On the Layers page, you can select preferences for opening and displaying layers in Focus.
Layers
Under Layers, in the When loading list, you can select the level of zoom to use when adding a new layer to a project.
You can select from the following:
- Zoom to Overview: Displays an overview of the map each time you open a new layer
- Zoom to Full Extents of Layer: Displays the full extents of the newly opened layer
- Don't Change the Zoom: Retains the active zoom level when a new layer is opened
You can also select to load rasters at a one-to-one zoom level by default by selecting the Load Rasters at 1:1 resolution check box. However, consider that if you open several rasters at the same time, the default enhancement may be unsatisfactory. If you intend to regularly open several rasters at the same time, you may want to leave the check box clear.
Rasters
Under Rasters, you can select the display properties to use when you open rasters.
In the Default resampling method list, you select how to resample the raster when viewing at greater than 1:1 resolution. The available options are as follows:
- Nearest neighbor is the most appropriate resampling method to use with discrete data. It identifies the gray level of the pixel closest to the specified input coordinates and assigns that value to the output coordinates. Although this method is considered the most efficient in computation time, it introduces small errors in the output image. The output image may be offset spatially by up to half a pixel, which may cause the image to have a jagged appearance.
- Bilinear interpolation determines the gray level from the weighted average of the nine closest pixels to the specified input coordinates and assigns that value to the output coordinates. This method generates an image with a smoother appearance than nearest neighbor, but the gray-level values are altered in the process, which can result in blurring or loss of image resolution. Similar to cubic-convolution resampling, bilinear interpolation is most appropriate for continuous data.
- Cubic convolution determines the gray level from the weighted average of the 16 pixels closest to the specified input coordinates and assigns that value to the output coordinates. The resulting image is slightly sharper than one produced with bilinear interpolation, and it does not have the disjointed appearance produced by nearest neighbor. Similar to bilinear interpolation, cubic convolution is most appropriate for continuous data.
In the Default visual enhancement list, you select the default visual enhancement to use with a newly opened raster. The available options are as folllows:
- None: Does not apply an enhancement to 8U data types. This setting does, however, apply a linear stretch or a linear enhancement to other data types using their pixel values. The stretch is applied using only those pixels displayed in the viewer. At a zoomed-out level, the pixel values are decimated before they are displayed in the viewer. Therefore, the range of pixels used for the linear stretch may be narrower than the actual range of pixels in the image file. This means that the actual minimum and maximum values in the image file may not be included in the calculation of the linear stretch. Tail Trim and Exclude Min/Max settings are ignored for all data types.
- Linear: Minimum and maximum values in the image are stretched uniformly over the entire range of the available output display to enhance the overall differences in gray levels in the image.
- Root: Compresses the range of higher values (brightness) and expands the range of lower values (darkness) so you can distinguish more detail in darker areas of an image while still retaining some detail in the brighter areas.
- Equalization: Distributes the values equally over the entire output display range, which results in a near-uniform histogram. This enhancement is effective in exposing details in the higher values (brightness) and lower values (darkness), but causes less contrast in the middle values.
- Adaptive: Combines the benefits of the Equalization and Linear enhancements, which results in a more natural display than Equalization, and compensates effectively for outliers.
- Infrequency: Assigns the values that occur least frequently in the image to the range of higher values (brightness) in the histogram so finer details become brighter.
In the Complex SAR interpretation list, you select how you want to visualize various interpretations of complex SAR data. You can load interpretations—for display only—without modifying the properties of the complex channel.
With a complex number, a + bi, where a corresponds to real part (I) and b to the imaginary part (Q).
The available options are as folllows:
- Intensity: Corresponds to I^2 + Q^2.
Intensity is also known as power.
- Amplitude: Corresponds to the square root of the intensity (I^2 + Q^2)^0.5
- Phase in radian: Corresponds to arctan (Q/I) in radian
- Phase in degrees: Corresponds to arctan (Q/I) in degrees
- Real: I
- Imaginary: Q
If you want to recompute the histogram using the pixels viewed currently each time the display changes, such as after panning or zooming, select the Auto re-enhance grayscale and RGB layers check box. If you want to use the histogram built when you selected the enhancement, and apply it to the display each time you pan or zoom, clear the check box.
Default Overviews
Under Default Overviews, you can select the automatic behavior for creating overviews (pyramids) and the downsampling method to use, respectively.
The available options are as follows:
- Never create overviews: No overviews are created on disk and the Create Overviews window does not appear when viewing a raster.
- Always generate default overviews: Overviews with all the default settings are generated automatically for each large raster that does not have existing overviews. The Create Overviews window does not appear when viewing a raster.
- Prompt for each raster: The Create Overviews window is displayed automatically for each large raster viewed.
If you want to have overviews created by using the default settings, in the Downsampling method list, select the method you want.
The available options are as follows:
- Nearest neighbor: Each pixel in the resampled raster acquires the same value as its nearest neighbor in the original raster. Although this method computes quickly, it can introduce small errors in the resampled raster, which may cause it to have a "jagged" appearance.
- Block average: Calculates the average value of a group of image pixels and uses that value for the screen pixel. This method often provides a more meaningful representation of the image in the viewer. This method is well suited to continuous-tone images, such as radar imagery.
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Block mode: Finds the most common value in a block of the image pixels and assigns that value to the output pixels. This method is well suited to thematic data, where any mathematical operations on pixel values (class numbers) have no meaning.