In our practices with raw bundle of GeoEye-1, we found that the pan-sharpening transformation method may bring too much histogram variance, which causes significantly-unbalanced color in overall image among imagery scenes in mosaic dataset (natural color band 321 with near-infrared weight value added).
Do we have any other approaches to apply for GeoEye-1 in order to get pan-sharpening transformation done and also can minimize histogram variance for better color-balanced image in overall?
Or, on color-balanced aspect, does anyone else have good practice with plenty of images in 'production' test and get acceptable results to share ?
The ESRI pan-sharpening transformation uses weighted averaging (WA) and the additional near-infrared band (optional) to create its pan-sharpened output bands. The weighted average is calculated by using the following formula: WA = (R * RW + G * GW + B * BW + I * IW) / (RW + GW + BW + IW)
The result of the weighted average is used to create an adjustment value (ADJ), which is then used in calculating the output values, as shown in the following example: ADJ = pan image - WA Red_out = R + ADJ Green_out = G + ADJ Blue_out = B + ADJ Near_Infrared_out = I + ADJ
For the ESRI pan-sharpening transformation, the weight values of 0.166, 0.167, 0.167, 0.5 (R, G, B, I) provide good results when using QuickBird imagery.
It has been found that by changing the near-infrared weight value, the green output can be made more or less vibrant.
