鱼眼相机 去畸变

目录

枕形畸变和去枕形畸变

去枕形畸变失败

枕形畸变和去枕形畸变

import cv2
import numpy as np
import matplotlib.pyplot as plt# 创建一个带网格的原始图像
def create_grid(image_size=512, grid_size=20):image = np.zeros((image_size, image_size, 3), dtype=np.uint8)for i in range(0, image_size, grid_size):cv2.line(image, (i, 0), (i, image_size), (255, 255, 255), 1)cv2.line(image, (0, i), (image_size, i), (255, 255, 255), 1)return image# 应用枕形畸变
def apply_pincushion_distortion(image, k1=0.05):image_size = image.shape[0]fx, fy = image_size * 1.0, image_size * 1.0cx, cy = image_size / 2, image_size / 2camera_matrix = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])dist_coeffs = np.array([k1, 0, 0, 0, 0])  # 正值增加枕形畸变h, w = image.shape[:2]new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coeffs, (w, h), 1)distorted_image = cv2.undistort(image, camera_matrix, dist_coeffs, None, new_camera_matrix)return distorted_image# 去除枕形畸变
def remove_pincushion_distortion(image, k1=0.0005):image_size = image.shape[0]fx, fy = image_size * 1.0, image_size * 1.0cx, cy = image_size / 2, image_size / 2camera_matrix = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])dist_coeffs = np.array([-k1, 0, 0, 0, 0])  # 负值去除枕形畸变h, w = image.shape[:2]new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coeffs, (w, h), 1)undistorted_image = cv2.undistort(image, camera_matrix, dist_coeffs, None, new_camera_matrix)return undistorted_image# 主函数
if __name__ == "__main__":original_grid = create_grid()distorted_grid = apply_pincushion_distortion(original_grid,k1=-0.2)undistorted_grid = remove_pincushion_distortion(distorted_grid,k1=-0.2-0.2)# 使用 OpenCV 展示图像cv2.imshow('Original Image', original_grid)cv2.imshow('Pincushion Distorted Image', distorted_grid)cv2.imshow('Undistorted Image', undistorted_grid)cv2.waitKey(0)cv2.destroyAllWindows()

去枕形畸变失败

import cv2
import numpy as np
import matplotlib.pyplot as plt# 创建一个带有枕形畸变的网格图像
def create_pincushion_distorted_grid(image_size=512, grid_size=20):image = np.zeros((image_size, image_size, 3), dtype=np.uint8)for i in range(0, image_size, grid_size):cv2.line(image, (i, 0), (i, image_size), (255, 255, 255), 1)cv2.line(image, (0, i), (image_size, i), (255, 255, 255), 1)k1, k2, p1, p2, k3 = -0.2, 0, 0, 0, 0  # 负数制造枕形畸变fx, fy = image_size, image_sizecx, cy = image_size / 2, image_size / 2camera_matrix = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])dist_coeffs = np.array([k1, k2, p1, p2, k3])map1, map2 = cv2.initUndistortRectifyMap(camera_matrix, dist_coeffs, None, camera_matrix, (image_size, image_size), 5)distorted_image = cv2.remap(image, map1, map2, cv2.INTER_LINEAR)return image, distorted_image, camera_matrix, dist_coeffs# 去除枕形畸变
def undistort_image(image, camera_matrix, dist_coeffs):h, w = image.shape[:2]new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coeffs, (w, h), 1, (w, h))undistorted_image = cv2.undistort(image, camera_matrix, dist_coeffs, None, new_camera_matrix)return undistorted_image# 主函数
if __name__ == "__main__":original_grid, distorted_grid, camera_matrix, dist_coeffs = create_pincushion_distorted_grid()# 手动生成去畸变的映射map1, map2 = cv2.initUndistortRectifyMap(camera_matrix, dist_coeffs, None, camera_matrix, (original_grid.shape[1], original_grid.shape[0]), cv2.CV_32FC1)undistorted_grid = cv2.remap(distorted_grid, map1, map2, cv2.INTER_LINEAR)# 使用 OpenCV 展示图像cv2.imshow('Original Image', original_grid)cv2.imshow('Distorted Image', distorted_grid)cv2.imshow('Undistorted Image', undistorted_grid)cv2.waitKey(0)cv2.destroyAllWindows()