After selecting an image layer in the Layer Manager, the Layer Properties panel displays image parameter options, including brightness, contrast, transparent color, interpolation method, display method, etc.

The system supports selecting multiple image layers simultaneously for batch property settings. However, when the selected layers contain both single-band and multi-band images, the parameters in the Display Method group cannot be uniformly set.

Image Parameters

No Value Settings

• No Value: Refers to pixel values in image data that have no practical meaning. You can directly enter a pixel value in the text box, or click the pick button to select a pixel value from the image layer (snapping supported), thereby setting the specified pixel value as no value.
• No Value Transparent: This checkbox is used to set the display color of the specified no value. When checked, no value is displayed transparently by default. When unchecked, you can click the drop-down button on the right and select a color from the pop-up color panel, and the no value pixels of the data will be displayed in the specified color.
  Notes:

  The no value on the Dataset Attribute panel of the image is expressed as an RGB decimal integer value. On the Image Dataset Layer Properties panel, the no value is associated with the vertex color. When the vertex color is RGB, if the no value is 96555, it is displayed as (1,21,43) on the Layer Properties panel.

Background Value Settings

The color of pixels with the specified background value can be replaced with another color.

• Background Value: Click the pick button to select a pixel value from the image layer on the map as the background value (snapping supported), or directly enter a value in the value box as the background value.
• Background Value Transparent: Click the drop-down button and select a replacement color from the pop-up color panel.

Transparent Color Settings

The transparent color settings are used to set a certain color in the image layer as transparent, making the areas covered by the specified color in the image appear transparent. To complete the transparent color settings, the Transparent Color and Transparent Color Tolerance commands need to be used together.

• Transparent Color: Check this checkbox to set the specified no value pixels as transparent display; uncheck to display the specified no value color in the specified color. You can click the pick button to select a pixel color from the image layer on the map as the transparent color (snapping supported), or click the drop-down button to select a color and set it as the transparent color.
• Transparent Color Tolerance: After setting the transparent color tolerance value, assuming the original color setting is (r, g, b) and the tolerance setting is a, the color range that needs to be displayed transparently is between (r-a, g-a, b-a) and (r+a, g+a, b+a).

Operation Steps

1. In the Layer Manager, select the image layer to be color-adjusted and set this layer as the current layer.
2. Enable the transparent color setting of the image layer by checking the Transparent Color checkbox. At the same time, the color button on the right side of the Transparent Color checkbox becomes available.
3. Click the drop-down button for transparent color setting to specify the color of the transparent effect in the image layer.
4. Set the transparent color tolerance. You can directly enter a value, or click the drop-down button on the right side of the Transparent Color Tolerance number adjustment box and use the slider to adjust the tolerance value. The tolerance value is an integer between 0 and 255.
5. After setting, the image layer will display the effect after the settings in real time.

Brightness

When the current layer is an image layer, the Brightness number adjustment box is used to adjust the brightness of the image layer. You can directly enter a value in the Brightness number adjustment box to adjust the brightness of the current layer, or click the Brightness number adjustment box and use the mouse slider to adjust the brightness, browsing the setting results in real time.

Contrast

When the current layer is an image layer, the Contrast number adjustment box is used to adjust the contrast of the image layer. You can directly enter a value in the Contrast number adjustment box to adjust the contrast of the current layer, or click the Contrast number adjustment box and use the mouse slider to adjust the contrast, browsing the setting results in real time.

Image Interpolation

When zooming and browsing an image layer, the original image needs to be mapped to a set of larger or smaller pixels. SuperMap provides 5 interpolation methods: Nearest Neighbor, Low Quality, High Quality, High Quality Bilinear Interpolation, and High Quality Bicubic Interpolation. Different interpolation methods determine the quality of image display, but the higher the display quality of the output image, the longer the processing time.

• Nearest Neighbor: A relatively simple image interpolation method with fast processing speed, but the image display effect is the worst.
• Low Quality: This method performs pre-filtering to ensure high-quality shrinking, but the display quality when the image is enlarged is poor.
• High Quality: The image display quality is high when zooming, but the output image takes longer.
• High Quality Bilinear Interpolation: Performs pre-filtering through the specified high-quality bilinear interpolation method to ensure high-quality display effects of the zoomed image.
• High Quality Bicubic: Performs pre-filtering through the specified high-quality bicubic method to ensure high-quality display effects of the zoomed image. This method produces the highest display quality.

Display Method

Display Method

Based on the number of bands in the image data, it is divided into single-band images and multi-band images. The provided display method settings differ, as described below.

• Single-Band Image
  • Default Display: Displays the image data without stretching. If the image data has a color table, it will be displayed using the color table; otherwise, it will be displayed in grayscale.

    Figure: Default Display

  • Stretch Display: You can select Minimum Maximum, Standard Deviation, Gaussian, or Percent Clip to adjust the display effect of the image, and you can also adjust the color scheme of the image.

    Figure: Stretch Display

  • Color Table Display: Displays using the color table of the image data, and allows adjustment of the color scheme.

    Figure: Color Table Display

• Multi-Band Image
  • Combination Display: Combination display combines the multi-bands of the image according to a specified vertex color (e.g., RGB, CMYK) to obtain a color image display effect, and supports image stretching display settings.

    Figure: Combination Display

  • Single Band Stretch Display: Select a band for display, then choose a stretch method. You can select Minimum Maximum, Standard Deviation, Gaussian, Percent Clip, etc., to adjust the display effect of the image, and also adjust the color scheme of the image.

    Figure: Single Band Standard Deviation Display

  • Single Band Color Table Display: Select a band for display, then adjust the color scheme.

    Figure: Single Band Color Table Display

  • Single Band Grid Function Display: Select a band for display, then apply a raster function to obtain the desired display effect. For detailed instructions on raster functions, please refer to the Raster Functions section in Raster Layer Properties.

    Figure: Single Band Grid Function Display

Vertex Color

Due to differences in color formation principles, there is a distinction in the way color is generated between display devices such as monitors and projectors that directly synthesize colors using light, and printing devices such as printers and presses that use pigments. To address these different color formation methods, SuperMap provides 7 color spaces: RGB, CMYK, RGBA, CMY, YIQ, YUV, and YCC.

The drop-down list of the Vertex Color combo box lists the supported color spaces, used to set the color display mode of the image data. Click the drop-down button on the right of the "Color Mode:" label and select the desired vertex color from the pop-up menu to complete the vertex color setting. The default vertex color is RGB.

Vertex Color	Description
RGB	Mainly used in display systems. RGB stands for Red, Green, Blue. The RGB vertex color uses the RGB model to assign an intensity value between 0 and 255 to the RGB components of each pixel in the image.
CMYK	Mainly used in printing systems. CMYK stands for Cyan, Magenta, Yellow, and Key (Black). It generates various colors by mixing the concentrations of the three primary colors (Cyan, Magenta, Yellow) and uses black to adjust brightness and purity.
RGBA	Mainly used in display systems. RGB stands for Red, Green, Blue, and A is used to control transparency.
CMY	Mainly used in printing systems. CMY (Cyan, Magenta, Yellow) generates various colors by mixing the concentrations of the three primary colors.
YIQ	Primarily used in the North American television system (NTSC).
YUV	Primarily used in the European television system (PAL).
YCC	Primarily used in JPEG image format.

Image Color Scheme

Layer Properties supports modifying the color scheme of Image Parameters. Click the combo box on the right side of the label control and select the applicable color scheme for the group.

Image Stretching

During the acquisition of image data, image quality may degrade due to various factors. The main purpose of stretching image data is to improve the display effect and quality of the image data, thereby enhancing image clarity, highlighting certain information of interest for human or machine analysis, suppressing some useless information, and improving the value of the image data. The essence of stretching image data is to change the brightness and contrast of the image, making the features in the image easier to identify.

Currently, SuperMap provides several types of stretching for image data, including: No Stretching, Standard Deviation, Minimum Maximum, Histogram Equalization, Histogram Specification, Gaussian, and Percent Clip.

Batch setting of stretch methods for image layers is supported. In the Layer Manager, select multiple image layers and uniformly set the stretch method on the Layer Properties panel to conveniently adjust the image display effect.

• No Stretching: No stretching is applied to the image. However, this absolute no stretching is only effective for image data with unsigned 8-bit storage format. The pixel values displayed on the computer for image data are all in the range 0 to 255. Therefore, for image data stored in a format other than unsigned 8-bit, SuperMap uses the Minimum Maximum method for display when no stretching is applied, making the values fall within the 0 to 255 range. As shown in the figure below, the left image is an unsigned 8-bit image without stretching, appearing dark, and the right image is the histogram of the Red Band, with display values concentrated in the low grayscale area.

  Figure: No Stretching and Histogram

• Minimum Maximum: Linear extrusion using the minimum and maximum pixel values. This method uses the minimum and maximum pixel values as the range for linear extrusion, distributing pixel values between [0, 255]. Through such stretching, the contrast and brightness of the image are significantly improved, making features in the image easier to identify. It is generally suitable for raster images with densely distributed pixel values.

  As shown in the figure below, the left image is the result after stretching, which is clearer than the unstretched image, and the contrast is enhanced. The gray histogram on the right is before stretching, and the red histogram is after stretching.

  Figure: Minimum Maximum and Histogram Before and After Stretching

• Standard Deviation: Increases image contrast by trimming the extreme values of the image and then applying linear extrusion to the other pixel values. Statistics of the original image data are performed, mainly to obtain a one standard deviation range. Then, based on the standard deviation coefficient, the standard deviation range is updated. The values within the finally calculated standard deviation range are linearly extruded to [0, 255], reducing the deviation of displayed pixel values from the mean.

  Standard Deviation: The arithmetic square root of the variance, reflecting the degree of dispersion of individuals within a group. Simply put, it indicates the deviation of most values in the group from the mean. A larger standard deviation means most values deviate more from the mean; a smaller standard deviation means most values are closer to the mean.

  As shown in the figure below, the pixel proportion within one standard deviation coefficient is 68%, within two standard deviation coefficients is 95%, and within three standard deviation coefficients is 99%. If the standard deviation coefficient is defined as 2, pixel values exceeding two standard deviations are pushed to 0 or 255. Pixel values between two standard deviations are linearly extruded to 0-255. Standard deviation is often used to brighten raster datasets with darker tones.

  The following histogram vividly describes the standard deviation stretch method. As shown in the figure below, the left image shows the effect after standard deviation stretching, and the right image compares the histograms before and after stretching. It can be seen that after stretching, the histogram shape of the image conforms to a normal distribution curve, and the standard deviation of the histogram after stretching increases, meaning the deviation of the displayed pixel values from the mean is reduced.

  Standard deviation is often used to brighten darker images.

  Figure: Standard Deviation Stretching and Histogram Before and After Stretching

• Gaussian: Aims to make the pixel values of the image data follow a normal distribution. Gaussian is a linear extrusion.
  • Gaussian Coefficient: The pixel values of the image are multiplied by the coefficient and then stretched to the [0, 255] range.
  • Using Median: If "Using Median" is checked, the image stretching performs Gaussian distribution centered on the median pixel value; if unchecked, the default is to perform Gaussian distribution centered on the maximum pixel value.
    Notes:

    If the image lacks statistical information, when using Min Max, Standard Deviation, or Gaussian, a dialog box will appear prompting: "The stretch method requires statistical data information. Do you want to calculate statistics and continue?" If you click OK, the image statistics will be calculated and the corresponding stretch method will be applied. If you click Cancel, the stretch method will switch to No Stretching.

• Percent Clip: Generally, it can be assumed that most pixels in the image data are within the upper and lower limits. By setting a percentage, pixel values outside this range can be pushed to the two endpoints. Then, linear extrusion is applied to the pixel values within the range. This stretch method excludes some pixels with low values and some with high values in the histogram from stretching, and then applies the Minimum Maximum method to stretch the remaining part. When using it, the exclusion percentages for the minimum and maximum values need to be set.

  You can set the stretch display separately for each band of multi-band image data. Click the "Histogram" button on the right side of the combo box to open the histogram of each band, and specify the minimum and maximum percentage values to be excluded from stretching. These percentages represent the percentage of pixels with low values and high values to be excluded from stretching.

  For example: For an image with pixel values ranging from [0, 100], if the minimum and maximum exclusion percentages are set to 10, applying "Percent Clip" will stretch the values between [10, 90] to the [0, 255] range for display, while [0, 10] will be displayed as 0 and [90, 100] as 255.

  As shown in the figure below, the first image shows the display effect and histogram without setting the stretch range. From the histogram, it can be seen that there are relatively few pixels in the low and high value areas, affecting the contrast of the image and making it unclear. Excluding these pixels from stretching can increase contrast and clarity. The second image below shows the effect after setting the stretch range to exclude pixels at both ends, applying percentage clipping only within the set range.

  Figure 1: Stretch Range Not Set	Figure 2: Stretch Range Set

• Histogram Equalization: Belongs to the histogram modification method, which essentially performs non-linear extrusion on the image. By redistributing pixel values, the number of pixels in a certain grayscale range is made approximately equal. This enhances the contrast of the peak part in the original histogram and reduces the contrast of the valley parts on both sides. Thus, the output image has a relatively flat segmented histogram, enhancing image contrast.

  Figure: Histogram Before and After Equalization (Image source from the internet)

  Figure: Histogram Equalization Stretch and Histogram Before and After Stretching

  After histogram equalization stretching, the overall contrast of the image becomes very strong. The essence of histogram equalization is to reduce the number of grayscale levels of the image in exchange for expanding contrast. Therefore, sometimes the information we need at a certain grayscale may be lost after conversion. When the quality of the original remote sensing data is poor, the data dynamic range is small, and the histogram distribution is extremely uneven, performing histogram equalization enhancement may result in a worse visual layering effect and easier loss of information.

• Histogram Specification: Mathematically transforms the image lookup table to make the histogram of one image similar to that of another image. Histogram specification is often used as preprocessing for adjacent image mosaicking or dynamic change research using multi-temporal remote sensing imagery. Through histogram specification, differences in effects between adjacent images caused by solar elevation angle or atmospheric influences can be partially eliminated.

  Histogram specification is similar to histogram equalization, except that the output result of histogram equalization is fixed and tends to produce a more equalized image, while the result of histogram specification is to import a histogram XML file and use the histogram specified by the new file to display the image.

  Notes:

  If the image has not created an image pyramid, when using Percent Clip, Histogram Specification, or Histogram Equalization, a dialog box will appear prompting: "The stretch method requires creating a histogram. Do you want to create it and continue?" If you click OK, a histogram will be created for the image and the corresponding stretch method will be applied. If you click Cancel, the stretch method will switch to No Stretching.

• Adaptive Stretch: Adaptive stretch (full name: Contrast Limited Adaptive Histogram Equalization) is a variant of adaptive histogram equalization. This method divides the image into multiple sub-regions, calculates the histogram of each region separately, and redistributes the brightness values of the image accordingly. This effectively enhances local contrast and improves edge definition within each region of the image.

  However, traditional adaptive histogram equalization may overamplify contrast in relatively uniform areas of the image (where the histogram is highly concentrated), leading to significant amplification of noise in those areas. Adaptive stretch effectively reduces this noise amplification problem by limiting the degree of contrast enhancement.

  This method is suitable for enhancing the local contrast of images and currently supports processing images with 8-bit unsigned and 16-bit unsigned data types.

  Regarding the handling of no-value areas:

  • Specified no-value areas (usually 0 or 255): The no-value areas specified by the user will be identified and excluded. The pixel values in these areas are retained as original during the calculation, so their display is unaffected by the enhancement processing.
  • Other areas: Pixel values in areas not specified as no-value will participate in the adaptive stretch calculation. The processed pixel values may change. If the resulting value happens to fall within the specified no-value range (e.g., 0 or 255), it may be mistakenly identified as a no-value area during display, causing visual anomalies.

  When using adaptive stretch, the following parameters need to be set:

  • Crop Threshold: By limiting the maximum number of pixels corresponding to a single pixel value in the histogram, it indirectly constrains the degree of local contrast enhancement. This effectively prevents significant noise amplification or artifacts in noisy areas or areas with concentrated grayscale distribution (e.g., flat areas) due to excessive enhancement.
  • Block Rows/Columns: Specifies the number of blocks into which the image is divided. The total number of blocks = rows × columns.
    • Large Block Rows/Columns: The sub-region area is small, making the enhancement algorithm more sensitive to local details of the image, resulting in finer and more significant local contrast enhancement. However, differences in processing results between adjacent sub-regions may cause blocky boundary artifacts.
    • Small Block Rows/Columns: The sub-region area is large, making the enhancement effect smoother and more uniform spatially, reducing the risk of block artifacts. However, the enhancement effect on small-scale details and textures in the image is weakened, possibly failing to fully improve local contrast.

Gamma

The Gamma parameter enables non-linear brightness and contrast adjustment of the image, thereby enhancing image display details and improving the display quality of image data. The Gamma parameter ranges from 0 to 10 (inclusive), with a numerical precision of two decimal places.

• When the Gamma value is 1, no Gamma correction is applied to the image.

• When the Gamma value is greater than 1, the contrast in dark areas of the image increases, making details more prominent, but details in bright areas may be lost, and the overall image becomes brighter.

• When the Gamma value is less than 1, the contrast in bright areas of the image increases, making details more prominent, but details in dark areas may be lost, and the overall image becomes darker.

Figure: Gamma=1	Figure: Gamma=2
Figure: Gamma=1	Figure: Gamma=0.4

Display the Orthorectified Image

If the dataset associated with the layer contains RPC information, this checkbox can be enabled. When checked, the image orthorectified based on elevation data is displayed; when unchecked, the uncorrected image is displayed.

After checking, the following three setting methods are provided in the elevation value input box and the drop-down menu on the right:

• Fixed Value: Displays the elevation values from the remote sensing image files by default. You can directly edit other values in the text input box.
• SRTM V4: Uses the elevation information in the remote sensing resource package. This option is available after performing Image Environment Deployment.
• Custom: Loads elevation information by specifying DEM data. SupportsTiff/GeoTIFF,Erdas Image,PCIDSK, andArcInfoGrid formats. Among them,ArcInfoGrid format data can only be obtained by clicking theAdd Folder button.

Related Topics

Set Common Layer Properties

Set Vector Layer Properties

Set Raster Layer Properties