Example Image Derivative

• 

  Input image

• 

  X derivative

• 

  XYX derivative

Example of how to compute different image derivatives. The gradient (1st order derivative) is probably the important image derivative and is used as a first step when extracting many types of image features. The code below shows how gradient, Hessian (2nd order), and arbitrary image derivatives can be computed.

Example Code:

• ExampleImageDerivative.java

Concepts:

• Image Derivative
• Gradient
• Hessian

Example Code

/**
 * Example showing how to compute different image derivatives using built in functions.
 *
 * @author Peter Abeles
 */
public class ExampleImageDerivative {
	public static void main( String[] args ) {
		BufferedImage input = UtilImageIO.loadImageNotNull(UtilIO.pathExample("simple_objects.jpg"));

		// We will use floating point images here, but GrayU8 with GrayS16 for derivatives also works
		var grey = new GrayF32(input.getWidth(), input.getHeight());
		ConvertBufferedImage.convertFrom(input, grey);

		// First order derivative, also known as the gradient
		var derivX = new GrayF32(grey.width, grey.height);
		var derivY = new GrayF32(grey.width, grey.height);

		GImageDerivativeOps.gradient(DerivativeType.SOBEL, grey, derivX, derivY, BorderType.EXTENDED);

		// Second order derivative, also known as the Hessian
		var derivXX = new GrayF32(grey.width, grey.height);
		var derivXY = new GrayF32(grey.width, grey.height);
		var derivYY = new GrayF32(grey.width, grey.height);

		GImageDerivativeOps.hessian(DerivativeType.SOBEL, derivX, derivY, derivXX, derivXY, derivYY, BorderType.EXTENDED);

		// There's also a built in function for computing arbitrary derivatives
		AnyImageDerivative<GrayF32, GrayF32> derivative =
				GImageDerivativeOps.createAnyDerivatives(DerivativeType.SOBEL, GrayF32.class, GrayF32.class);

		// the boolean sequence indicates if its an X or Y derivative
		derivative.setInput(grey);
		GrayF32 derivXYX = derivative.getDerivative(true, false, true);

		// Visualize the results
		var gui = new ListDisplayPanel();
		gui.addImage(ConvertBufferedImage.convertTo(grey, null), "Input Grey");
		gui.addImage(VisualizeImageData.colorizeSign(derivX, null, -1), "Sobel X");
		gui.addImage(VisualizeImageData.colorizeSign(derivY, null, -1), "Sobel Y");
		// Use colors to show X and Y derivatives in one image. Looks pretty.
		gui.addImage(VisualizeImageData.colorizeGradient(derivX, derivY, -1, null), "Sobel X and Y");
		gui.addImage(VisualizeImageData.colorizeSign(derivXX, null, -1), "Sobel XX");
		gui.addImage(VisualizeImageData.colorizeSign(derivXY, null, -1), "Sobel XY");
		gui.addImage(VisualizeImageData.colorizeSign(derivYY, null, -1), "Sobel YY");
		gui.addImage(VisualizeImageData.colorizeSign(derivXYX, null, -1), "Sobel XYX");

		ShowImages.showWindow(gui, "Image Derivatives", true);
	}
}