Initial commit

new file:   Copy_of_Exz_with_hamamatsu.m
	new file:   Exz_mod.m
	new file:   Exz_with_hamamatsu.m
	new file:   GS.m
	new file:   MRAF.m
	new file:   MRAF_8bit.bmp
	new file:   PSF of spherical aberration/Exz.m
	new file:   PSF of spherical aberration/Thumbs.db
	new file:   PSF of spherical aberration/josaa-12-10-2136.pdf
	new file:   PSF of spherical aberration/josaa-12-2-325.pdf
	new file:   PSF of spherical aberration/main.m
	new file:   "PSF of spherical aberration/\351\207\215\350\246\201psf\346\226\207\347\214\256.pdf"
	new file:   Spherical_aberration_SiminCao.m
	new file:   gen_m.m
	new file:   gen_rectangle.m
	new file:   hamamatsu.m
	new file:   m.tif
	new file:   m2.tif
	new file:   photo/50-30.BMP
	new file:   photo/8bit_50-30.BMP
	new file:   photo/8bit_ellipse.BMP
	new file:   photo/convert_8bit.exe
	new file:   photo/ellipse.BMP
	new file:   rect_MRAF_SiminCao.m
	new file:   rectangle.tif
	new file:   size/.vscode/settings.json
	new file:   size/black_c_20THSize_4f_1.064lamda.bmp
	new file:   size/black_c_30THSize_4f_61.064lamda.bmp
	new file:   size/black_output.bmp
	new file:   size/black_rect_30THSize_4f_1.064lamda.bmp
	new file:   size/black_rect_30THSize_4f_6_1.064lamda.bmp
	new file:   size/c_20THSize_4f_1.064lamda.bmp
	new file:   size/c_20THSize_4f_1.064lamda_resize.bmp
	new file:   size/c_30THSize_4f_61.064lamda.bmp
	new file:   size/c_30THSize_4f_61.064lamda_resize.bmp
	new file:   size/noisy_output.bmp
	new file:   size/output.bmp
	new file:   size/rect_30THSize_4f_1.064lamda.bmp
	new file:   size/rect_30THSize_4f_1.064lamda_resize.bmp
	new file:   size/rect_30THSize_4f_6_1.064lamda.bmp
	new file:   size/rect_30THSize_4f_6_1.064lamda_resize.bmp
	new file:   size/resize_4.7z
	new file:   size/resize_black.7z
	new file:   size/size copy.py
	new file:   size/size.py
	new file:   size/wave.7z
	new file:   sp.m
	new file:   to8bit.m
	new file:   trans_8bit.zip
	new file:   wavef/A.bmp
	new file:   wavef/B_linear.bmp
	new file:   wavef/PHA SID230828-2003.csv
	new file:   wavef/PHA_bilinear_1280_1024.csv
	new file:   wavef/PHA_bilinear_reversal.csv
	new file:   wavef/PHA_output_1280_1024.csv
	new file:   wavef/Untitled-1.py
	new file:   wavef/filled.bmp
	new file:   wavef/from PIL import Image.py
	new file:   wavef/matrix_filled.csv
	new file:   wavef/output.bmp
	new file:   wavef/output.csv
	new file:   wavef/output2.bmp
	new file:   wavef/pha_wavef copy.py
	new file:   wavef/pha_wavef.py
	new file:   wavef/pha_wavef_step.py
	new file:   wavef/wavef.zip
	new file:   wavef/xy_values.csv
	new file:   "wavef/\346\226\260\345\273\272\346\226\207\344\273\266\345\244\271/matrix.csv"
	new file:   "wavef/\346\226\260\345\273\272\346\226\207\344\273\266\345\244\271/matrix_filled.csv"
This commit is contained in:
wxchen
2023-08-29 23:06:40 +08:00
commit ba13a3f053
69 changed files with 1320863 additions and 0 deletions

46
size/size.py Normal file
View File

@@ -0,0 +1,46 @@
from PIL import Image
import numpy as np
# 读取原始图像
path = "c_30THSize_4f_61.064lamda.bmp"
original_image = Image.open(path)
original_width, original_height = original_image.size
# 创建目标图像1280x1024像素灰度模式
target_width, target_height = 1280, 1024
target_image = Image.new("L", (target_width, target_height), color=0)
# 计算图像放置位置
x_offset = (target_width - original_width) // 2
y_offset = (target_height - original_height) // 2
# 将原始图像放置在目标图像中央
target_image.paste(original_image, (x_offset, y_offset))
# 将目标图像转换为NumPy数组
target_array = np.array(target_image)
# # 在周围填充随机噪声
# noise_level = 256 # 随机噪声的灰度级别
# noise = np.random.randint(
# 0, noise_level, (target_height, target_width)).astype(np.uint8)
# target_array = np.where(target_array == 0, noise, target_array)
# # 创建包含噪声的新图像
# noisy_image = Image.fromarray(target_array.astype(np.uint8))
# # 保存为位图BMP图像
# noisy_image.save("black_"+path)
# 创建黑色填充
black_color = 0 # 黑色像素值为0
target_array[:y_offset, :] = black_color # 上方填充
target_array[y_offset + original_height:, :] = black_color # 下方填充
target_array[:, :x_offset] = black_color # 左侧填充
target_array[:, x_offset + original_width:] = black_color # 右侧填充
# 创建包含黑色填充的新图像
padded_image = Image.fromarray(target_array)
# 保存为位图BMP图像
padded_image.save("black_"+path)