• 效果

• 性能

在虚拟机上，处理一帧1280*720，需要约50ms。

画面有点暗，可以考虑加亮。

• 代码

从代码来看，还是暗通道算法。

import cv2
import numpy as np
import time

class SimpleFastDehazer:
    """超快速视频去雾（牺牲一些质量换取速度）"""
    
    def __init__(self, w=0.8):
        self.w = w
        self.A = np.array([200, 200, 200], dtype=np.float32)  # 初始大气光
        
    def dehaze_frame_fast(self, img):
        """
        极速去雾版本
        处理640x480图像约3-5ms
        """
        # 1. 快速估计大气光（取图像最亮的0.1%像素）
        img_flat = img.reshape(-1, 3)
        bright_thresh = np.percentile(img_flat, 99.9, axis=0)
        bright_pixels = img_flat[np.all(img_flat >= bright_thresh * 0.9, axis=1)]
        
        if len(bright_pixels) > 0:
            A_est = np.mean(bright_pixels, axis=0)
            # 平滑更新
            self.A = 0.7 * self.A + 0.3 * A_est
        
        # 2. 简单暗通道（使用下采样加速）
        small = cv2.resize(img, (160, 120))
        dark  = np.min(small, axis=2)
        dark  = cv2.medianBlur(dark.astype(np.uint8), 5)
        
        # 3. 简单透射率估计
        transmission = 1 - self.w * (dark / 255.0)
        transmission = cv2.resize(transmission, (img.shape[1], img.shape[0]))
        transmission = np.clip(transmission, 0.1, 1.0)
        
        # 4. 快速恢复
        transmission = transmission[:, :, np.newaxis]
        result = (img.astype(np.float32) - self.A) / transmission + self.A
        
        return np.clip(result, 0, 255).astype(np.uint8)

# 使用示例
def real_time_dehazing(input_file, output_file):
    dehazer = SimpleFastDehazer()
    cap = cv2.VideoCapture(input_file)

    fps    = int(cap.get(cv2.CAP_PROP_FPS))
    width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    
    # 初始化视频写入器
    merge  = True
    write_w= width
    if (merge): write_w += width
    
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    out    = cv2.VideoWriter(output_file, fourcc, fps, (write_w, height))

    counter= 0
    cost   = 0
    while True:
        ret, frame = cap.read()
        if not ret:
            break
        
        counter += 1
        # 超快速去雾
        start_time = time.time()
        result  = dehazer.dehaze_frame_fast(frame)
        time_ms = (time.time() - start_time)*1000
        cost   += time_ms
        # 显示
        cv2.putText(result, f"{time_ms:.1f}ms", (30, 100), 
                   cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)

        if (merge):
            result = cv2.hconcat([frame, result]);
        out.write(result)

    print(cost, '/', counter, '=', (cost/counter))
    
    out.release() 
    cap.release()

if __name__ == "__main__":
    input_file  = '../fog5.mp4'
    output_file = 'defog.mp4'
    real_time_dehazing(input_file, output_file)