Image Registration Based on Matlab SIFT Algorithm

Image Registration Based on Matlab SIFT Algorithm

Image registration is one of the important problems in the field of computer vision, which is used to align two or more images so that they can achieve the best match at the geometric and pixel level. SIFT algorithm is a commonly used image registration technology, which has the characteristics of high efficiency, accuracy and robustness.

This article will introduce how to use Matlab to implement image registration based on SIFT algorithm, including steps such as image preprocessing, key point detection, feature description, feature matching, and image transformation.

1. Image preprocessing

Before the SIFT algorithm image registration, it is necessary to do some preprocessing work on the original image in order to better extract the local features of the image. Common preprocessing methods include operations such as grayscale, normalization, denoising, and edge detection.

The following is the code for grayscale and normalization:

% 读取图片并转化为灰度图
img1 = imread('image1.jpg');
img2 = imread('image2.jpg');
gray