Examples of ConvolveOp

ae.java.awt.image.ConvolveOp
This class implements a convolution from the source to the destination. Convolution using a convolution kernel is a spatial operation that computes the output pixel from an input pixel by multiplying the kernel with the surround of the input pixel. This allows the output pixel to be affected by the immediate neighborhood in a way that can be mathematically specified with a kernel.
This class operates with BufferedImage data in which color components are premultiplied with the alpha component. If the Source BufferedImage has an alpha component, and the color components are not premultiplied with the alpha component, then the data are premultiplied before being convolved. If the Destination has color components which are not premultiplied, then alpha is divided out before storing into the Destination (if alpha is 0, the color components are set to 0). If the Destination has no alpha component, then the resulting alpha is discarded after first dividing it out of the color components.
Rasters are treated as having no alpha channel. If the above treatment of the alpha channel in BufferedImages is not desired, it may be avoided by getting the Raster of a source BufferedImage and using the filter method of this class which works with Rasters.
If a RenderingHints object is specified in the constructor, the color rendering hint and the dithering hint may be used when color conversion is required.
Note that the Source and the Destination may not be the same object. @see Kernel @see ae.java.awt.RenderingHints#KEY_COLOR_RENDERING @see ae.java.awt.RenderingHints#KEY_DITHERING
java.awt.image.ConvolveOp
This class implements a convolution from the source to the destination. Convolution using a convolution kernel is a spatial operation that computes the output pixel from an input pixel by multiplying the kernel with the surround of the input pixel. This allows the output pixel to be affected by the immediate neighborhood in a way that can be mathematically specified with a kernel.
This class operates with BufferedImage data in which color components are premultiplied with the alpha component. If the Source BufferedImage has an alpha component, and the color components are not premultiplied with the alpha component, then the data are premultiplied before being convolved. If the Destination has color components which are not premultiplied, then alpha is divided out before storing into the Destination (if alpha is 0, the color components are set to 0). If the Destination has no alpha component, then the resulting alpha is discarded after first dividing it out of the color components.
Rasters are treated as having no alpha channel. If the above treatment of the alpha channel in BufferedImages is not desired, it may be avoided by getting the Raster of a source BufferedImage and using the filter method of this class which works with Rasters.
If a RenderingHints object is specified in the constructor, the color rendering hint and the dithering hint may be used when color conversion is required.
Note that the Source and the Destination may not be the same object. @version 10 Feb 1997 @see Kernel @see java.awt.RenderingHints#KEY_COLOR_RENDERING @see java.awt.RenderingHints#KEY_DITHERING

Examples of ae.java.awt.image.ConvolveOp

                retRaster =  dst;
            }
            break;


          case CONVOLVE_OP:
            ConvolveOp cOp = (ConvolveOp) op;
            if (convolveRaster(src, dst,
                               cOp.getKernel(), cOp.getEdgeCondition()) > 0) {
                retRaster = dst;
            }
            break;


          default:

View Full Code Here

Examples of java.awt.image.ConvolveOp

    }
    
    private void sharpen() {
        img = picture.getImage();
        BufferedImage src = Utilities.toBufferedImage(new DcImageIcon(img));
        BufferedImageOp op = new ConvolveOp(
                new Kernel(3, 3, new float[] { 0.0f, -0.75f, 0.0f, -0.75f, 4.0f, 
                                              -0.75f, 0.0f, -0.75f, 0.0f }));
        update(op, src);
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp

    }
    
    private void blur() {
        img = picture.getImage();
        BufferedImage src = Utilities.toBufferedImage(new DcImageIcon(img));
        BufferedImageOp op = new ConvolveOp(
                new Kernel(3, 3, new float[] {.1111f, .1111f, .1111f, .1111f, .1111f, 
                                              .1111f, .1111f, .1111f, .1111f, }));
        update(op, src);
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp

        float[] data = new float[size * size];
        float value = 1 / (float) (size * size);
        for (int i = 0; i < data.length; i++) {
            data[i] = value;
        }
        return new ConvolveOp(new Kernel(size, size, data));
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp


        float ninth = 1.0f / 9.0f;
        float[] blurKernel = {ninth, ninth, ninth, ninth, ninth, ninth, ninth,
            ninth, ninth};
        convolutionKernel = new Kernel(3, 3, blurKernel);
        blurOperator = new ConvolveOp(convolutionKernel, ConvolveOp.EDGE_NO_OP,
                renderingHints);
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp

        float[] data = new float[size * size];
        float value = 1.0f / (float) (size * size);
        for (int i = 0; i < data.length; i++) {
            data[i] = value;
        }
        return new ConvolveOp(new Kernel(size, size, data));
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp

        float[] data = new float[size * size];
        float value = 1.0f / (float) (size * size);
        for (int i = 0; i < data.length; i++) {
            data[i] = value;
        }
        return new ConvolveOp(new Kernel(size, size, data));
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp

        g2.dispose();
        
        // 1.5 second vs 0.3 second
//        long start = System.currentTimeMillis();
        image = changeImageWidth(image, image.getWidth() / 2);
        ConvolveOp gaussianFilter = getGaussianBlurFilter(BLUR_SIZE, true);
        image = gaussianFilter.filter(image, null);
        gaussianFilter = getGaussianBlurFilter(BLUR_SIZE, false);
        image = gaussianFilter.filter(image, null);
        ColorTintFilter colorMixFilter = new ColorTintFilter(Color.WHITE, 0.4f);
        image = colorMixFilter.filter(image, null);
        image = changeImageWidth(image, image.getWidth() * 2);
//        System.out.println("time = " +
//                           ((System.currentTimeMillis() - start) / 1000.0f));

View Full Code Here

Examples of java.awt.image.ConvolveOp

        if (horizontal) {
            kernel = new Kernel(size, 1, data);
        } else {
            kernel = new Kernel(1, size, data);
        }
        return new ConvolveOp(kernel, ConvolveOp.EDGE_NO_OP, null);
    }

View Full Code Here

Examples of java.awt.image.ConvolveOp

    }


    private void updateKernel() {
        float[] kernel = new float[kernelSize * kernelSize];
        Arrays.fill(kernel, blurIntensity);
        blur = new ConvolveOp(new Kernel(kernelSize, kernelSize, kernel));
    }

View Full Code Here

0 1 2 3 4 5

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.