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js实现ostu

2026-04-07 02:08:38JavaScript

使用JavaScript实现Otsu算法

Otsu算法是一种用于图像二值化的自动阈值选择方法，通过最大化类间方差来确定最佳阈值。以下为JavaScript实现步骤：

计算灰度直方图

function computeHistogram(imageData) {
  const histogram = new Array(256).fill(0);
  for (let i = 0; i < imageData.length; i += 4) {
    const gray = Math.round(0.299 * imageData[i] + 0.587 * imageData[i + 1] + 0.114 * imageData[i + 2]);
    histogram[gray]++;
  }
  return histogram;
}

计算Otsu阈值

function otsuThreshold(histogram, totalPixels) {
  let sum = 0;
  for (let t = 0; t < 256; t++) sum += t * histogram[t];

  let sumB = 0;
  let wB = 0;
  let wF = 0;
  let maxVariance = 0;
  let threshold = 0;

  for (let t = 0; t < 256; t++) {
    wB += histogram[t];
    if (wB === 0) continue;

    wF = totalPixels - wB;
    if (wF === 0) break;

    sumB += t * histogram[t];
    const mB = sumB / wB;
    const mF = (sum - sumB) / wF;

    const variance = wB * wF * Math.pow(mB - mF, 2);
    if (variance > maxVariance) {
      maxVariance = variance;
      threshold = t;
    }
  }

  return threshold;
}

应用阈值进行二值化

js实现ostu

function applyThreshold(imageData, threshold) {
  const newImageData = new Uint8ClampedArray(imageData.length);
  for (let i = 0; i < imageData.length; i += 4) {
    const gray = Math.round(0.299 * imageData[i] + 0.587 * imageData[i + 1] + 0.114 * imageData[i + 2]);
    const value = gray > threshold ? 255 : 0;
    newImageData[i] = newImageData[i + 1] = newImageData[i + 2] = value;
    newImageData[i + 3] = 255; // Alpha通道
  }
  return newImageData;
}

完整调用示例

function otsuBinarization(imageData) {
  const histogram = computeHistogram(imageData);
  const totalPixels = imageData.length / 4;
  const threshold = otsuThreshold(histogram, totalPixels);
  return applyThreshold(imageData, threshold);
}