Examples of java.awt.image.Kernel

java.awt.image.Kernel
The Kernel class defines a matrix that describes how a specified pixel and its surrounding pixels affect the value computed for the pixel's position in the output image of a filtering operation. The X origin and Y origin indicate the kernel matrix element that corresponds to the pixel position for which an output value is being computed. @see ConvolveOp @version 10 Feb 1997

        float[] kernel = new float[blurMagnitude * blurMagnitude];
        for (int i = 0, n = kernel.length; i < n; i++) {
            kernel[i] = 1f / n;
        }


        ConvolveOp blur = new ConvolveOp(new Kernel(blurMagnitude, blurMagnitude,
            kernel), ConvolveOp.EDGE_NO_OP, null);
        bufferedImage = blur.filter(bufferedImage, null);


        graphics.drawImage(bufferedImage, 0, 0, null);

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        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));
    }

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        // build the convolve filter
        ConvolveMatrixRable convolve = new ConvolveMatrixRable8Bit(pad);
        for (int i = 0; i < kernelMatrix.length; i++) {
            kernelMatrix[i] /= divisor;
        }
        convolve.setKernel(new Kernel(orderXY[0], orderXY[1], kernelMatrix));
        convolve.setTarget(new Point(targetXY[0], targetXY[1]));
        convolve.setBias(bias);
        convolve.setEdgeMode(padMode);
        convolve.setKernelUnitLength(kernelUnitLength);
        convolve.setPreserveAlpha(preserveAlpha);

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        return kernelData;
    }


    private Kernel makeQualityKernelX(int len) {
        return new Kernel(len, 1, computeQualityKernelData(len, stdDevX));
    }

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    private Kernel makeQualityKernelX(int len) {
        return new Kernel(len, 1, computeQualityKernelData(len, stdDevX));
    }


    private Kernel makeQualityKernelY(int len) {
        return new Kernel(1, len, computeQualityKernelData(len, stdDevY));
    }

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        if (filterDesc == null) {
            //
            // First time filter is converted: create its corresponding
            // SVG filter
            //
            Kernel kernel = convolveOp.getKernel();
            Element filterDef =
                domFactory.createElementNS(SVG_NAMESPACE_URI, SVG_FILTER_TAG);
            Element feConvolveMatrixDef =
                domFactory.createElementNS(SVG_NAMESPACE_URI,
                                           SVG_FE_CONVOLVE_MATRIX_TAG);


            // Convert the kernel size
            feConvolveMatrixDef.setAttributeNS(null, SVG_ORDER_ATTRIBUTE,
                                             kernel.getWidth() + SPACE +
                                             kernel.getHeight());


            // Convert the kernel values
            StringBuffer kernelMatrixBuf = new StringBuffer();
            float data[] = kernel.getKernelData(null);
            for(int i=0; i<data.length; i++){
                kernelMatrixBuf.append(doubleString(data[i]));
                kernelMatrixBuf.append(SPACE);
            }

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    Graphics2D big = src.createGraphics();
    AffineTransform affineTransform = new AffineTransform();
    big.drawImage(img, affineTransform, element.jGetFrame());
    
    Kernel kernel = new Kernel(matrix.getColumns(),matrix.getRows(), convert2DTo1D(matrix,matrix.getColumns(),matrix.getRows()));
    ConvolveOp con = new ConvolveOp(kernel);


    con.filter(src,bufferedImage);


  }

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    for (int i = 0; i < data.length; i++) {
      data[i] /= total;
    }
    
    // create filter kernel
    Kernel kernel = null;
    if (horizontal) {
      kernel = new Kernel(size, 1, data);
    } else {
      kernel = new Kernel(1, size, data);
    }
    return new ConvolveOp(kernel, ConvolveOp.EDGE_NO_OP, null);
  }

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        // build the convolve filter
        ConvolveMatrixRable convolve = new ConvolveMatrixRable8Bit(pad);
        for (int i = 0; i < kernelMatrix.length; i++) {
            kernelMatrix[i] /= divisor;
        }
        convolve.setKernel(new Kernel(orderXY[0], orderXY[1], kernelMatrix));
        convolve.setTarget(new Point(targetXY[0], targetXY[1]));
        convolve.setBias(bias);
        convolve.setEdgeMode(padMode);
        convolve.setKernelUnitLength(kernelUnitLength);
        convolve.setPreserveAlpha(preserveAlpha);

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    }
 
    int size = radius * 2 + 1;
    float[] data = table(radius, size);
 
    Kernel kernel = null;
    if(horizontal){
      kernel = new Kernel(size,1,data);
    }
    else{
      kernel = new Kernel(1,size,data);
    }
 
    return new ConvolveOp(kernel, ConvolveOp.EDGE_NO_OP, null);
  }

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