Guidelines for Best Practice and Quality Checking of Ortho Imagery

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Guidelines for Best Practice and Quality Checking of Ortho Imagery – Issue 3.0 Page 24• Multiplicative. The multiplicative algorithm is derived by using the four possible arithmeticmethods to incorporate an intensity image into a chromatic image (addition, subtraction,division, and multiplication).• PCA Sharpening. Principal Components Analysis is based on a rotation in which thecovariance matrix becomes diagonal (all off diagonal elements are zero). The 1st principalcomponent (PC) contains most of the information. The panchromatic band is substituted infor the 1st principal component. Image is rotated back to original space.• Gramm Schmidt Sharpening. This is a Kodak / RSI proprietary sharpening algorithm. Thealgorithm is based on a rotation similar in nature to PCA. The results are quite similar to PCA– robustness is an issue especially in heavily vegetated scenes• Wavelet Sharpening. A relatively new sharpening algorithm involving wavelets has comeinto use lately. The low resolution RGB image is upsampled to match the panchromaticresolution, then converted to HIS space. High frequency information from the panchromaticband is extracted and added to the intensity band. The result is converted back to RGB space• UNB Sharpening. UNB stands for University of New Brunswick. Algorithm is proprietary andwas developed by Dr. Yun Zhang at UNB. This algorithm has been licensed by bothDigitalGlobe and PCI (latest version of Geomatica). This is DigitalGlobe’s most popular pansharpening algorithm to date.
Guidelines for Best Practice and Quality Checking of Ortho Imagery – Issue 3.0 Page 2511 MosaickingMosaicking is used for producing a visually appealing orthoimage of large areas. In order to achievethis goal, the input images should have consistent geometric and radiometric characteristics so thatthe seams will be as less visible as possible in the output mosaic. Table 11 presents the main steps ofthe process and the quality checks to be followed.Operation Best practice Quality checkRadiometricpre-processingArea selectionInput images should be radiometrically homogeneousMosaic as much as possible only images acquired in asingle collect (same conditions)The most nadir chips of the images should be used formosaicking to reduce distortion effects (smear)Images should be contrast, lightness(and colour) balancedSimilar types of objects not varyingmore than 10% in DN value (average).Check the seamlines against the imagenadir points and footprintsSeamlinesRun batch process with automatic seam generation butwith user interaction for reviewing and editingseamlinesTable 11. Best practice and QC for the production of orthomosaics.Visual check for full coverage at theAOI with seamlines polygonsSeamlines not to cut through welldefined features (e.g. buildingsespecially if not a DSM used)Visual check along seams forgeometric discrepancies or featheringeffects (blur)The final mosaics (usually tiled) should be accompanied with the following metadata:• A shapefile of the seamlines polygons and the information regarding with the input images(see 5.3)• A shapefile of the tiles distribution and their attributes• Analytical information about the radiometric processing of the input imagesFigure 3. Seamlines polygons and tiles distribution (NAIP 2007 Arizona Preliminary SeamlineShapefile Inspection)
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Guidelines for Best Practice and Quality Checking of Ortho Imagery

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