High Spatial Resolution Digital Imagery

41

represented a significant problem in creating usable mosaics. The ENVI imaging

processing software offers a cross-track illumination correction. The routine

calculates the overall row (east-to-west) average DNs within an image and then

fits a polynomial to the averages, for each band, to potentially correct (or flatten)

the reflectance data in the cross-track direction (south-to-north). If applied prop-

erly, the darker southern edge of each image should brighten, while the pixels at

the northern edge should darken slightly. This correction routine was applied to

each flightline after removal of the water pixels. The correction algorithm ignores

the background pixels (i.e., DN = 0) when calculating the across-track averages

and when applying the polynomial functions.

for mosaicking, an attempt was made to equalize the histograms of two overlap-

ping flightlines. This technique uses a simple mathematical formula to match the

general shape of the mean DN curves between two image files. Figure 24

displays the mean and standard deviation DN curves for the 14-band images

BLINE7E and BLINE8W. These curves were calculated using only the overlap

regions of the two adjacent flightlines. The formula employed to match one

histogram to the other is:

⎡⎛ *DNin *- *DNt *⎞

⎤

⎟ σ*DNr *⎥ + *DNr*

σ*DNt*

⎣⎝

⎠

⎦

Where

σ*DNt *= standard deviation of transform image

σ*DNr *= standard deviation of reference image

Flightline BLINE7E was transformed to the reference image BLINE8W.

Within the image processing software, the equation is applied to the 14-band in-

put image (BLINE7E) using matrix algebra. The four mean and standard devia-

tion terms are one-dimensional arrays (or vectors). The output image is an ad-

justed 14-band image. Figure 25 depicts the output mosaic, as both a true-color

and false-color file. While the equalization calculation worked nearly perfectly,