Generate an orthomosaic using the Orthomosaic wizard—ArcGIS Pro

Available with Advanced license.

An orthomosaic is a photogrammetrically orthorectified image product mosaicked from an image collection, where the geometric distortion has been corrected and the imagery has been color balanced to produce a seamless mosaic dataset.

Color-balanced imagery showing seamlines and the resulting orthomosaic

The Orthomosaic wizard provides a common workflow for generating ortho image mosaics from the adjusted image collection. The Orthomosaic wizard provides a guided workflow with four preconfigured steps to generate a photogrammetrically corrected image from your image collection:

Orthorectification
Color balancing
Seamline generation
Orthomosaic settings

You can modify the default processing parameters, but you cannot remove a step. To perform a specific step, you can use the Custom wizard.

Orthorectification settings

Select the elevation source that will be used to orthorectify your mosaic.

Note:

Satellite imagery is orthorectified during adjustment using the workspace DEM. For all other workspace types, the image collection is orthorectified when generating the orthomosaic.

Parameters for Orthorectification settings


Parameter name	Description
Elevation Source	The digital elevation model (DEM) that will be used to orthorectify the orthomosaic. Options include the reference DEM for the workspace, a DEM generated using the DEMs Wizard, or an external DEM.

Color balance settings

Modify the settings to color balance your orthomosaic. Color balancing adjusts the appearance of individual images to make the transition from one image to an adjoining image appear seamless.

Parameters for color balance settings


Parameter name	Description
Select Mosaic Candidates	The Select Mosaic Candidates parameter is typically used for image collection with dense overlaps such as drones. It is used to find an optimum set of images that can be used in mosaicking images. The selected images will be used in seamline building, color balancing, and output mosaic operation.
Balance Method	The color balancing algorithm to use. Dodging—Image pixel values will be adjusted toward a target color surface using a dodging window and the corresponding gamma function established from the local statistics of the window and the target color surface. The color surface can be calculated from the input image collection with the specified color surface type or from an external target raster. This is the default. Histogram—Image pixel value will be adjusted by matching the histogram of each image to the histogram of the entire image collection or the histogram of the external target raster if specified. This technique works well when all of the images to be color balanced have a similar histogram. Standard deviation—Image pixel value will be adjusted by matching the histogram within one standard deviation between each image and the entire image collection or the target raster if specified. This technique works best when all of the images to be color balanced have normal distributions.
Color Surface Type	If the Dodging balance method is used, each pixel needs a target color, which is determined by the surface type. Single color—All the pixels will be altered toward a single color point, which is the average of all pixels. This technique is appropriate when there are only a small number of images and a few types of ground objects. If there are too many rasters or there are too many types of ground surface features, the output color may become blurred. Color grid—Pixels will be altered toward a grid of color points that are distributed across the image collection. This technique is appropriate when you have a large number of images or areas with a large number of diverse ground objects. First order—A color surface (a slanted plane) will be represented as a first order polynomial. This technique tends to create smoother color changes and uses less storage in the auxiliary table, but it may take longer to process compared to the color grid surface. All pixels may be altered toward many points obtained from the two-dimensional polynomial slanted plane. The result is similar to that of Single color. Second order—A color surface will be represented as a second order polynomial. This technique tends to create a smoother color change and uses less storage in the auxiliary table, but it may take longer to process compared to the color grid surface. All input pixels are altered toward a set of multiple points obtained from the two-dimensional polynomial parabolic surface. This method produces an intermediate result between that of Single color and Color grid. This is the default. Third order—A color surface will be represented as a third order polynomial. This technique tends to create a smoother color change and uses less storage in the auxiliary table, but it may take longer to process compared to the color grid surface. All input pixels are altered toward multiple points obtained from the cubic surface. The result is similar to that of Color grid.
Target Raster	The raster that will be used as a target to color balance the image collection. It can be a raster dataset, a mosaic dataset, or an image service. The statistics required by the balance method and color surface type, if applicable, will be derived from this target image.
Recalculate Statistics	Once color balancing has been performed, there may be new pixel values in your raster. Check the check box to calculate the statistics with the latest pixel values.
Number of Columns to Skip	The number of horizontal pixels between samples. A skip factor controls the portion of the raster that is used when calculating the statistics. The input value indicates the horizontal or vertical skip factor, where a value of 1 will use each pixel and a value of 2 will use every second pixel. The skip factor can only range from 1 to the number of columns/rows in the raster. The value must be greater than zero and less than or equal to the number of columns in the raster. The default is 1 or the last skip factor used. The skip factors for raster datasets stored in a file geodatabase or an enterprise geodatabase are different. First, if the x and y skip factors are different, the smaller skip factor will be used for both the x and y skip factors. Second, the skip factor is related to the pyramid level that most closely fits the skip factor chosen. If the skip factor value is not equal to the number of pixels in a pyramid layer, the number is rounded down to the next pyramid level, and those statistics are used.
Number of Rows to Skip	The number of vertical pixels between samples. A skip factor controls the portion of the raster that is used when calculating the statistics. The input value indicates the horizontal or vertical skip factor, where a value of 1 will use each pixel and a value of 2 will use every second pixel. The skip factor can only range from 1 to the number of columns/rows in the raster. The value must be greater than zero and less than or equal to the number of rows in the raster. The default is 1 or the last y skip factor used. The skip factors for raster datasets stored in a file geodatabase or an enterprise geodatabase are different. First, if the x and y skip factors are different, the smaller skip factor will be used for both the x and y skip factors. Second, the skip factor is related to the pyramid level that most closely fits the skip factor chosen. If the skip factor value is not equal to the number of pixels in a pyramid layer, the number is rounded down to the next pyramid level, and those statistics are used.

Seamline settings

Specify the seamline settings for your orthomosaic. Seamlines are polygons that are used for defining mosaicking boundaries and resolving the image overlaps.

Parameters for seamline settings


Parameter name	Description
Computation Method	The computation method that will be used to generate seamlines: Disparity—Seamlines will be generated based on the disparity images of stereo pairs. This method can avoid seamlines cutting through buildings. Voronoi—Seamlines will be generated using the area Voronoi diagram. This is the default. Radiometry—Seamlines will be generated based on the spectral patterns of features within the imagery. Edge Detection—Seamlines will be generated over intersecting areas based on the edges of features in the area. Geometry—Seamlines will be generated for overlapping areas based on the intersection of footprints. Areas with no overlapping imagery will merge the footprints.
Advanced Options
Pixel Size	The pixel size to use for seamline generation. Sometimes, a mosaic dataset contains raster items with different resolutions. Use this parameter choose the pixel size for generating seamlines.
Minimum Region Size	Specify the minimum region size, in pixel units. Any polygons smaller than this specified threshold will be removed in the seamline result. The default is 100 pixels.
Processing
Blend Width Units	The unit of measurement to use for blend width: Pixels—Measure using the number of pixels. This is the default. Ground units—Measure using the same units as the mosaic dataset.
Blend Width	Blending (feathering) occurs along a seamline between pixels where there are overlapping rasters. The blend width defines how many pixels will be blended. If the blend width value is 10, and you use BOTH as the blend type, then 5 pixels will be blended on the inside and outside of the seamline. If the value is 10, and the blend type is INSIDE, then 10 pixels will be blended on the inside of the seamline.
Blend Type	The method that will be used to blend one image into another over the seamlines. The options are to blend inside the seamlines, outside the seamlines, or both inside and outside. Both— Pixels on either side of the seamlines will be blended. For example, if the Blend Width value is 10 pixels, 5 pixels will be blended on the inside and the outside of the seamline. This is the default. Inside—Pixels inside the seamline will be blended. Outside—Pixels outside the seamline will be blended.
Request Size Type	The units that will be used for the Request Size value. Pixels—The request size will be modified based on the pixel size. This option resamples the closest image based on the raster pixel size. This is the default. Pixel scaling factor—The request size will be modified by specifying a scaling factor. This option resamples the closest image by multiplying the raster pixel size (from cell size level table) with the pixel size factor.
Request Size	Specify the number of columns and rows for resampling. The maximum value is 5,000. Increase or decrease this value based on the complexity of your raster data. Greater image resolution provides more detail in the raster dataset but also increases the processing time.
Sliver Removal Options
Minimum Thinness Ratio	Define how thin a polygon can be, before it is considered a sliver. This is based on a scale from 0 to 1.0, where a value of 0.0 represents a polygon that is almost a straight line, and a value of 1.0 represents a polygon that is a circle. Slivers are removed when building seamlines.
Maximum Sliver Size	The maximum size a polygon can be to still be considered a sliver. This parameter is specified in pixels and is based on the Request Size value, not the spatial resolution of the source raster. Any polygon that is less than the square of this value is considered a sliver. Slivers are removed when building seamlines.

Orthomosaic settings

Specify the output settings for your mosaic.

Parameters for orthomosaic settings


Parameter name	Description
Pixel Size	The pixel size that will be used for the orthomosaic.
Format	The output format that will be used for the orthomosaic: Cloud Raster Format TIFF Format JPEG Format JPEG2000 Format Meta Raster Format
Compression	The compression method that will be used for the output. The following options will be available based on the Format value you choose: None LZW JPEG JPEG2000 LERC