python代码实现单目相机的无裁剪畸变矫正

单目相机的无裁剪畸变矫正可以通过opencv库实现，具体操作步骤如下：

1. 读取相机内参矩阵和畸变系数

import cv2
import numpy as np

# 读取相机内参矩阵和畸变系数
camera_matrix = np.loadtxt('camera_matrix.txt')
dist_coeffs = np.loadtxt('dist_coeffs.txt')

2. 读取待校正的图像

# 读取待校正的图像
img = cv2.imread('distorted_img.png')

3. 根据相机内参矩阵和畸变系数计算映射矩阵

# 计算映射矩阵
h, w = img.shape[:2]
new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coeffs, (w, h), 1, (w, h))
mapx, mapy = cv2.initUndistortRectifyMap(camera_matrix, dist_coeffs, None, new_camera_matrix, (w, h), 5)

4. 对图像进行矫正

# 进行矫正
dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)

完整代码如下：

import cv2
import numpy as np

# 读取相机内参矩阵和畸变系数
camera_matrix = np.loadtxt('camera_matrix.txt')
dist_coeffs = np.loadtxt('dist_coeffs.txt')

# 读取待校正的图像
img = cv2.imread('distorted_img.png')

# 计算映射矩阵
h, w = img.shape[:2]
new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coeffs, (w, h), 1, (w, h))
mapx, mapy = cv2.initUndistortRectifyMap(camera_matrix, dist_coeffs, None, new_camera_matrix, (w, h), 5)

# 进行矫正
dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)

# 显示结果
cv2.imshow('original', img)
cv2.imshow('corrected', dst)
cv2.waitKey(0)

其中，`camera_matrix.txt` 和 `dist_coeffs.txt` 分别是相机内参矩阵和畸变系数的文本文件，可以通过相机标定获取。`distorted_img.png` 是待校正的图像。