AdaptiveContrastCommand Class

Summary

Performs adaptive contrast enhancement (ACE) to regions that are originally low in contrast. This command is available in the Medical and above toolkits.

Syntax

Objective-C

C++/CLI

Java

Python

public class AdaptiveContrastCommand : RasterCommand

@interface LTAdaptiveContrastCommand : LTRasterCommand

public class AdaptiveContrastCommand 
    extends RasterCommand

public ref class AdaptiveContrastCommand : public RasterCommand

class AdaptiveContrastCommand(RasterCommand):

Remarks

Adaptive contrast enhancement (ACE) adjusts image contrast by giving more contrast to areas which are originally low in contrast. This is different from histogram-based techniques which are based on all image pixels (the histogram itself).
Local histogram equalization is another technique that can be used to reveal detail of areas, since it depends on area pixels only. Use LocalHistogramEqualizeCommand to perform a local histogram equalization.
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.

Adaptive Contrast Function - Before

Adaptive Contrast Function - After

View additional platform support for this Adaptive Contrast function.

Example

Run the AdaptiveContrastCommand on an image.

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Color; 
 
 
public void AdaptiveContrastCommandExample() 
{ 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "sample1.cmp")); 
 
   // Prepare the command 
   AdaptiveContrastCommand command = new AdaptiveContrastCommand(); 
   command.Amount = 200; 
   command.Dimension = 9; 
   // Apply Adaptive Contrast Enhancement. 
   command.Run(image); 
   codecs.Save(image, Path.Combine(LEAD_VARS.ImagesDir, "Result.jpg"), RasterImageFormat.Jpeg, 24); 
} 
 
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.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.color.*; 
 
 
public void adaptiveContrastCommandExample() { 
 
    final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
 
    // Load an image 
    RasterCodecs codecs = new RasterCodecs(); 
    codecs.setThrowExceptionsOnInvalidImages(true); 
 
    RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "sample1.cmp")); 
 
    // Prepare the command 
    AdaptiveContrastCommand command = new AdaptiveContrastCommand(); 
    command.setAmount(200); 
    command.setDimension(9); 
 
    // Apply Adaptive Contrast Enhancement 
    command.run(image); 
    codecs.save(image, combine(LEAD_VARS_IMAGES_DIR, "Results.jpg"), RasterImageFormat.JPEG, 24); 
 
    assertTrue(new File(combine(LEAD_VARS_IMAGES_DIR, "Results.jpg")).exists()); 
    System.out.println("Command run and image exported to: " + combine(LEAD_VARS_IMAGES_DIR, "Results.jpg")); 
 
}