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Sky.java
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Sky.java
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package com.biubiu.example;
import org.bytedeco.javacpp.BytePointer;
import org.bytedeco.javacv.CanvasFrame;
import org.bytedeco.javacv.Frame;
import org.bytedeco.javacv.OpenCVFrameConverter;
import javax.swing.*;
import static org.bytedeco.javacpp.opencv_core.*;
import static org.bytedeco.javacpp.opencv_imgcodecs.IMREAD_COLOR;
import static org.bytedeco.javacpp.opencv_imgcodecs.imread;
/**
* @author :张音乐
* @date :Created in 2021/11/20 下午4:17
* @description:风景- 天空滤镜
* @email: zhangyule1993@sina.com
* @version:
*/
public class Sky {
public static void main(String[] args) {
String filepath = "/home/yinyue/opencv/20220103145739.jpg";
Mat img = imread(filepath, IMREAD_COLOR);
if(img.empty()) {
System.out.println("cannot open file");
return;
}
OpenCVFrameConverter.ToMat converter = new OpenCVFrameConverter.ToMat();
// 饱和度调整
Mat sat = doSaturate(img, 60);
// 明度调整
Mat lig = doLightness(sat, 25);
// 对比度调整
Mat con = doContrast(lig, 60);
// 阴影调整
Mat sha = doShadow(con, 20);
// 高光调整
Mat hig = doHighLight(sha, 25);
// 色温调整
Mat target = doHighLight(hig, -30);
// 显示
Frame targetFrame = converter.convert(target);
CanvasFrame targetCanvas = new CanvasFrame("天空滤镜处理后", 1);
targetCanvas.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
targetCanvas.showImage(targetFrame);
}
/**
* 饱和度调整
* @param img
* @param percent
* @return
*/
private static Mat doSaturate(Mat img, int percent) {
float increment = percent * 1.0f / 100;
int height = img.rows();
int width = img.cols();
for(int i = 0; i < height; i++) {
for (int j = 0; j < width; j++) {
BytePointer ptr = img.ptr(i, j);
int b = ptr.get(0) < 0 ? (ptr.get(0) + 256) : ptr.get(0);
int g = ptr.get(1) < 0 ? (ptr.get(1) + 256) : ptr.get(1);
int r = ptr.get(2) < 0 ? (ptr.get(2) + 256) : ptr.get(2);
float max = Math.max(b, Math.max(g, r));
float min = Math.min(b, Math.min(g, r));
float delta = (max - min) / 255;
if(delta == 0) {
continue;
}
float value = (max + min) / 255;
float L = value / 2;
float S = 0f, alpha;
if(L < 0.5) {
S = delta / value;
}
if(increment >= 0) {
if((increment + S) >= 1) {
alpha = S;
} else {
alpha = 1 - increment;
}
alpha = 1 / alpha - 1;
int B = (int) (b + (b - L * 255) * alpha);
int G = (int) (g + (g - L * 255) * alpha);
int R = (int) (r + (r - L * 255) * alpha);
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
} else {
alpha = increment;
int B = (int) (b + (b - L * 255) * alpha);
int G = (int) (g + (g - L * 255) * alpha);
int R = (int) (r + (r - L * 255) * alpha);
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
}
}
}
return img;
}
/**
* 明度
* @param img
* @param percent
* @return
*/
private static Mat doLightness(Mat img, float percent) {
float alpha = percent / 100;
alpha = Math.max(-1.f, Math.min(1.f, alpha));
int height = img.rows();
int width = img.cols();
for(int i = 0; i < height; i++) {
for (int j = 0; j < width; j++) {
BytePointer ptr = img.ptr(i, j);
int b = ptr.get(0) < 0 ? (ptr.get(0) + 256) : ptr.get(0);
int g = ptr.get(1) < 0 ? (ptr.get(1) + 256) : ptr.get(1);
int r = ptr.get(2) < 0 ? (ptr.get(2) + 256) : ptr.get(2);
if(alpha >= 0) {
int B = (int) (b * (1 - alpha) + 255 * alpha);
int G = (int) (g * (1 - alpha) + 255 * alpha);
int R = (int) (r * (1 - alpha) + 255 * alpha);
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
} else {
int B = (int) (b * (1 + alpha));
int G = (int) (g * (1 + alpha));
int R = (int) (r * (1 + alpha));
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
}
}
}
return img;
}
/**
* 对比度
* @param img
* @param percent
* @return
*/
private static Mat doContrast(Mat img, float percent) {
float alpha = percent / 100.f;
alpha = Math.max(-1.f, Math.min(1.f, alpha));
int thresh = 127;
int height = img.rows();
int width = img.cols();
for(int i = 0; i < height; i++) {
for (int j = 0; j < width; j++) {
BytePointer ptr = img.ptr(i, j);
int b = ptr.get(0) < 0 ? (ptr.get(0) + 256) : ptr.get(0);
int g = ptr.get(1) < 0 ? (ptr.get(1) + 256) : ptr.get(1);
int r = ptr.get(2) < 0 ? (ptr.get(2) + 256) : ptr.get(2);
if(alpha == 0) {
int B = b > thresh ? 255 : 0;
int G = g > thresh ? 255 : 0;
int R = r > thresh ? 255 : 0;
ptr.put((byte) B, (byte) G, (byte) R);
} else if (alpha >= 0) {
int B = (int) (thresh + (b - thresh) / (1 - alpha));
int G = (int) (thresh + (g - thresh) / (1 - alpha));
int R = (int) (thresh + (r - thresh) / (1 - alpha));
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
} else {
int B = (int) (thresh + (b - thresh) * (1 + alpha));
int G = (int) (thresh + (g - thresh) * (1 + alpha));
int R = (int) (thresh + (r - thresh) * (1 + alpha));
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
}
}
}
return img;
}
/**
* 阴影
* @param img
* @param light
* @return
*/
private static Mat doShadow(Mat img, int light) {
// 生成灰度图
Mat gray = new Mat(img.size(), CV_32FC1);
Mat fs = img.clone();
fs.convertTo(fs, CV_32FC3);
MatVector vector = new MatVector();
split(fs, vector);
Mat v2 = vector.get(2);
Mat v0 = vector.get(0);
MatExpr x1 = multiply(0.299f, v2);
MatExpr x2 = multiply(0.587, v2);
MatExpr x3 = multiply(0.114, v0);
MatExpr add = add(x1, add(x2, x3));
MatExpr divide = divide(add, 255);
gray = divide.asMat();
// 确定高光区
Mat thresh = new Mat(gray.size(), gray.type());
// thresh = multiply(gray, gray).asMat();
// MatExpr sb1 = subtract();
MatExpr chat = subtract(new Scalar(1.0f, 1.0f, 1.0f, 0), gray);
thresh = chat.mul(chat).asMat();
// 取平均值作为阈值
Scalar t = mean(thresh);
Mat mask = new Mat(gray.size(), CV_8UC1);
// threshold(thresh, mask, t.blue(), 255, THRESH_BINARY | THRESH_OTSU);
// mask.setTo(new Mat(1, 1, CV_32SC4, t), new Mat(1, 1, CV_32SC4, new Scalar(255, 255, 255, 0)));
// 取平均值当阈值,进行二值化得到掩膜mask
inRange(thresh, new Mat(t), new Mat(new Scalar(255, 255, 255, 0)), mask);
// 参数设置
int max = 4;
float bright = light / 100.0f / max;
float mid = 1.0f + max * bright;
// 边缘平滑过渡
Mat midrate = new Mat(img.size(), CV_32FC1);
Mat brightrate = new Mat(img.size(), CV_32FC1);
for (int i = 0; i < img.rows(); ++i) {
for (int j = 0; j < img.cols(); ++j) {
BytePointer m = mask.ptr(i, j);
BytePointer th = thresh.ptr(i, j);
BytePointer mi = midrate.ptr(i, j);
BytePointer br = brightrate.ptr(i, j);
int value = m.get(0) < 0 ? (m.get(0) + 256) : m.get(0);
float thv = th.getFloat(0);
if(value == 255) {
mi.putFloat(mid);
br.putFloat(bright);
} else {
float s = (float) ((mid - 1.0f) / t.blue() * thv + 1.0f);
mi.putFloat(s);
float p = (float) (1.0f / t.blue() * thv) * bright;
br.putFloat(p);
}
}
}
Mat result = new Mat(img.size(), img.type());
// 高光提亮,获取结果图
for (int i = 0; i < img.rows(); ++i) {
for (int j = 0; j < img.cols(); ++j) {
BytePointer mi = midrate.ptr(i, j);
BytePointer br = brightrate.ptr(i, j);
BytePointer in = img.ptr(i, j);
BytePointer rPtr = result.ptr(i, j);
// int v = in.get(0) < 0 ? (in.get(0) + 256) : in.get(0);
float miv = mi.getFloat(0);
float brv = br.getFloat(0);
for(int k = 0; k < 3; k++) {
int v = in.get(k) < 0 ? (in.get(k) + 256) : in.get(k);
float temp = (float) (Math.pow(v / 255.f, 1.0f / miv) * (1.0 / (1 - brv)));
temp = Math.min(1.0f, Math.max(0.0f, temp));
rPtr.position(k).put((byte) (255 * temp));
}
}
}
return result;
}
/**
* 高光
* @param img
* @param light
* @return
*/
private static Mat doHighLight(Mat img, int light) {
// 生成灰度图
Mat gray = new Mat(img.size(), CV_32FC1);
Mat fs = img.clone();
fs.convertTo(fs, CV_32FC3);
MatVector vector = new MatVector();
split(fs, vector);
Mat v2 = vector.get(2);
Mat v0 = vector.get(0);
MatExpr x1 = multiply(0.299f, v2);
MatExpr x2 = multiply(0.587, v2);
MatExpr x3 = multiply(0.114, v0);
MatExpr add = add(x1, add(x2, x3));
MatExpr divide = divide(add, 255);
gray = divide.asMat();
// 确定高光区
Mat thresh = new Mat(gray.size(), gray.type());
// thresh = multiply(gray, gray).asMat();
thresh = gray.mul(gray).asMat();
// 取平均值作为阈值
Scalar t = mean(thresh);
Mat mask = new Mat(gray.size(), CV_8UC1);
// threshold(thresh, mask, t.blue(), 255, THRESH_BINARY | THRESH_OTSU);
// mask.setTo(new Mat(1, 1, CV_32SC4, t), new Mat(1, 1, CV_32SC4, new Scalar(255, 255, 255, 0)));
// 取平均值当阈值,进行二值化得到掩膜mask
inRange(thresh, new Mat(t), new Mat(new Scalar(255, 255, 255, 0)), mask);
// 参数设置
int max = 4;
float bright = light / 100.0f / max;
float mid = 1.0f + max * bright;
// 边缘平滑过渡
Mat midrate = new Mat(img.size(), CV_32FC1);
Mat brightrate = new Mat(img.size(), CV_32FC1);
for (int i = 0; i < img.rows(); ++i) {
for (int j = 0; j < img.cols(); ++j) {
BytePointer m = mask.ptr(i, j);
BytePointer th = thresh.ptr(i, j);
BytePointer mi = midrate.ptr(i, j);
BytePointer br = brightrate.ptr(i, j);
int value = m.get(0) < 0 ? (m.get(0) + 256) : m.get(0);
float thv = th.getFloat(0);
if(value == 255) {
mi.putFloat(mid);
br.putFloat(bright);
} else {
float s = (float) ((mid - 1.0f) / t.blue() * thv + 1.0f);
mi.putFloat(s);
float p = (float) (1.0f / t.blue() * thv) * bright;
br.putFloat(p);
}
}
}
Mat result = new Mat(img.size(), img.type());
// 高光提亮,获取结果图
for (int i = 0; i < img.rows(); ++i) {
for (int j = 0; j < img.cols(); ++j) {
BytePointer mi = midrate.ptr(i, j);
BytePointer br = brightrate.ptr(i, j);
BytePointer in = img.ptr(i, j);
BytePointer rPtr = result.ptr(i, j);
// int v = in.get(0) < 0 ? (in.get(0) + 256) : in.get(0);
float miv = mi.getFloat(0);
float brv = br.getFloat(0);
for(int k = 0; k < 3; k++) {
int v = in.get(k) < 0 ? (in.get(k) + 256) : in.get(k);
float temp = (float) (Math.pow(v / 255.f, 1.0f / miv) * (1.0 / (1 - brv)));
temp = Math.min(1.0f, Math.max(0.0f, temp));
rPtr.position(k).put((byte) (255 * temp));
}
}
}
return result;
}
/**
* 色温
* @param img
* @param percent
* @return
*/
private static Mat doColorTemperature(Mat img, int percent) {
Mat result = img.clone();
int rows = result.rows();
int cols = result.cols();
int level = percent / 2;
for(int i = 0; i < rows; i++) {
for (int j = 0; j < cols; j++) {
BytePointer ptr = result.ptr(i, j);
int b = ptr.get(0) < 0 ? (ptr.get(0) + 256) : ptr.get(0);
int g = ptr.get(1) < 0 ? (ptr.get(1) + 256) : ptr.get(1);
int r = ptr.get(2) < 0 ? (ptr.get(2) + 256) : ptr.get(2);
// 一般情况下,认为暖色偏黄色,冷色偏蓝色,基于此逻辑,在提高色温的时候,对红色和绿色通道进行增强,对蓝色通道进行减弱,这样就能让图像的黄色占比提高,进而达到暖黄色的效果;
// 反之亦然,降低色温,只需要增强蓝色通道,减少红色和绿色。
int B = b - level;
int G = g + level;
int R = r + level;
ptr.put((byte) Math.max(0, Math.min(B, 255)), (byte) Math.max(0, Math.min(G, 255)), (byte) Math.max(0, Math.min(R, 255)));
}
}
return result;
}
}