视频亮度对比度

复制import cv2
import numpy as np

# 读取图像
img = cv2.imread('input.jpg')

# 亮度（+50）、对比度（1.5）、饱和度（1.3）、Gamma（0.8）
alpha = 1.5  # 对比度
beta = 50    # 亮度

# 亮度和对比度
adjusted = cv2.convertScaleAbs(img, alpha=alpha, beta=beta)

# 饱和度（HSV空间）
hsv = cv2.cvtColor(adjusted, cv2.COLOR_BGR2HSV).astype(np.float32)
hsv[:,:,1] = np.clip(hsv[:,:,1] * 1.3, 0, 255)
adjusted = cv2.cvtColor(hsv.astype(np.uint8), cv2.COLOR_HSV2BGR)

# Gamma校正
gamma = 0.8
lookup = np.array([(i / 255.0) ** (1.0 / gamma) * 255 for i in range(256)]).astype(np.uint8)
adjusted = cv2.LUT(adjusted, lookup)

cv2.imwrite('output.jpg', adjusted)

复制package main

import (
	"image"
	"image/color"
	"image/jpeg"
	"math"
	"os"
)

func main() {
	file, _ := os.Open("input.jpg")
	defer file.Close()
	src, _, _ := image.Decode(file)

	bounds := src.Bounds()
	dst := image.NewRGBA(bounds)

	alpha := 1.5   // 对比度
	beta := 50.0   // 亮度
	gamma := 0.8   // Gamma
	sat := 1.3     // 饱和度

	for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
		for x := bounds.Min.X; x < bounds.Max.X; x++ {
			r, g, b, a := src.At(x, y).RGBA()
			// 转为0-255
			rf := float64(r>>8) * alpha + beta
			gf := float64(g>>8) * alpha + beta
			bf := float64(b>>8) * alpha + beta

			// Gamma
			rf = math.Pow(rf/255.0, 1.0/gamma) * 255
			gf = math.Pow(gf/255.0, 1.0/gamma) * 255
			bf = math.Pow(bf/255.0, 1.0/gamma) * 255

			// 饱和度（简化：RGB转HSV再转回）
			// 此处省略完整HSV转换，实际可用colorful库
			dst.Set(x, y, color.RGBA{
				R: uint8(math.Min(math.Max(rf, 0), 255)),
				G: uint8(math.Min(math.Max(gf, 0), 255)),
				B: uint8(math.Min(math.Max(bf, 0), 255)),
				A: uint8(a >> 8),
			})
		}
	}

	out, _ := os.Create("output.jpg")
	defer out.Close()
	jpeg.Encode(out, dst, nil)
}

复制// 浏览器端 Canvas 实现（无需外部库）
function adjustVideoFrame(canvas, brightness, contrast, saturation, gamma) {
  const ctx = canvas.getContext('2d');
  const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
  const data = imageData.data;

  for (let i = 0; i < data.length; i += 4) {
    let r = data[i];
    let g = data[i + 1];
    let b = data[i + 2];

    // 亮度和对比度
    r = r * contrast + brightness;
    g = g * contrast + brightness;
    b = b * contrast + brightness;

    // Gamma
    r = Math.pow(r / 255, 1 / gamma) * 255;
    g = Math.pow(g / 255, 1 / gamma) * 255;
    b = Math.pow(b / 255, 1 / gamma) * 255;

    // 饱和度（简化：加权平均转灰度再插值）
    const gray = 0.299 * r + 0.587 * g + 0.114 * b;
    r = gray + (r - gray) * saturation;
    g = gray + (g - gray) * saturation;
    b = gray + (b - gray) * saturation;

    data[i] = Math.min(255, Math.max(0, r));
    data[i + 1] = Math.min(255, Math.max(0, g));
    data[i + 2] = Math.min(255, Math.max(0, b));
  }

  ctx.putImageData(imageData, 0, 0);
}

// 使用示例：adjustVideoFrame(canvas, 50, 1.5, 1.3, 0.8);