Example Planar Image - Revision history

Peter at 23:08, 17 January 2022

2022-01-17T23:08:29Z

Peter at 19:01, 12 July 2021

2021-07-12T19:01:40Z

Peter at 02:25, 22 December 2020

2020-12-22T02:25:00Z

← Older revision		Revision as of 02:25, 22 December 2020
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	In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.33/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

	Concepts:		Concepts:
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	<syntaxhighlight lang="java">		<syntaxhighlight lang="java">
	/**		/**
	* <p>
	* {@link Planar} images are one way in which color images can be stored and manipulated inside		* {@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}.		* 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		* This is unlike the more common interleaved format where color information is stored in adjacent bytes in
	* the same image.		* the same image.
	* </p>
	*		*
	* <p>
	* The main advantage of {@link Planar} is the ease at which gray scale operations can be applied to each		* 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,		* 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		* 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.		* situations for some scientific applications where processing each band independently makes more sense.
	* </p>
	*		*
	* @author Peter Abeles		* @author Peter Abeles
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	public static void independent( BufferedImage input ) {		public static void independent( BufferedImage input ) {
	// convert the BufferedImage into a Planar		// convert the BufferedImage into a Planar
	Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input, null, true, GrayU8.class);

	// declare the output blurred image		// declare the output blurred image
	Planar<GrayU8> blurred = image.createSameShape();		Planar<GrayU8> blurred = image.createSameShape();

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

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

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

	int x = 10, y = 10;		int x = 10, y = 10;

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

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

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

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	public static void convertToGray( BufferedImage input ) {		public static void convertToGray( BufferedImage input ) {
	// convert the BufferedImage into a Planar		// convert the BufferedImage into a Planar
	Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input, null, true, GrayU8.class);

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

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

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

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

	gui.addImage(outputAve,"Gray Averaged");		gui.addImage(outputAve, "Gray Averaged");
	gui.addImage(outputWeighted,"Gray Weighted");		gui.addImage(outputWeighted, "Gray Weighted");
	gui.addImage(outputBand0,"Band 0");		gui.addImage(outputBand0, "Band 0");
	}		}

	public static void main( String ~~args~~[] ) {		public static void main( String[] args ) {
	BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("apartment_building_02.jpg"));		BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("apartment_building_02.jpg"));

	~~// Uncomment lines below to run each example~~

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

	ShowImages.showWindow(gui,"Color Planar Image Examples",true);		ShowImages.showWindow(gui, "Color Planar Image Examples", true);
	}		}
	}		}
	</syntaxhighlight>		</syntaxhighlight>

Peter at 14:36, 15 March 2019

2019-03-15T14:36:28Z

← Older revision		Revision as of 14:36, 15 March 2019
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	In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.33/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

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

Peter at 16:01, 17 August 2017

2017-08-17T16:01:04Z

Peter at 23:46, 1 December 2016

2016-12-01T23:46:57Z

← Older revision		Revision as of 23:46, 1 December 2016
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	In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

	Concepts:		Concepts:
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	GPixelMath.averageBand(image, gray);		GPixelMath.averageBand(image, gray);
	BufferedImage outputAve = ConvertBufferedImage.convertTo(gray,null);		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		// create an output image just from the first band
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	gui.addImage(outputAve,"Gray Averaged");		gui.addImage(outputAve,"Gray Averaged");
			gui.addImage(outputWeighted,"Gray Weighted");
	gui.addImage(outputBand0,"Band 0");		gui.addImage(outputBand0,"Band 0");
	}		}

Peter: Peter moved page Example MultiSpectral to Example Planar Image

2016-03-28T04:56:54Z

Peter moved page Example MultiSpectral to Example Planar Image

← Older revision	Revision as of 04:56, 28 March 2016
(No difference)

Peter at 04:56, 28 March 2016

2016-03-28T04:56:23Z

← Older revision		Revision as of 04:56, 28 March 2016
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	The class ~~MultiSpectral~~ is used to store color images where each color or band is stored as an independent gray scale image. This allows for each band in the image to be independently processed or modified easily. MultiSpectral images are different from how color images are most commonly stored, which is in an interleaved format. The advantage of using independent gray scale images for each band is that they can be easily processed by algorithms written for ~~ImageSingleBand~~.		The class Planar is used to store color images where each color or band is stored as an independent gray scale image. The advantage of using independent gray scale images for each band is that they can be easily processed by algorithms written for ImageGray.

	In the example code below it is demonstrated how to convert ~~MultiSpectral~~ to and from BufferedImages, how to process each band ~~in a MultiSpectral~~ independently, and how to access the values ~~of pixels inside the MultiSpectral image~~.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.22/examples/src/boofcv/examples/imageprocessing/~~ExampleMultiSpectralImages~~.java ~~ExampleMultiSpectralImages~~.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

	Concepts:		Concepts:
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	= Example Code =		= Example Code =

			<syntaxhighlight lang="java">
			/**
			* <p>
			* {@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.
			* </p>
			*
			* <p>
			* 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.
			* </p>
			*
			* @author Peter Abeles
			*/
			public class ExamplePlanarImages {

	~~<syntaxhighlight lang="java">~~
	public static ListDisplayPanel gui = new ListDisplayPanel();		public static ListDisplayPanel gui = new ListDisplayPanel();

	/**		/**
	* Many operations designed to only work on {@link ~~boofcv.struct.image.ImageSingleBand~~} can be applied		* Many operations designed to only work on {@link ImageGray} can be applied
	* to a ~~MultiSpectral~~ image by feeding in each band one at a time.		* to a Planar image by feeding in each band one at a time.
	*/		*/
	public static void independent( BufferedImage input ) {		public static void independent( BufferedImage input ) {
	// convert the BufferedImage into a ~~MultiSpectral~~		// convert the BufferedImage into a Planar
	~~MultiSpectral~~<~~ImageUInt8~~> image = ConvertBufferedImage.convertFromMulti(input,null,true,~~ImageUInt8~~.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromMulti(input,null,true,GrayU8.class);

	// declare the output blurred image		// declare the output blurred image
	~~MultiSpectral~~<~~ImageUInt8~~> blurred = image.createSameShape();		Planar<GrayU8> blurred = image.createSameShape();

	// Apply Gaussian blur to each band in the image		// Apply Gaussian blur to each band in the image
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	/**		/**
	* Values of pixels can be read and modified by accessing the internal {@link ~~boofcv.struct.image.ImageSingleBand~~}.		* Values of pixels can be read and modified by accessing the internal {@link ImageGray}.
	*/		*/
	public static void pixelAccess( BufferedImage input ) {		public static void pixelAccess( BufferedImage input ) {
	// convert the BufferedImage into a ~~MultiSpectral~~		// convert the BufferedImage into a Planar
	~~MultiSpectral~~<~~ImageUInt8~~> image = ConvertBufferedImage.convertFromMulti(input,null,true,~~ImageUInt8~~.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromMulti(input,null,true,GrayU8.class);

	int x = 10, y = 10;		int x = 10, y = 10;
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	/**		/**
	* There is no real perfect way that everyone agrees on for converting color images into gray scale		* 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 ~~MultiSpectral~~ image into a gray scale image are shown		* images. Two examples of how to convert a Planar image into a gray scale image are shown
	* in this example.		* in this example.
	*/		*/
	public static void convertToGray( BufferedImage input ) {		public static void convertToGray( BufferedImage input ) {
	// convert the BufferedImage into a ~~MultiSpectral~~		// convert the BufferedImage into a Planar
	~~MultiSpectral~~<~~ImageUInt8~~> image = ConvertBufferedImage.convertFromMulti(input,null,true,~~ImageUInt8~~.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromMulti(input,null,true,GrayU8.class);

	~~ImageUInt8~~ gray = new ~~ImageUInt8~~( image.width,image.height);		GrayU8 gray = new GrayU8( image.width,image.height);

	// creates a gray scale image by averaging intensity value across pixels		// creates a gray scale image by averaging intensity value across pixels
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	// Uncomment lines below to run each example		// Uncomment lines below to run each example

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

	ShowImages.showWindow(gui,"~~Multi Spectral~~ Examples",true);		ShowImages.showWindow(gui,"Color Planar Image Examples",true);
	}		}
			}
	</syntaxhighlight>		</syntaxhighlight>

Peter at 04:06, 5 March 2016

2016-03-05T04:06:25Z

← Older revision		Revision as of 04:06, 5 March 2016
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	In the example code below it is demonstrated how to convert MultiSpectral to and from BufferedImages, how to process each band in a MultiSpectral independently, and how to access the values of pixels inside the MultiSpectral image.		In the example code below it is demonstrated how to convert MultiSpectral to and from BufferedImages, how to process each band in a MultiSpectral independently, and how to access the values of pixels inside the MultiSpectral image.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/imageprocessing/ExampleMultiSpectralImages.java ExampleMultiSpectralImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.22/examples/src/boofcv/examples/imageprocessing/ExampleMultiSpectralImages.java ExampleMultiSpectralImages.java]

	Concepts:		Concepts:
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	<syntaxhighlight lang="java">		<syntaxhighlight lang="java">
			public static ListDisplayPanel gui = new ListDisplayPanel();

	/**		/**
	* Many operations designed to only work on {@link boofcv.struct.image.ImageSingleBand} can be applied		* Many operations designed to only work on {@link boofcv.struct.image.ImageSingleBand} can be applied
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	BufferedImage output = new BufferedImage(image.width,image.height,input.getType());		BufferedImage output = new BufferedImage(image.width,image.height,input.getType());
	ConvertBufferedImage.convertTo(blurred, output,true);		ConvertBufferedImage.convertTo(blurred, output,true);
	~~ShowImages~~.~~showWindow~~(input,"Input");
	~~ShowImages~~.~~showWindow~~(output,"~~Output~~");		gui.addImage(input,"Input");
			gui.addImage(output,"Gaussian Blur");
	}		}

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	// convert the BufferedImage into a MultiSpectral		// convert the BufferedImage into a MultiSpectral
	MultiSpectral<ImageUInt8> image = ConvertBufferedImage.convertFromMulti(input,null,true,ImageUInt8.class);		MultiSpectral<ImageUInt8> image = ConvertBufferedImage.convertFromMulti(input,null,true,ImageUInt8.class);

	ImageUInt8 gray = new ImageUInt8( image.width,image.height);		ImageUInt8 gray = new ImageUInt8( image.width,image.height);

	// creates a gray scale image by averaging intensity value across pixels		// creates a gray scale image by averaging intensity value across pixels
	GPixelMath.averageBand(image, gray);		GPixelMath.averageBand(image, gray);
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	BufferedImage outputBand0 = ConvertBufferedImage.convertTo(image.getBand(0),null);		BufferedImage outputBand0 = ConvertBufferedImage.convertTo(image.getBand(0),null);

	~~ShowImages~~.~~showWindow~~(outputAve,"~~Average~~");		gui.addImage(outputAve,"Gray Averaged");
	~~ShowImages~~.~~showWindow~~(outputBand0,"Band 0");		gui.addImage(outputBand0,"Band 0");
	}		}

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	ExampleMultiSpectralImages.independent(input);		ExampleMultiSpectralImages.independent(input);
	// ExampleMultiSpectralImages.pixelAccess(input);		ExampleMultiSpectralImages.pixelAccess(input);
	// ExampleMultiSpectralImages.convertToGray(input);		ExampleMultiSpectralImages.convertToGray(input);

			ShowImages.showWindow(gui,"Multi Spectral Examples",true);
	}		}
	</syntaxhighlight>		</syntaxhighlight>

Peter at 15:28, 9 November 2015

2015-11-09T15:28:36Z

← Older revision		Revision as of 15:28, 9 November 2015
Line 3:		Line 3:
	In the example code below it is demonstrated how to convert MultiSpectral to and from BufferedImages, how to process each band in a MultiSpectral independently, and how to access the values of pixels inside the MultiSpectral image.		In the example code below it is demonstrated how to convert MultiSpectral to and from BufferedImages, how to process each band in a MultiSpectral independently, and how to access the values of pixels inside the MultiSpectral image.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/imageprocessing/ExampleMultiSpectralImages.java ExampleMultiSpectralImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/imageprocessing/ExampleMultiSpectralImages.java ExampleMultiSpectralImages.java]

	Concepts:		Concepts:
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	ConvertBufferedImage.convertTo(blurred, output,true);		ConvertBufferedImage.convertTo(blurred, output,true);
	ShowImages.showWindow(input,"Input");		ShowImages.showWindow(input,"Input");
	ShowImages.showWindow(output,"~~Ouput~~");		ShowImages.showWindow(output,"Output");
	}		}

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	public static void main( String args[] ) {		public static void main( String args[] ) {
	BufferedImage input = UtilImageIO.loadImage("~~../data/applet/~~apartment_building_02.jpg");		BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("apartment_building_02.jpg"));

	// Uncomment lines below to run each example		// Uncomment lines below to run each example

← Older revision		Revision as of 23:08, 17 January 2022
Line 1:		Line 1:
	The class Planar is used to store color images where each color or band is stored as an independent gray scale image. The advantage of using independent gray scale images for each band is that they can be easily processed by algorithms written for ImageGray.		The class Planar is used to store color images where each color or band is stored as an independent gray scale image. The advantage of using independent gray scale images for each band is that they can be easily processed by algorithms written for ImageGray.

	In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.40/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

	Concepts:		Concepts:
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	// Declare the BufferedImage manually to ensure that the color bands have the same ordering on input		// Declare the BufferedImage manually to ensure that the color bands have the same ordering on input
	// and output		// and output
	~~BufferedImage~~ output = new BufferedImage(image.width, image.height, input.getType());		var output = new BufferedImage(image.width, image.height, input.getType());
	ConvertBufferedImage.convertTo(blurred, output, true);		ConvertBufferedImage.convertTo(blurred, output, true);

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	Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input, null, true, GrayU8.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input, null, true, GrayU8.class);

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

	// creates a gray scale image by averaging intensity value across pixels		// creates a gray scale image by averaging intensity value across pixels
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	public static void main( String[] args ) {		public static void main( String[] args ) {
	BufferedImage input = UtilImageIO.~~loadImage~~(UtilIO.pathExample("apartment_building_02.jpg"));		BufferedImage input = UtilImageIO.loadImageNotNull(UtilIO.pathExample("apartment_building_02.jpg"));

	ExamplePlanarImages.independent(input);		ExamplePlanarImages.independent(input);

← Older revision		Revision as of 19:01, 12 July 2021
Line 3:		Line 3:
	In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

	Concepts:		Concepts:
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	/**		/**
	* {@link Planar} images are one way in which color images can be stored and manipulated inside		* {@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}.		* 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		* This is unlike the more common interleaved format where color information is stored in adjacent bytes in
	* the same image.		* the same image.
	*		*
	* The main advantage of {@link Planar} is the ease at which gray scale operations can be applied to each		* 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,		* 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		* 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.		* situations for some scientific applications where processing each band independently makes more sense.
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	/**		/**
	* There is no real perfect way that everyone agrees on for converting color images into gray scale		* 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		* images. Two examples of how to convert a Planar image into a gray scale image are shown
	* in this example.		* in this example.
	*/		*/

← Older revision		Revision as of 16:01, 17 August 2017
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	In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.		In the example code below it is demonstrated how to convert Planar to and from BufferedImages, how to process each band independently, and how to access the pixel values.

	Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]		Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/imageprocessing/ExamplePlanarImages.java ExamplePlanarImages.java]

	Concepts:		Concepts:
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	public static void independent( BufferedImage input ) {		public static void independent( BufferedImage input ) {
	// convert the BufferedImage into a Planar		// convert the BufferedImage into a Planar
	Planar<GrayU8> image = ConvertBufferedImage.~~convertFromMulti~~(input,null,true,GrayU8.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);

	// declare the output blurred image		// declare the output blurred image
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	public static void pixelAccess( BufferedImage input ) {		public static void pixelAccess( BufferedImage input ) {
	// convert the BufferedImage into a Planar		// convert the BufferedImage into a Planar
	Planar<GrayU8> image = ConvertBufferedImage.~~convertFromMulti~~(input,null,true,GrayU8.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);

	int x = 10, y = 10;		int x = 10, y = 10;
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	public static void convertToGray( BufferedImage input ) {		public static void convertToGray( BufferedImage input ) {
	// convert the BufferedImage into a Planar		// convert the BufferedImage into a Planar
	Planar<GrayU8> image = ConvertBufferedImage.~~convertFromMulti~~(input,null,true,GrayU8.class);		Planar<GrayU8> image = ConvertBufferedImage.convertFromPlanar(input,null,true,GrayU8.class);

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