双目图像的畸变矫正代码

双目图像的畸变矫正主要包括以下步骤：

1. 标定相机，获取相机的内参和畸变参数；
2. 对左右两张图像进行畸变矫正；
3. 对两张图像进行立体匹配。

下面是Python代码实现：

import cv2
import numpy as np

# 标定相机，获取相机的内参和畸变参数
def calibrate_camera(images, chessboard_size):
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
    objp = np.zeros((chessboard_size[0]*chessboard_size[1], 3), np.float32)
    objp[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2)
    objpoints = []
    imgpoints = []
    
    for image in images:
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        ret, corners = cv2.findChessboardCorners(gray, chessboard_size, None)
        
        if ret:
            objpoints.append(objp)
            corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
            imgpoints.append(corners2)
            
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
    
    return mtx, dist

# 对左右两张图像进行畸变矫正
def undistort_images(images, mtx, dist):
    undistorted_images = []
    
    for image in images:
        undistorted_image = cv2.undistort(image, mtx, dist)
        undistorted_images.append(undistorted_image)
        
    return undistorted_images

# 对两张图像进行立体匹配
def stereo_match(left_image, right_image):
    window_size = 3
    min_disp = 16
    num_disp = 112 - min_disp
    stereo = cv2.StereoSGBM_create(minDisparity=min_disp, numDisparities=num_disp, blockSize=window_size)
    gray_left = cv2.cvtColor(left_image, cv2.COLOR_BGR2GRAY)
    gray_right = cv2.cvtColor(right_image, cv2.COLOR_BGR2GRAY)
    disparity = stereo.compute(gray_left, gray_right)
    
    return disparity

# 读取左右两张图像
left_image = cv2.imread('left_image.jpg')
right_image = cv2.imread('right_image.jpg')

# 标定相机，获取相机的内参和畸变参数
mtx, dist = calibrate_camera([left_image, right_image], (9, 6))

# 对左右两张图像进行畸变矫正
undistorted_left_image, undistorted_right_image = undistort_images([left_image, right_image], mtx, dist)

# 对两张图像进行立体匹配
disparity = stereo_match(undistorted_left_image, undistorted_right_image)

# 显示结果
cv2.imshow('Left Image', left_image)
cv2.imshow('Right Image', right_image)
cv2.imshow('Undistorted Left Image', undistorted_left_image)
cv2.imshow('Undistorted Right Image', undistorted_right_image)
cv2.imshow('Disparity', disparity)
cv2.waitKey(0)
cv2.destroyAllWindows()

其中，`calibrate_camera`函数用于标定相机，获取相机的内参和畸变参数；`undistort_images`函数用于对左右两张图像进行畸变矫正；`stereo_match`函数用于对两张图像进行立体匹配。最后，使用`cv2.imshow`函数显示结果。