An optimum interpolation method applied to the resampling of NOAAAVHRR data

Two main problems must be solved in the geometric processing of satellite data: geometric registration and resampling. When the data must be geometrically registered over a reference map, and particularly when the output pixel size is not the same as the original pixel size, the quality of the resampling can determine the quality of the output, not only in the visual appearance of the image, but also in the numerically interpolated values when used in multitemporal or multisensor studies. The “optimum” interpolation algorithm for AVHRR data is defined over a 6×6 window in order to: consider overlapping effects among adjacent pixels. The response for each new pixel R(x, y) is determined as a linear combination of the response R _i(x_iy_i) of the surrounding pixels in the window (i=1,36). The weighting coefficients μ_i are calculated from the ground projection of the effective spatial response function for each AVHRR pixel, taking into account the particular viewing angle and geometry of the pixels on the ground. This method is intended to give an optimal interpolation of AVHRR scenes along all the scanline, in order to compensate for off-nadir radiometric alterations associated to the varying spatial resolution and the blurring introduced by the pixel overlaps. The optimum method, as mathematically defined, is highly expensive in CPU time. Then, a big effort is necessary to implement the algorithms so that they could be operationally applied. Two approaches are considered: a general numerical method and a pseudo-analytical approximation. A Landsat TM image corresponding to the same date of the AVHRR image is used to test the quality of the radiometric interpolation procedure