Java Code Examples for org.opencv.imgproc.Imgproc#getStructuringElement()
The following examples show how to use
org.opencv.imgproc.Imgproc#getStructuringElement() .
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Example 1
| Source File: GeneralUtils.java From super-cloudops with Apache License 2.0 | 6 votes |
|
/**
* 图像腐蚀/膨胀处理 腐蚀和膨胀对处理没有噪声的图像很有利，慎用
*/
public static Mat erodeDilateImg(Mat src) {
Mat outImage = new Mat();
// size 越小，腐蚀的单位越小，图片越接近原图
Mat structImage = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(2, 2));
/**
* 图像腐蚀 腐蚀说明： 图像的一部分区域与指定的核进行卷积， 求核的最`小`值并赋值给指定区域。
* 腐蚀可以理解为图像中`高亮区域`的'领域缩小'。 意思是高亮部分会被不是高亮部分的像素侵蚀掉，使高亮部分越来越少。
*/
Imgproc.erode(src, outImage, structImage, new Point(-1, -1), 2);
src = outImage;
/**
* 膨胀 膨胀说明： 图像的一部分区域与指定的核进行卷积， 求核的最`大`值并赋值给指定区域。
* 膨胀可以理解为图像中`高亮区域`的'领域扩大'。 意思是高亮部分会侵蚀不是高亮的部分，使高亮部分越来越多。
*/
Imgproc.dilate(src, outImage, structImage, new Point(-1, -1), 1);
src = outImage;
return src;
}
Example 2
| Source File: GeneralUtils.java From super-cloudops with Apache License 2.0 | 6 votes |
|
/**
* 图像腐蚀
*
* @param src
* @return
*/
public static Mat erode(Mat src) {
Mat outImage = new Mat();
// size 越小，腐蚀的单位越小，图片越接近原图
Mat structImage = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(2, 2));
/**
* 图像腐蚀 腐蚀说明： 图像的一部分区域与指定的核进行卷积， 求核的最`小`值并赋值给指定区域。
* 腐蚀可以理解为图像中`高亮区域`的'领域缩小'。 意思是高亮部分会被不是高亮部分的像素侵蚀掉，使高亮部分越来越少。
*/
Imgproc.erode(src, outImage, structImage, new Point(-1, -1), 1);
src = outImage;
return src;
}
Example 3
| Source File: MainActivity.java From MOAAP with MIT License | 6 votes |
|
@Override
protected void onActivityResult(int requestCode, int resultCode, Intent imageReturnedIntent) {
//Put it there, just in case:)
super.onActivityResult(requestCode, resultCode, imageReturnedIntent);
switch(requestCode) {
case SELECT_PHOTO:
if(resultCode == RESULT_OK && read_external_storage_granted){
try {
final Uri imageUri = imageReturnedIntent.getData();
final InputStream imageStream = getContentResolver().openInputStream(imageUri);
final Bitmap selectedImage = BitmapFactory.decodeStream(imageStream);
src = new Mat(selectedImage.getHeight(), selectedImage.getWidth(), CvType.CV_8UC4);
Utils.bitmapToMat(selectedImage, src);
src_gray = new Mat(selectedImage.getHeight(), selectedImage.getWidth(), CvType.CV_8UC1);
switch (ACTION_MODE) {
case HomeActivity.GAUSSIAN_BLUR:
Imgproc.GaussianBlur(src, src, new Size(9, 9), 0);
break;
case HomeActivity.MEAN_BLUR:
Imgproc.blur(src, src, new Size(9, 9));
break;
case HomeActivity.MEDIAN_BLUR:
Imgproc.medianBlur(src, src, 9);
break;
case HomeActivity.SHARPEN:
Mat kernel = new Mat(3, 3, CvType.CV_16SC1);
//int[] values = {0, -1, 0, -1, 5, -1, 0, -1, 0};
Log.d("imageType", CvType.typeToString(src.type()) + "");
kernel.put(0, 0, 0, -1, 0, -1, 5, -1, 0, -1, 0);
Imgproc.filter2D(src, src, src_gray.depth(), kernel);
break;
case HomeActivity.DILATE:
Imgproc.cvtColor(src, src_gray, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(src_gray, src_gray, 100, 255, Imgproc.THRESH_BINARY);
Mat kernelDilate = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3));
Imgproc.dilate(src_gray, src_gray, kernelDilate);
Imgproc.cvtColor(src_gray, src, Imgproc.COLOR_GRAY2RGBA, 4);
break;
case HomeActivity.ERODE:
Imgproc.cvtColor(src, src_gray, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(src_gray, src_gray, 100, 255, Imgproc.THRESH_BINARY);
Mat kernelErode = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
Imgproc.erode(src_gray, src_gray, kernelErode);
Imgproc.cvtColor(src_gray, src, Imgproc.COLOR_GRAY2RGBA, 4);
break;
case HomeActivity.THRESHOLD:
Imgproc.cvtColor(src, src_gray, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(src_gray, src_gray, 100, 255, Imgproc.THRESH_BINARY);
Imgproc.cvtColor(src_gray, src, Imgproc.COLOR_GRAY2RGBA, 4);
break;
case HomeActivity.ADAPTIVE_THRESHOLD:
Imgproc.cvtColor(src, src_gray, Imgproc.COLOR_BGR2GRAY);
Imgproc.adaptiveThreshold(src_gray, src_gray, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY, 3, 0);
Imgproc.cvtColor(src_gray, src, Imgproc.COLOR_GRAY2RGBA, 4);
break;
}
Bitmap processedImage = Bitmap.createBitmap(src.cols(), src.rows(), Bitmap.Config.ARGB_8888);
Log.i("imageType", CvType.typeToString(src.type()) + "");
Utils.matToBitmap(src, processedImage);
ivImage.setImageBitmap(selectedImage);
ivImageProcessed.setImageBitmap(processedImage);
Log.i("process", "process done");
} catch (FileNotFoundException e) {
e.printStackTrace();
}
}
break;
}
}
Example 4
| Source File: OpenCVoperation.java From Human-hair-detection with Apache License 2.0 | 6 votes |
|
public void skinSegmentation()
{
matrix3_skindetection = new Mat(matrix2_grabcut.size(),matrix2_grabcut.type());
matrix3_skindetection.setTo(new Scalar(0,0,255));
Mat skinMask = new Mat();
Mat hsvMatrix = new Mat();
Scalar lower = new Scalar(0,48,80);
Scalar upper = new Scalar(20,255,255);
Imgproc.cvtColor(matrix2_grabcut, hsvMatrix, Imgproc.COLOR_BGR2HSV);
Core.inRange(hsvMatrix, lower, upper, skinMask);
Mat kernel =Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE,new Size(11,11));
Imgproc.erode(skinMask, skinMask, kernel);
Imgproc.dilate(skinMask, skinMask, kernel);
Imgproc.GaussianBlur(skinMask,skinMask, new Size(3,3), 0);
Core.bitwise_and(matrix2_grabcut, matrix2_grabcut, matrix3_skindetection,skinMask);
Imgcodecs.imwrite(resultDirectory+skinDetectionOutput , matrix3_skindetection);
}
Example 5
| Source File: OpenCVoperation.java From Human-hair-detection with Apache License 2.0 | 6 votes |
|
public void performErosion_Dilution()
{
erosion_dilutionMatrix = new Mat(this.matrix7_output.size(),this.matrix7_output.type());
int erosion_size=2;
//erosion
Mat element1 = Imgproc.getStructuringElement(Imgproc.MORPH_ERODE, new Size(2*erosion_size + 1, 2*erosion_size+1));
Imgproc.erode(matrix7_output, erosion_dilutionMatrix, element1);
Imgcodecs.imwrite(resultDirectory+erosionOutput,erosion_dilutionMatrix);
/*
//dilation
Mat element2 = Imgproc.getStructuringElement(Imgproc.MORPH_DILATE, new Size(2*erosion_size + 1, 2*erosion_size+1));
Imgproc.dilate(erosion_dilutionMatrix, erosion_dilutionMatrix, element2);
Imgcodecs.imwrite(resultDirectory+this.dilationOutput,erosion_dilutionMatrix);
*/
}
Example 6
| Source File: StepByStepTestActivity.java From CVScanner with GNU General Public License v3.0 | 6 votes |
|
Mat buildSkeleton(Mat img){
Mat morph = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_CROSS, new Size(3, 3));
Mat skel = new Mat(img.size(), CvType.CV_8UC1, Scalar.all(0));
Mat eroded = new Mat();
Mat temp = new Mat();
boolean done = false;
do{
Imgproc.morphologyEx(img, eroded, Imgproc.MORPH_ERODE, morph);
Imgproc.morphologyEx(eroded, temp, Imgproc.MORPH_DILATE, morph);
Core.subtract(img, temp, temp);
Core.bitwise_or(skel, temp, skel);
eroded.copyTo(img);
done = Core.countNonZero(img) == 0;
}while (!done);
return skel;
}
Example 7
| Source File: Finder.java From SikuliNG with MIT License | 5 votes |
|
public static List<Element> detectChanges(Mat base, Mat mChanged) {
int PIXEL_DIFF_THRESHOLD = 3;
int IMAGE_DIFF_THRESHOLD = 5;
Mat mBaseGray = Element.getNewMat();
Mat mChangedGray = Element.getNewMat();
Mat mDiffAbs = Element.getNewMat();
Mat mDiffTresh = Element.getNewMat();
Mat mChanges = Element.getNewMat();
List<Element> rectangles = new ArrayList<>();
Imgproc.cvtColor(base, mBaseGray, toGray);
Imgproc.cvtColor(mChanged, mChangedGray, toGray);
Core.absdiff(mBaseGray, mChangedGray, mDiffAbs);
Imgproc.threshold(mDiffAbs, mDiffTresh, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
if (Core.countNonZero(mDiffTresh) > IMAGE_DIFF_THRESHOLD) {
Imgproc.threshold(mDiffAbs, mDiffAbs, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
Imgproc.dilate(mDiffAbs, mDiffAbs, Element.getNewMat());
Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
Imgproc.morphologyEx(mDiffAbs, mDiffAbs, Imgproc.MORPH_CLOSE, se);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat mHierarchy = Element.getNewMat();
Imgproc.findContours(mDiffAbs, contours, mHierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
rectangles = contoursToRectangle(contours);
Core.subtract(mDiffAbs, mDiffAbs, mChanges);
Imgproc.drawContours(mChanges, contours, -1, new Scalar(255));
//logShow(mDiffAbs);
}
return rectangles;
}
Example 8
| Source File: Finder.java From SikuliX1 with MIT License | 5 votes |
|
public static List<Region> findChanges(FindInput2 findInput) {
findInput.setAttributes();
Mat previousGray = SXOpenCV.newMat();
Mat nextGray = SXOpenCV.newMat();
Mat mDiffAbs = SXOpenCV.newMat();
Mat mDiffThresh = SXOpenCV.newMat();
Imgproc.cvtColor(findInput.getBase(), previousGray, toGray);
Imgproc.cvtColor(findInput.getTarget(), nextGray, toGray);
Core.absdiff(previousGray, nextGray, mDiffAbs);
Imgproc.threshold(mDiffAbs, mDiffThresh, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
List<Region> rectangles = new ArrayList<>();
if (Core.countNonZero(mDiffThresh) > IMAGE_DIFF_THRESHOLD) {
Imgproc.threshold(mDiffAbs, mDiffAbs, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
Imgproc.dilate(mDiffAbs, mDiffAbs, SXOpenCV.newMat());
Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
Imgproc.morphologyEx(mDiffAbs, mDiffAbs, Imgproc.MORPH_CLOSE, se);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat mHierarchy = SXOpenCV.newMat();
Imgproc.findContours(mDiffAbs, contours, mHierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
for (MatOfPoint contour : contours) {
int x1 = 99999;
int y1 = 99999;
int x2 = 0;
int y2 = 0;
List<org.opencv.core.Point> points = contour.toList();
for (Point point : points) {
int x = (int) point.x;
int y = (int) point.y;
if (x < x1) x1 = x;
if (x > x2) x2 = x;
if (y < y1) y1 = y;
if (y > y2) y2 = y;
}
Region rect = new Region(x1, y1, x2 - x1, y2 - y1);
rectangles.add(rect);
}
}
return rectangles;
}
Example 9
| Source File: MovementDetectionProcessor.java From Camdroid with Apache License 2.0 | 5 votes |
|
protected void execute() {
out = gray();
Imgproc.equalizeHist(out, out);
synchronized (mog) {
mog.apply(out, this.mask, (double) (-10 + learning_rate) / 10);
}
Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_DILATE,
new Size(3, 3));
Imgproc.dilate(mask, mask, kernel);
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(this.mask, contours, new Mat(),
Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
double maxheight = object_max_size * this.in.height() / 100;
double minheight = object_min_size * this.in.height() / 100;
Iterator<MatOfPoint> each = contours.iterator();
each = contours.iterator();
while (each.hasNext()) {
MatOfPoint contour = each.next();
Rect rect = Imgproc.boundingRect(contour);
if (rect.height > minheight && rect.height < maxheight) {
Imgproc.rectangle(out, rect.tl(), rect.br(), new Scalar(255,
0, 0), 1);
}
}
}
Example 10
| Source File: Filter.java From FTCVision with MIT License | 5 votes |
|
/**
* Dilate the image using morphological transformations
*
* @param img Image matrix
* @param amount Amount to dilate = 0
*/
public static void dilate(Mat img, int amount) {
Mat kernel = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_RECT,
new Size(2 * amount + 1, 2 * amount + 1),
new Point(amount, amount));
Imgproc.dilate(img, img, kernel);
}
Example 11
| Source File: Filter.java From FTCVision with MIT License | 5 votes |
|
/**
* Erode the image using morphological transformations
*
* @param img Image matrix
* @param amount Amount to erode = 0
*/
public static void erode(Mat img, int amount) {
Mat kernel = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_RECT,
new Size(2 * amount + 1, 2 * amount + 1),
new Point(amount, amount));
Imgproc.erode(img, img, kernel);
}
Example 12
| Source File: CVProcessor.java From CVScanner with GNU General Public License v3.0 | 5 votes |
|
public static List<MatOfPoint> findContoursForMRZ(Mat src){
Mat img = src.clone();
src.release();
double ratio = getScaleRatio(img.size());
int width = (int) (img.size().width / ratio);
int height = (int) (img.size().height / ratio);
Size newSize = new Size(width, height);
Mat resizedImg = new Mat(newSize, CvType.CV_8UC4);
Imgproc.resize(img, resizedImg, newSize);
Mat gray = new Mat();
Imgproc.cvtColor(resizedImg, gray, Imgproc.COLOR_BGR2GRAY);
Imgproc.medianBlur(gray, gray, 3);
//Imgproc.blur(gray, gray, new Size(3, 3));
Mat morph = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(13, 5));
Mat dilatedImg = new Mat();
Imgproc.morphologyEx(gray, dilatedImg, Imgproc.MORPH_BLACKHAT, morph);
gray.release();
Mat gradX = new Mat();
Imgproc.Sobel(dilatedImg, gradX, CvType.CV_32F, 1, 0);
dilatedImg.release();
Core.convertScaleAbs(gradX, gradX, 1, 0);
Core.MinMaxLocResult minMax = Core.minMaxLoc(gradX);
Core.convertScaleAbs(gradX, gradX, (255/(minMax.maxVal - minMax.minVal)),
- ((minMax.minVal * 255) / (minMax.maxVal - minMax.minVal)));
Imgproc.morphologyEx(gradX, gradX, Imgproc.MORPH_CLOSE, morph);
Mat thresh = new Mat();
Imgproc.threshold(gradX, thresh, 0, 255, Imgproc.THRESH_OTSU);
gradX.release();
morph.release();
morph = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(21, 21));
Imgproc.morphologyEx(thresh, thresh, Imgproc.MORPH_CLOSE, morph);
Imgproc.erode(thresh, thresh, new Mat(), new Point(-1, -1), 4);
morph.release();
int col = (int) resizedImg.size().width;
int p = (int) (resizedImg.size().width * 0.05);
int row = (int) resizedImg.size().height;
for(int i = 0; i < row; i++)
{
for(int j = 0; j < p; j++){
thresh.put(i, j, 0);
thresh.put(i, col-j, 0);
}
}
List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(thresh, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
hierarchy.release();
Log.d(TAG, "contours found: " + contours.size());
Collections.sort(contours, new Comparator<MatOfPoint>() {
@Override
public int compare(MatOfPoint o1, MatOfPoint o2) {
return Double.valueOf(Imgproc.contourArea(o2)).compareTo(Imgproc.contourArea(o1));
}
});
return contours;
}
Example 13
| Source File: ALTMRetinex.java From OptimizedImageEnhance with MIT License | 5 votes |
|
private static Mat localAdaptation(Mat Lg, int rows, int cols, int r, double eps, double krnlRatio) {
int krnlSz = Stream.of(3.0, rows * krnlRatio, cols * krnlRatio).max(Double::compare).orElse(3.0).intValue();
// maximum filter: using dilate to extract the local maximum of a image block, which acts as the maximum filter
// Meanwhile, minimum filter can be achieved by using erode function
Mat Lg_ = new Mat();
Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(krnlSz, krnlSz), new Point(-1, -1));
Imgproc.dilate(Lg, Lg_, kernel);
// guided image filter
return Filters.GuidedImageFilter(Lg, Lg_, r, eps);
}
Example 14
| Source File: GeneralUtils.java From super-cloudops with Apache License 2.0 | 5 votes |
|
/**
* 膨胀
*
* @param src
* @return
*/
public static Mat dialate(Mat src) {
Mat outImage = new Mat();
// size 越小，腐蚀的单位越小，图片越接近原图
Mat structImage = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(2, 2));
Imgproc.dilate(src, outImage, structImage, new Point(-1, -1), 2);
src = outImage;
return src;
}
Example 15
| Source File: SXOpenCV.java From SikuliX1 with MIT License | 5 votes |
|
public static List<Match> doFindChanges(Image original, Image changed) {
List<Match> changes = new ArrayList<>();
if (changed.isValid()) {
int PIXEL_DIFF_THRESHOLD = 3;
int IMAGE_DIFF_THRESHOLD = 5;
Mat previousGray = SXOpenCV.newMat();
Mat nextGray = SXOpenCV.newMat();
Mat mDiffAbs = SXOpenCV.newMat();
Mat mDiffTresh = SXOpenCV.newMat();
Imgproc.cvtColor(original.getContent(), previousGray, toGray);
Imgproc.cvtColor(changed.getContent(), nextGray, toGray);
Core.absdiff(previousGray, nextGray, mDiffAbs);
Imgproc.threshold(mDiffAbs, mDiffTresh, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
if (Core.countNonZero(mDiffTresh) > IMAGE_DIFF_THRESHOLD) {
Imgproc.threshold(mDiffAbs, mDiffAbs, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
Imgproc.dilate(mDiffAbs, mDiffAbs, SXOpenCV.newMat());
Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
Imgproc.morphologyEx(mDiffAbs, mDiffAbs, Imgproc.MORPH_CLOSE, se);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat mHierarchy = SXOpenCV.newMat();
Imgproc.findContours(mDiffAbs, contours, mHierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
changes = contoursToRectangle(contours);
}
}
return changes;
}
Example 16
| Source File: CVProcessor.java From CVScanner with GNU General Public License v3.0 | 4 votes |
|
public static List<MatOfPoint> findContours(Mat src){
Mat img = src.clone();
//find contours
double ratio = getScaleRatio(img.size());
int width = (int) (img.size().width / ratio);
int height = (int) (img.size().height / ratio);
Size newSize = new Size(width, height);
Mat resizedImg = new Mat(newSize, CvType.CV_8UC4);
Imgproc.resize(img, resizedImg, newSize);
img.release();
Imgproc.medianBlur(resizedImg, resizedImg, 7);
Mat cannedImg = new Mat(newSize, CvType.CV_8UC1);
Imgproc.Canny(resizedImg, cannedImg, 70, 200, 3, true);
resizedImg.release();
Imgproc.threshold(cannedImg, cannedImg, 70, 255, Imgproc.THRESH_OTSU);
Mat dilatedImg = new Mat(newSize, CvType.CV_8UC1);
Mat morph = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3));
Imgproc.dilate(cannedImg, dilatedImg, morph, new Point(-1, -1), 2, 1, new Scalar(1));
cannedImg.release();
morph.release();
ArrayList<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(dilatedImg, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
hierarchy.release();
dilatedImg.release();
Log.d(TAG, "contours found: " + contours.size());
Collections.sort(contours, new Comparator<MatOfPoint>() {
@Override
public int compare(MatOfPoint o1, MatOfPoint o2) {
return Double.valueOf(Imgproc.contourArea(o2)).compareTo(Imgproc.contourArea(o1));
}
});
return contours;
}
Example 17
| Source File: DarkChannelPriorDehaze.java From OptimizedImageEnhance with MIT License | 4 votes |
|
public static Mat enhance(Mat image, double krnlRatio, double minAtmosLight, double eps) {
image.convertTo(image, CvType.CV_32F);
// extract each color channel
List<Mat> rgb = new ArrayList<>();
Core.split(image, rgb);
Mat rChannel = rgb.get(0);
Mat gChannel = rgb.get(1);
Mat bChannel = rgb.get(2);
int rows = rChannel.rows();
int cols = rChannel.cols();
// derive the dark channel from original image
Mat dc = rChannel.clone();
for (int i = 0; i < image.rows(); i++) {
for (int j = 0; j < image.cols(); j++) {
double min = Math.min(rChannel.get(i, j)[0], Math.min(gChannel.get(i, j)[0], bChannel.get(i, j)[0]));
dc.put(i, j, min);
}
}
// minimum filter
int krnlSz = Double.valueOf(Math.max(Math.max(rows * krnlRatio, cols * krnlRatio), 3.0)).intValue();
Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(krnlSz, krnlSz), new Point(-1, -1));
Imgproc.erode(dc, dc, kernel);
// get coarse transmission map
Mat t = dc.clone();
Core.subtract(t, new Scalar(255.0), t);
Core.multiply(t, new Scalar(-1.0), t);
Core.divide(t, new Scalar(255.0), t);
// obtain gray scale image
Mat gray = new Mat();
Imgproc.cvtColor(image, gray, Imgproc.COLOR_RGB2GRAY);
Core.divide(gray, new Scalar(255.0), gray);
// refine transmission map
int r = krnlSz * 4;
t = Filters.GuidedImageFilter(gray, t, r, eps);
// get minimum atmospheric light
minAtmosLight = Math.min(minAtmosLight, Core.minMaxLoc(dc).maxVal);
// dehaze each color channel
rChannel = dehaze(rChannel, t, minAtmosLight);
gChannel = dehaze(gChannel, t, minAtmosLight);
bChannel = dehaze(bChannel, t, minAtmosLight);
// merge three color channels to a image
Mat outval = new Mat();
Core.merge(new ArrayList<>(Arrays.asList(rChannel, gChannel, bChannel)), outval);
outval.convertTo(outval, CvType.CV_8UC1);
return outval;
}
