本文整理了Java中org.opencv.core.Core.multiply()方法的一些代码示例，展示了Core.multiply()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Core.multiply()方法的具体详情如下：
包路径：org.opencv.core.Core
类名称：Core
方法名：multiply

Core.multiply介绍

[英]Calculates the per-element scaled product of two arrays.

The function multiply calculates the per-element product of two arrays:

dst(I)= saturate(scale * src1(I) * src2(I))

There is also a "MatrixExpressions" -friendly variant of the first function. See "Mat.mul".

For a not-per-element matrix product, see "gemm".

Note: Saturation is not applied when the output array has the depth CV_32S. You may even get result of an incorrect sign in the case of overflow.
[中]计算两个阵列的每元素比例积。
函数multiply计算两个数组的每元素乘积：
dst（I）=饱和（标度src1（I）src2（I））
还有一个“MatrixExpressions”——第一个函数的友好变体。参见“Mat.mul”。
对于非每元素矩阵乘积，请参见“gemm”。
注意：当输出数组的深度为CV_32S时，不应用饱和度。在溢出的情况下，您甚至可能会得到错误符号的结果。

代码示例

代码示例来源：origin: ytai/IOIOPlotter

Core.multiply(procImage_, new Scalar(0.25, 0.25, 0.25), procImage_);
Core.add(procImage_, new Scalar(192, 192, 192), procImage_);

代码示例来源：origin: JavaOpenCVBook/code

protected void processOperation() {
  Imgproc.Canny(originalImage, image, 220, 255, 3, false);
  Imgproc.threshold(image, image, 100, 255, Imgproc.THRESH_BINARY_INV);
  Imgproc.distanceTransform(image, image, Imgproc.CV_DIST_L2, 3);
  image.convertTo(image, CvType.CV_8UC1);
  Core.multiply(image, new Scalar(20), image);
  
  updateView();
}

代码示例来源：origin: ytai/IOIOPlotter

private void clear() {
  // Resize to native resolution divided by blur factor.
  float scale = LINE_WIDTH_TO_IMAGE_WIDTH / blur_ / srcImage_.cols();
  Imgproc.resize(srcImage_, imageResidue_, new Size(), scale, scale, Imgproc.INTER_AREA);
  // Negative.
  final Mat scalar = new Mat(1, 1, CvType.CV_64FC1).setTo(new Scalar(255));
  Core.subtract(scalar, imageResidue_, imageResidue_);
  // Convert to S16.
  imageResidue_.convertTo(imageResidue_, CvType.CV_16SC1);
  // Full scale is now blur * GRAY_RESOLUTION.
  Core.multiply(imageResidue_, new Scalar(blur_ * GRAY_RESOLUTION / 255), imageResidue_);
  // Clear map.
  curves_.clear();
  kernelFactory_.setDimensions(imageResidue_.width(), imageResidue_.height());
}

代码示例来源：origin: nroduit/Weasis

multiply(histogram, scalar, histogram);

代码示例来源：origin: nroduit/Weasis

public Mat getMaskedDosePlaneHist(double slicePosition, Mat mask, int maxDose) {
  DicomImageElement dosePlane = (DicomImageElement) this.getDosePlaneBySlice(slicePosition);
  int rows = dosePlane.getImage().toMat().rows();
  int cols = dosePlane.getImage().toMat().cols();
  // Calculate dose matrix for OpenCV
  Mat src = new Mat(rows, cols, CvType.CV_32FC1);
  dosePlane.getImage().toMat().convertTo(src, CvType.CV_32FC1);
  Scalar scalar = new Scalar(this.doseGridScaling * 100);
  Mat doseMatrix = new Mat(rows, cols, CvType.CV_32FC1);
  multiply(src, scalar, doseMatrix);
  List<Mat> doseMatrixVector = new ArrayList<>();
  doseMatrixVector.add(doseMatrix);
  // Masked dose plan histogram
  Mat hist = new Mat();
  // Number of histogram bins
  MatOfInt histSize = new MatOfInt(maxDose);
  // Dose varies from 0 to maxDose
  MatOfFloat histRange = new MatOfFloat(0, maxDose);
  // Only one 0-th channel
  MatOfInt channels = new MatOfInt(0);
  // Ned to change the structure dose mask type vor OpenCV histogram calculation
  Mat maskSrc = new Mat(mask.rows(), mask.cols(), CvType.CV_8U);
  mask.convertTo(maskSrc, CvType.CV_8U);
  Imgproc.calcHist(doseMatrixVector, channels, maskSrc, hist, histSize, histRange);
  
  return hist;
}