|
马上注册,结交更多好友,享用更多功能^_^
您需要 登录 才可以下载或查看,没有账号?立即注册
x
代码:
import cv2
import numpy as np
# 1. 分割遥感影像为多块图幅
def split_image(image, block_size):
height, width = image.shape[:2]
block_images = []
for i in range(0, height, block_size):
for j in range(0, width, block_size):
block = image[i:i+block_size, j:j+block_size]
block_images.append(block)
return block_images
# 2. 分别对每块图幅转为灰度图像
def convert_to_gray(image):
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
return gray_image
# 3. 对各个图像进行边缘检测
# def edge_detection(image):
# edges = cv2.Canny(image, 0.5, 2)
# return edges
def edge_detection(image):
sobel_x = cv2.Sobel(image, cv2.CV_64F, 1, 0, ksize=3)
sobel_y = cv2.Sobel(image, cv2.CV_64F, 0, 1, ksize=3)
edges = cv2.magnitude(sobel_x, sobel_y)
edges = cv2.convertScaleAbs(edges)
return edges
# 4. 消除噪声干扰
def remove_noise(image):
denoised_image = cv2.medianBlur(image, 5)
return denoised_image
# 5. 将各个图幅合并为一个图幅
#
# def merge_images(images, block_size):
# num_blocks = len(images)
# rows = int(np.ceil(np.sqrt(num_blocks))) # 向上取整
# cols = rows
# merged_image = np.zeros((rows * block_size, cols * block_size), dtype=np.uint8)
# for i, image in enumerate(images):
# x = (i % cols) * block_size
# y = (i // cols) * block_size
# merged_image[y:y+image.shape[0], x:x+image.shape[1]] = image
# return merged_image
def merge_images(images, original_image_shape):
merged_image = np.zeros(original_image_shape, dtype=np.uint8)
block_size = images[0].shape[0] # assume all blocks have the same size
rows = original_image_shape[0] // block_size
cols = original_image_shape[1] // block_size
for i, image in enumerate(images):
x = (i % cols) * block_size
y = (i // cols) * block_size
merged_image[y:y+image.shape[0], x:x+image.shape[1]] = image
return merged_image
# 6. 导出结果
def export_result(image, file_path):
cv2.imwrite(file_path, image)
# 示例代码
image_path = r"C:\Users\WINDOWS\Desktop\taiyuan\python\dune\dune.tif"
block_size = 800
# 读取遥感影像
image = cv2.imread(image_path)
# 1. 分割遥感影像为多块图幅
block_images = split_image(image, block_size)
# 2. 分别对每块图幅转为灰度图像
gray_images = [convert_to_gray(block) for block in block_images]
# 3. 对各个图像进行边缘检测
edges_images = [edge_detection(gray) for gray in gray_images]
# 4. 消除噪声干扰
denoised_images = [remove_noise(edges) for edges in edges_images]
# 5. 将各个图幅合并为一个图幅
# merged_image = merge_images(denoised_images, block_size)
merged_image = merge_images(denoised_images, image.shape)
# 6. 导出结果
export_result(merged_image, "output.jpg")
报错:
Traceback (most recent call last):
File "C:\Users\WINDOWS\Desktop\taiyuan\python\segement.py", line 87, in <module>
merged_image = merge_images(denoised_images, image.shape)
File "C:\Users\WINDOWS\Desktop\taiyuan\python\segement.py", line 59, in merge_images
merged_image[y:y+image.shape[0], x:x+image.shape[1]] = image
ValueError: could not broadcast input array from shape (800,800) into shape (800,800,3) |
|