MinimumCommand Class

Summary

Dilates dark objects by the specified amount. This command is available in the Document/Medical toolkits.

Syntax

Objective-C

C++/CLI

Java

Python

public class MinimumCommand : RasterCommand

@interface LTMinimumCommand : LTRasterCommand

public class MinimumCommand 
    extends RasterCommand

public ref class MinimumCommand : public RasterCommand

class MinimumCommand(RasterCommand):

Remarks

This command can process the whole image or a region of the image.
The effect can be controlled by specifying the size of the neighborhood that is used for calculating each pixel value. For example, for 8x8, set the Dimension property to 8 or pass 8 for the dimension parameter of the Constructor. Each pixel is replaced with the minimum value of its neighborhood.
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.
This command supports signed/unsigned data images.

For more information, refer to Removing Noise.

Minimum Function - Before

Minimum Function - After

View additional platform support for this Minimum function.

Example

Run the MinimumCommand on an image with a neighborhood Dimensions = 3x3 pixels.

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Core; 
 
public void MinimumCommandExample() 
{ 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, @"ImageProcessingDemo\NaturalFruits.jpg")); 
 
   // Prepare the command 
   MinimumCommand command = new MinimumCommand(); 
   //Apply the Minimum filter. 
   command.Dimension = 3; 
   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.assertTrue; 
 
import leadtools.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.core.MinimumCommand; 
 
 
public void minimumCommandExample() { 
   final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
   final String outputFileName = combine(LEAD_VARS_IMAGES_DIR, "Result.jpg"); 
 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.setThrowExceptionsOnInvalidImages(true); 
 
   RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "NaturalFruits.jpg")); 
 
   // Prepare the command 
   MinimumCommand command = new MinimumCommand(); 
 
   // Apply the Minimum filter. 
   command.setDimension(3); 
   command.run(image); 
   codecs.save(image, outputFileName, RasterImageFormat.JPEG, 0); 
 
   assertTrue(new File(outputFileName).exists()); 
   System.out.println("Command run and image saved to " + outputFileName); 
}