All pixels are altered toward many points obtained from the two-dimensional polynomial slanted plane.
FIRST_ORDER- 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. Pixels are altered toward multiple target colors, which are distributed across the mosaic dataset. COLOR_GRID- Use when you have a large number of raster datasets, or areas with a large number of diverse ground objects. All the pixels are altered toward a single color point-the average of all pixels. If there are too many raster datasets or too many types of ground surfaces, the output color may become blurred. SINGLE_COLOR- Use when there are only a small number of raster datasets and a few different types of ground objects. All input pixels are altered toward multiple points obtained from the cubic surface. Third order- 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. Second order- 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. First order- 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. Color grid- Use when you have a large number of raster datasets, or areas with a large number of diverse ground objects. Single color- Use when there are only a small number of raster datasets and a few different types of ground objects. To remove a color correction, right-click the mosaic dataset in the Catalog pane and click Remove > Remove Color Balancing When standard deviation balancing is used-The target standard deviation is obtained from the reference target image. When histogram balancing is used-The target histogram is obtained from the reference target image. For the polynomial order surfaces, the coefficients of the polynomial are obtained by least square fitting, from the reference target image. For color grid, the reference target image is resampled to a suitable grid. For single color, the average value of the reference target image is used. When dodging balancing is used-The target color that will be derived depends on the target color surface type that was chosen. The Target Raster is a raster that is used to guide color balancing. There are five types of target color surfaces that you can choose from: single color, color grid, first order surface, second order surface, and third order surface. When using the dodging technique, each pixel needs a target color, which is picked up from the target color surface. The target color surface is only available if the dodging balancing technique is chosen. On the tool's dialog box, these three parameters are found in the Preprocessing Options parameter category. The actions defined by the Exclude Area Raster, Stretch Type, and Gamma parameters ( exclude_raster, stretch_type, and gamma in Python) are performed before any color balancing takes place. 
If the bit depth of the input mosaic dataset and the target raster are different, the pixel values will be automatically scaled so that they are both in the same bit depth. If there are more bands in the input mosaic dataset, the bands in the target raster will be used again, sequentially. Ideally, the number of bands should be the same. The bands in the Target Raster need to be in the same order as the bands in the input mosaic dataset.
None of the raster dataset have an associated color map. Only 8-bit unsigned and 16-bit unsigned bit depths are supported. All the bands have their histogram built. All the bands have their statistics calculated. 
Color balancing can only take place if the following is true about your data:
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