one.empty3.feature.GaussFilterPixM Maven / Gradle / Ivy

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3D rendering engine. Plus modeling. Expected glsl textures 3d and 2d rendering

There is a newer version: 2024.5.10

/*
 * Copyright (c) 2022-2023. Manuel Daniel Dahmen
 *
 *
 *    Copyright 2012-2023 Manuel Daniel Dahmen
 *
 *    Licensed under the Apache License, Version 2.0 (the "License");
 *    you may not use this file except in compliance with the License.
 *    You may obtain a copy of the License at
 *
 *        http://www.apache.org/licenses/LICENSE-2.0
 *
 *    Unless required by applicable law or agreed to in writing, software
 *    distributed under the License is distributed on an "AS IS" BASIS,
 *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *    See the License for the specific language governing permissions and
 *    limitations under the License.
 */

package one.empty3.feature;

public class GaussFilterPixM extends FilterPixM {
    private final PixM in;
    public double sigma = 0.8;

    public GaussFilterPixM() {
        super(3, 3);
        in = null;
    }

    public GaussFilterPixM(PixM in, int squareSize) {
        super(squareSize, squareSize);
        this.in = in;
    }

    @Override
    public double filter(double x, double y) {
        double ret = 0.0;
        for (double i = x - in.lines / 2; i < x + in.lines / 2; i++)
            for (double j = y - in.columns / 2; j < y + in.columns / 2; j++) {
                ret += in.get((int) i, (int) j) * Math.exp(
                        -((x - i) * (x - i) + (y - j) * (y - j))
                                / 2 / sigma / sigma) / 2 / Math.PI / sigma / sigma;
            }
        return ret;
    }

    /*
     * Gaussian filter Matrix
     * @param halfSquareSizeMinus1 n*n square distribution
     * @param sigma gauss parameter
     * @param pixM image
     */
    public GaussFilterPixM(PixM pixM, int halfSquareSizeMinus1, double sigma) {
        this(pixM, halfSquareSizeMinus1 * 2 + 1);
        this.sigma = sigma;
        for (int comp = 0; comp < getCompCount(); comp++) {
            setCompNo(comp);
            fill();
        }
        setCompNo(0);
    }

    public void fill() {
        for (int i = 0; i < columns; i++)
            for (int j = 0; j < lines; j++) {
                set(i, j, filter(i - columns / 2,
                        j - lines / 2)
                );
            }
    }

    public double getSigma() {
        return sigma;
    }

    public void setSigma(double sigma) {
        this.sigma = sigma;
    }
}