fi,j表示在图像f中,第i行,第j列的像素强度;gi,j表示在图像g中,第i行,第j列的像素强度. Python 实现 #!/usr/bin/env python#-*- coding: utf8 -*-"""# Author: klchang # Date: 2018.10 # Description: histogram equalization of a gray image."""from__
直方图均衡化是一种图像处理方法,用来提高图像的对比度,本博客涉及到直方图的应用PYTHON+OPENCV2 如果一个图像的像素取值范围在很狭窄的一个区域内,那么图像的细节就不是那么的明显,如果可以将图像的像素分布范围均衡化,那么能够提高图像的对比度,如下图所示: 使用python+opencv2计算一幅图像的直方图,图像如下图: 由...
灰度图的直⽅图均衡化（HistogramEqualization）原理与 Python实现 原理 直⽅图均衡化是⼀种通过使⽤图像直⽅图，调整对⽐度的图像处理⽅法；通过对图像的强度（intensity）进⾏某种⾮线性变换，使得变换后的图像直⽅图为近似均匀分布，从⽽，达到提⾼图像对⽐度和增强图⽚的⽬的。普通...
Histogram Equalization in Python In this section, I will show you how to implement the histogram equalization method in Python. We will use the above image (pout.jpg) in our experiments. Let's go through the process step by step. The first thing we need to do is import the OpenCV and ...
Also write the code using OpenCV to perform histogram equalization. Software Required: Anaconda - Python 3.7 Algorithm: Step1: Read the gray and color image using imread() Step2: Print the image using imshow(). Step3: Use calcHist() function to mark the image in graph frequency for gray ...
Histogram matching, also known as histogram specification or histogram equalization matching, is a technique used to transform the intensity distribution of an image to match a specified target histogram. The goal of histogram matching is to take an input image and generate an output image that has...
```python import cv2 import numpy as np def histogram_equalization(image): # 获取图像的灰度值 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # 计算灰度直方图 hist = cv2.calcHist([gray], [0], None, [256], [0, 256]) # 计算直方图的累积分布函数 ...
Most of the traditional LLIE methods are based on histogram equalization (HE) [10] and Retinex theory [11,12]. The traditional methods have achieved good performance on specific images and have also inspired recent work [13,14]. However, these methods focus on modifying the intensity values ...