boofcv.examples.imageprocessing.ExamplePlanarImages Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of examples Show documentation
BoofCV is an open source Java library for real-time computer vision and robotics applications.
There is a newer version: 1.1.6
/*
 * Copyright (c) 2011-2019, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package boofcv.examples.imageprocessing;

import boofcv.alg.color.ColorRgb;
import boofcv.alg.filter.blur.BlurImageOps;
import boofcv.core.image.ConvertImage;
import boofcv.gui.ListDisplayPanel;
import boofcv.gui.image.ShowImages;
import boofcv.io.UtilIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.io.image.UtilImageIO;
import boofcv.struct.image.GrayU8;
import boofcv.struct.image.ImageGray;
import boofcv.struct.image.Planar;

import java.awt.image.BufferedImage;

/**
 * 
 * {@link Planar} images are one way in which color images can be stored and manipulated inside
 * of BoofCV.  Inside of a Planar image each color band is stored as an independent {@link ImageGray}.
 * This is unlike the more common interleaved format where color information is stored in adjacent bytes in
 * the same image.
 * 
 *
 * 
 * The main advantage of {@link Planar} is the ease at which gray scale operations can be applied to each
 * band independently with no additional code.  This is particularly useful in a library,
 * such as BoofCV, which is heavily focused on gray scale image processing and computer vision. The are also
 * situations for some scientific applications where processing each band independently makes more sense.
 * 
 *
 * @author Peter Abeles
 */
public class ExamplePlanarImages {

	public static ListDisplayPanel gui = new ListDisplayPanel();

	/**
	 * Many operations designed to only work on {@link ImageGray} can be applied
	 * to a Planar image by feeding in each band one at a time.
	 */
	public static void independent( BufferedImage input ) {
		// convert the BufferedImage into a Planar
		Planar image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);

		// declare the output blurred image
		Planar blurred = image.createSameShape();
		
		// Apply Gaussian blur to each band in the image
		for( int i = 0; i < image.getNumBands(); i++ ) {
			// note that the generalized version of BlurImageOps is not being used, but the type
			// specific version.
			BlurImageOps.gaussian(image.getBand(i),blurred.getBand(i),-1,5,null);
		}
		
		// Declare the BufferedImage manually to ensure that the color bands have the same ordering on input
		// and output
		BufferedImage output = new BufferedImage(image.width,image.height,input.getType());
		ConvertBufferedImage.convertTo(blurred, output,true);

		gui.addImage(input,"Input");
		gui.addImage(output,"Gaussian Blur");
	}

	/**
	 * Values of pixels can be read and modified by accessing the internal {@link ImageGray}.
	 */
	public static void pixelAccess(  BufferedImage input ) {
		// convert the BufferedImage into a Planar
		Planar image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);

		int x = 10, y = 10;

		// to access a pixel you first access the gray image for the each band
		for( int i = 0; i < image.getNumBands(); i++ )
			System.out.println("Original "+i+" = "+image.getBand(i).get(x,y));

		// change the value in each band
		for( int i = 0; i < image.getNumBands(); i++ )
			image.getBand(i).set(x, y, 100 + i);

		// to access a pixel you first access the gray image for the each band
		for( int i = 0; i < image.getNumBands(); i++ )
			System.out.println("Result   "+i+" = "+image.getBand(i).get(x,y));
	}

	/**
	 * There is no real perfect way that everyone agrees on for converting color images into gray scale
	 * images.  Two examples of how to convert a Planar image into a gray scale image are shown
	 * in this example.
	 */
	public static void convertToGray( BufferedImage input ) {
		// convert the BufferedImage into a Planar
		Planar image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);

		GrayU8 gray = new GrayU8( image.width,image.height);

		// creates a gray scale image by averaging intensity value across pixels
		ConvertImage.average(image, gray);
		BufferedImage outputAve = ConvertBufferedImage.convertTo(gray,null);

		// convert to gray scale but weigh each color band based on how human vision works
		ColorRgb.rgbToGray_Weighted(image, gray);
		BufferedImage outputWeighted = ConvertBufferedImage.convertTo(gray,null);

		// create an output image just from the first band
		BufferedImage outputBand0 = ConvertBufferedImage.convertTo(image.getBand(0),null);

		gui.addImage(outputAve,"Gray Averaged");
		gui.addImage(outputWeighted,"Gray Weighted");
		gui.addImage(outputBand0,"Band 0");
	}
	
	public static void main( String args[] ) {
		BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("apartment_building_02.jpg"));

		// Uncomment lines below to run each example

		ExamplePlanarImages.independent(input);
		ExamplePlanarImages.pixelAccess(input);
		ExamplePlanarImages.convertToGray(input);

		ShowImages.showWindow(gui,"Color Planar Image Examples",true);
	}
}