不同TIFF图像像素平均亮度计算与ImageJ结果不一致求助

• 我编写的Python代码用于读取图像并计算平均亮度和标准差，处理某组偏暗的.TIF数据集时，计算结果与ImageJ直方图结果一致；但处理新的.tiff数据集时，亮度结果差异极大，标准差却完全相同。
• 已准备两组数据各2张图像及对应计算结果（白色背景为ImageJ结果）用于对比。
• 注：对图像应用了5×5中值滤波，对比时使用的是已完成中值滤波的图像；原始图像DPI分别为72和96，处理后均为96 DPI，且均为16位图像；为统计图像中的黑色像素，临时给像素值加1，计算后再减回原值；尝试更换其他库替代cv2，问题仍存在。

计算代码 #

import cv2
import numpy as np

def calc_xray_count(image_path):
    original_image = cv2.imread(image_path, cv2.IMREAD_ANYDEPTH)
    median_filtered_image = cv2.medianBlur(original_image, 5)
    median_filtered_image += 1  # Avoid not counting black pixels in image
    pixel_count = np.prod(median_filtered_image.shape)
    img_brightness_sum = np.sum(median_filtered_image)
    img_var = np.var(median_filtered_image)
 
    if (pixel_count > 0):
        img_avg_brightness = (img_brightness_sum/pixel_count) -1 # Subtract back to real data
    else:
        img_avg_brightness = 0
 
    print(f"mean brightness: {img_avg_brightness}")
    print(f"mean std: {np.sqrt(img_var)}")
    return img_avg_brightness, img_var

内容的提问来源于stack exchange，提问作者Niandra Lades