newResult

public class Image2D {

    static BufferedImage imageInput;
    static BufferedImage imageOutput;

    public static BufferedImage convolution(float kernel[][], int wigth, int height, int sizeKernel, int kernelXY) {


        imageOutput = imageInput.getSubimage(0, 0, wigth, height);
        int r = 0, g = 0, b = 0;
        RGB c = new RGB();
        int pixels[][] = new int[wigth][height]; // contian a pixels

        // calculate imageInput --------------------
        for (int i = 0; i < wigth; i++) {
            for (int j = 0; j < height; j++) {
                pixels[i][j] = imageInput.getRGB(i, j); // get RGB
                for (int k = i; k < sizeKernel - 1; k++) {
                    for (int l = j; l < sizeKernel - 1; l++) {
                        int xloc = i + (k - kernelXY);
                        int yloc = j + (l - kernelXY);
                        if (xloc >= 0 && xloc < i && yloc >= 0 && yloc < j) {
                            //     try {

                            r += c.red(pixels, xloc, yloc) * (kernel[i - 1 + k][j - 1 + l]/10); // calculate a RED and call red method
                            g += c.green(pixels, xloc, yloc) * (kernel[i - 1 + k][j - 1 + l]/10); // calculate a GREEN and call green method
                            b += c.blue(pixels, xloc, yloc) * (kernel[i - 1 + k][j - 1 + l]/10); // calculate a BLUE and call blue method

                            int rgb = (r << 16) | (g << 8) | b;
                            imageOutput.setRGB(i, j, rgb);
                            //  } catch (Exception e) {
                            //      System.out.println(e.getMessage());
                            //  }

                        }
                    }
                }
            }
        }
        return imageInput = imageOutput;

    }

    public static void gaussianFillter(BufferedImage img) {
        float gaussian[][] = {
            {1 / 9, 1 / 9, 1 / 9},
            {1 / 9, 1 / 9, 1 / 9},
            {1 / 9, 1 / 9, 1 / 9}
        };

        // get size imageInput and kernel
        int wight = img.getWidth();
        int heigth = img.getHeight();
        int kernelSize = gaussian.length;
        int kernelXY = kernelSize / 2; // find a center of kernel

        // make a result with convolution method
        convolution(gaussian, wight, heigth, kernelSize, kernelXY);

    }