Maximum mutual information moving target detection based on MATLAB

Maximum mutual information moving target detection based on MATLAB

In the field of computer vision, object detection is an important task that involves accurately identifying and locating specific objects from images or videos. Maximum Mutual Information (MMI) is a commonly used method that can be used for moving target detection. This article will introduce how to use MATLAB to implement moving target detection based on maximum mutual information, and provide the corresponding source code.

1. Introduction
   Maximum mutual information is a measure of the correlation between two random variables. In moving target detection, we can use the maximum mutual information to measure the similarity between two frames in the image sequence to detect moving targets.

2. Algorithm steps
   The following are the steps of the moving target detection algorithm based on maximum mutual information:

Step 1: Read the input image sequence
First, we need to read the input image sequence. You can use MATLAB's image processing functions to achieve this step.

% 读取图像序列
imageSequence = readImageSequence('image_sequence_folder');

Step 2: Extract the moving target area
Next, we need to extract the moving target area in the image sequence. This step can be accomplished using various moving target detection algorithms, such as optical flow or differential image methods. in the text,