Image enhancement techniques play an important role in digital image processing, one of which is histogram equalization. Histogram equalization is a method used to improve the contrast of an image by redistributing the distribution of pixel gray levels to enhance the visual effect of the image. In this article, we will introduce how to use MATLAB for image histogram equalization and provide the corresponding source code.
First, let's understand how histogram equalization works. The histogram of an image represents the number of pixels at different gray levels. The goal of histogram equalization is to redistribute the gray levels of pixels so that the histogram of the image has a uniform distribution throughout the entire gray range. Doing this enhances the contrast of the image, making details in the image clearer.
The following are the steps for image histogram equalization using MATLAB:
Step 1: Read the image
We first need to read an image to be processed. Images can be read using MATLAB's imread function. Assuming that the image file we want to process is named "image.jpg", we can use the following code to read the image:
image = imread('image.jpg');
Step 2: Calculate Histogram
Next, we need to calculate the histogram of the image. You can use MATLAB's imhist function to calculate the histogram of an image. The following code will calculate the histogram of the image and store it in the variable hist:
hist =</