of the platform is unstable. A physically based simulation model of motion blur is proposed. The model uses an image motion vector (IMV) field to describe the relative motion presented on the image plane during the exposure time. Based on the IMV field, the opto-electrons blurring model is built to simulate the blurring effect. A physical experiment was made to validate the model. The experiment result demonstrates that the simulation result generated by the model provided is more precise than the traditional PSF method, and a more complex motion status can be presented by the proposed method.
Image simulation plays an important role in remote sensing system design and data processing algorithm development, supposing that the fidelity of the simulated images is high enough. Many remote sensing image simulation models generate the geometric characteristics of the images through a georeferencing, convolution, and resampling process. In the georeferencing and resampling steps, each pixel is taken as a point, meanwhile a shift-invariant detector point spread function (PSF) is used in the convolution step. It omits the footprint size variation caused by the ground relief, earth curvature, and oblique viewing. To improve the fidelity of the simulated images, a pixel-size-varying (PSV) method was proposed: the four corners of each detector in a whiskbroom, pushbroom, or staring imaging sensor are separately considered in the georeferencing step, the sensor detector PSF is abandoned from the convolution step, and then the PSV sampling is simulated using an overlapping-area-weighted sum of the oversampled pixels. A validation experiment was conducted in simulating EO-1 Hyperion L1R data from georeferenced HyMap reflectance data. It showed that the PSV method outperforms the traditional method in the spectral aspect and is equal to the traditional method in other aspects, by comparing the simulated images with the actual one.
The HJ-1A and HJ-1B satellites were launched successfully on September 6, 2008. For effective monitoring of the environmental and natural disasters, both HJ-1A and HJ-1B carry a charge-coupled device (CCD) sensor, with each CCD sensor containing two cameras, which results in a ground swath of about 700 km for each satellite. The CCD can make cross-track multiple view angle measurements with a field of view of >40 deg . The Earth’s surface can be covered completely within 48 h in four spectral bands from 0.43 to 0.90 μm. We have presented a method of extracting the hemispherical-directional reflectance factor (HDRF) from CCD imagery and normalizing HDRF to a standard geometric situation. After geometric correction and registration, radiometric calibration, and correction for atmospheric effects, multitemporal HDRFs were obtained for the flat land surface located in Northern China with different land cover types. The angular observations were extracted from a series of overpasses of the CCD aboard HJ-1A and HJ-1B. We then inverted the HDRFs by the semiempirical kernel-driven bidirectional reflectance distribution function (BRDF) model and normalized the HDRFs to nadir-viewing direction. This study shows the significance of directional effects in the HJ-1A and HJ-1B CCD data and the feasibility of normalizing HDRFs’ CCD data when the angular effects must be taken into account.
KEYWORDS: 3D modeling, Statistical modeling, Solar radiation models, Data modeling, Computer simulations, Vegetation, Scattering, Near infrared, Reflectivity, Performance modeling
In this paper we present an analytical model for the computation of radiation transfer of discontinuous vegetation
canopies. Some initial results of gap probability and bidirectional gap probability of discontinuous vegetation canopies,
which are important parameters determining the radiative environment of the canopies, are given and compared with a 3-
D computer simulation model. In the model, negative exponential attenuation of light within individual plant canopies is
assumed. Then the computation of gap probability is resolved by determining the entry points and exiting points of the
ray with the individual plants via their equations in space. For the bidirectional gap probability, which determines the
single-scattering contribution of the canopy, a gap statistical analysis based model was adopted to correct the dependence
of gap probabilities for both solar and viewing directions. The model incorporates the structural characteristics, such as
plant sizes, leaf size, row spacing, foliage density, planting density, leaf inclination distribution. Available experimental
data are inadequate for a complete validation of the model. So it was evaluated with a three dimensional computer
simulation model for 3D vegetative scenes, which shows good agreement between these two models' results. This model
should be useful to the quantification of light interception and the modeling of bidirectional reflectance distributions of
discontinuous canopies.
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