/**
 * @author Pacien TRAN-GIRARD
 * @author Timothée FLOURE
 */
public final class Filter {

    public static final float[][] SMOOTH_CORE = new float[][]{
            {0.1f, 0.1f, 0.1f},
            {0.1f, 0.2f, 0.1f},
            {0.1f, 0.1f, 0.1f}
    };
    public static final float[][] SOBEL_X_CORE = new float[][]{
            {-1, 0, 1},
            {-2, 0, 2},
            {-1, 0, 1}
    };
    public static final float[][] SOBEL_Y_CORE = new float[][]{
            {-1, -2, -1},
            {0, 0, 0},
            {1, 2, 1}
    };

    /**
     * Get a pixel without accessing out of bounds
     *
     * @param gray a HxW float array, H > 0, W > 0
     * @param row  Y coordinate
     * @param col  X coordinate
     * @return nearest valid pixel color
     */
    public static float at(float[][] gray, int row, int col) {
        int maxRow = gray.length - 1;
        int maxCol = gray[0].length - 1;

        if (row < 0) row = 0;
        if (col < 0) col = 0;

        if (row > maxRow) row = maxRow;
        if (col > maxCol) col = maxCol;

        return gray[row][col];
    }

    /**
     * Combine neighbour pixels using the given kernel.
     *
     * @param gray   a HxW float array
     * @param kernel a MxN float array, with M and N odd
     * @param row    Y coordinate
     * @param col    X coordinate
     * @return the pixel value
     */
    private static float combineNeighbours(float[][] gray, float[][] kernel, int row, int col) {
        int kernelWidth = kernel[0].length;
        int kernelHeight = kernel.length;

        int rowOffset = row - kernelWidth / 2; // int division
        int colOffset = col - kernelHeight / 2; // int division

        float pixelValue = 0;

        for (int kernelRow = 0; kernelRow < kernelHeight; ++kernelRow)
            for (int kernelCol = 0; kernelCol < kernelWidth; ++kernelCol)
                pixelValue += kernel[kernelRow][kernelCol]
                        * Filter.at(gray, rowOffset + kernelRow, colOffset + kernelCol);

        return pixelValue;
    }

    /**
     * Convolve a single-channel image with specified kernel.
     *
     * @param gray   a HxW float array
     * @param kernel a MxN float array, with M and N odd
     * @return a HxW float array
     */
    public static float[][] filter(float[][] gray, float[][] kernel) {
        int width = gray[0].length;
        int height = gray.length;

        float[][] filteredImage = new float[height][width];

        for (int row = 0; row < height; ++row)
            for (int col = 0; col < width; ++col)
                filteredImage[row][col] = Filter.combineNeighbours(gray, kernel, row, col);

        return filteredImage;
    }

    /**
     * Smooth a single-channel image
     *
     * @param gray a HxW float array
     * @return a HxW float array
     */
    public static float[][] smooth(float[][] gray) {
        return Filter.filter(gray, SMOOTH_CORE);
    }

    /**
     * Compute horizontal Sobel filter
     *
     * @param gray a HxW float array
     * @return a HxW float array
     */
    public static float[][] sobelX(float[][] gray) {
        return Filter.filter(gray, SOBEL_X_CORE);
    }

    /**
     * Compute vertical Sobel filter
     *
     * @param gray a HxW float array
     * @return a HxW float array
     */
    public static float[][] sobelY(float[][] gray) {
        return Filter.filter(gray, SOBEL_Y_CORE);
    }

    /**
     * Compute the magnitude of combined Sobel filters
     *
     * @param gray a HxW float array
     * @return a HxW float array
     */
    public static float[][] sobel(float[][] gray) {
        float[][] x = Filter.sobelX(gray);
        float[][] y = Filter.sobelY(gray);

        int width = gray[0].length;
        int height = gray.length;

        float[][] sobelImage = new float[height][width];

        for (int row = 0; row < height; ++row) {
            for (int col = 0; col < width; ++col) {
                sobelImage[row][col] = (float) Math.sqrt(Math.pow(x[row][col], 2) + Math.pow(y[row][col], 2));
            }
        }

        return sobelImage;
    }

}