Package java.awt.image

Examples of java.awt.image.Kernel

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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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        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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        // 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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    public WritableRaster apply( WritableRaster image ) {
        if( ! enabled ) {
            return image;
        }
        Kernel kernel = new Kernel( convolveWidth, convolveHeight, data );
        ConvolveOp op = new ConvolveOp( kernel, ConvolveOp.EDGE_NO_OP, null );
        WritableRaster r = op.filter( image, null );
        return r;
    }
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        for (int i = 0; i < data.length; i++) {
            data[i] /= total;
        }       
       
        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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        ConvolveOp op = getGaussianBlurFilter1D(radius, true);
       
        // Copy of data, but faster than recalculating
        float[] data = op.getKernel().getKernelData(null);
       
        ConvolveOp op1 = new ConvolveOp(new Kernel(1, op.getKernel().getWidth(), data),
                ConvolveOp.EDGE_NO_OP, null);
       
        return new ConvolveOp[] { op, op1 };
    }
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                index++;
            }
        }
        for (int i = 0; i < rows*cols; i++)
            matrix[i] /= total;
        Kernel kernel = new Kernel(cols, rows, matrix);
        return kernel;
    }
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        }
        for (int i = 0; i < rows; i++)
            matrix[i] /= total;

        return new Kernel[] {
            new Kernel(rows, 1, matrix),
            new Kernel(1, rows, matrix),
        };
    }
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    /**
     * Construct a filter with the given 3x3 kernel.
     * @param matrix an array of 9 floats containing the kernel
     */
    public ConvolveFilter(float[] matrix) {
        this(new Kernel(3, 3, matrix));
    }
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