MultiscaleEnhancementCommand Class

Summary

Enhances an image's contrast, edges, and density range for use in Computed Radiography (CR), in a way that all relevant image features are rendered with an appropriate level of visibility. This command is available in the Medical toolkits.

Syntax

Objective-C

C++/CLI

Java

Python

public class MultiscaleEnhancementCommand : RasterCommand

@interface LTMultiscaleEnhancementCommand : LTRasterCommand

public class MultiscaleEnhancementCommand 
    extends RasterCommand

public ref class MultiscaleEnhancementCommand : public RasterCommand

class MultiscaleEnhancementCommand(RasterCommand):

Remarks

The command wraps techniques of image enhancements, such as contrast enhancement, edge enhancement and latitude reduction, for Computed Radiography (CR).
In multi scale enhancement, the image is decomposed into components or levels. Those components or levels that contain details will be enhanced separately from other components or levels.
This will improve the visualization for the subtle image features without the risk of losing information of other features.
To find the number of levels in any image follow this equation:
MaximumLevels = ceil( log( max(pimage->Width, pimage->Height)) / log(2));
The command will consider values larger than 10000 for contrast as 10000. If the user used a contrast of 0, then image contrast will not be improved.
Best results are obtained if contrast is in the range of 15 percent ~ 30 percent. The larger the value the stronger the enhancement will be. Any stronger enhancement than 30 percent will reveal noise and no new enhancement will be noticed.
The user can further enhance the image with:
- edge enhancements (use MultiscaleEnhancementCommandFlags.EdgeEnhancement) and/or
- latitude reduction (use MultiscaleEnhancementCommandFlags.LatitudeReduction)
The edge levels, edge coefficient, latitude levels and latitude coefficient values are available for advanced users. Using -1 would give the maximum enhancements.
This command supports 12 and 16-bit grayscale and 48 and 64-bit color images. Support for 12 and 16-bit grayscale and 48 and 64-bit color images is available only in the Document/Medical toolkits.
This command does not support 32-bit grayscale images.

For more information, refer to Changing Brightness and Contrast.

Multiscale Enhancement Function - Before

Multiscale Enhancement Function - After

View additional platform support for this Multiscale Enhancement function.

Example

Run the MultiscaleEnhancementCommand on an image.

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Core; 
 
 
public void MultiScaleEnhancementCommandExample() 
{ 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "Master.jpg")); 
 
   // Prepare the command 
   MultiscaleEnhancementCommand command = new MultiscaleEnhancementCommand(); 
   command.Contrast = 2000; 
   command.EdgeLevels = 4; 
   command.EdgeCoefficient = -1; 
   command.LatitudeLevels = 0; 
   command.LatitudeCoefficient = 0; 
   command.Type = MultiscaleEnhancementCommandType.Gaussian; 
   command.Flags = MultiscaleEnhancementCommandFlags.EdgeEnhancement; 
   // Apply multiscale enhancement 
   command.Run(image); 
 
} 
 
static class LEAD_VARS 
{ 
   public const string ImagesDir = @"C:\LEADTOOLS23\Resources\Images"; 
}

 
import java.io.File; 
import java.io.IOException; 
 
import org.junit.*; 
import org.junit.runner.JUnitCore; 
import org.junit.runner.Result; 
import org.junit.runner.notification.Failure; 
import static org.junit.Assert.*; 
 
import leadtools.RasterImage; 
import leadtools.RasterImageFormat; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.core.MultiscaleEnhancementCommand; 
import leadtools.imageprocessing.core.MultiscaleEnhancementCommandFlags; 
import leadtools.imageprocessing.core.MultiscaleEnhancementCommandType; 
 
 
public void multiScaleEnhancementCommandExample() { 
   // Load an image 
   final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.setThrowExceptionsOnInvalidImages(true); 
 
   RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "Master.jpg")); 
 
   // Prepare the command 
   MultiscaleEnhancementCommand command = new MultiscaleEnhancementCommand(); 
 
   command.setContrast(2000); 
   command.setEdgeLevels(4); 
   command.setEdgeCoefficient(-1); 
   command.setLatitudeLevels(0); 
   command.setLatitudeCoefficient(0); 
   command.setType(MultiscaleEnhancementCommandType.GAUSSIAN); 
   command.setFlags(MultiscaleEnhancementCommandFlags.EDGE_ENHANCEMENT.getValue()); 
   assertTrue(command.getLatitudeLevels() == 0); 
 
   String destFileName = combine(LEAD_VARS_IMAGES_DIR, "Product.jpg"); 
   codecs.save(image, destFileName, RasterImageFormat.BMP, 24); 
 
   // Apply multiscale enhancement 
   command.run(image); 
 
   image.dispose(); 
   codecs.dispose(); 
 
   assertTrue(new File(destFileName).exists()); 
   System.out.printf("File saved successfully to %s%n", destFileName); 
}