54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
import numpy as np
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from spectral.io import envi
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from PIL import Image
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import matplotlib.pyplot as plt
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import os
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def linear_stretch_2_percent(data):
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"""
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应用2%线性拉伸到数据
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参数:
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data: 输入的单波段数据
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返回:
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拉伸后的数据 (0-255)
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"""
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# 计算2%和98%的分位数
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low = np.percentile(data, 2)
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high = np.percentile(data, 98)
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# 应用线性拉伸
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stretched = np.clip((data - low) / (high - low), 0, 1) * 255
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return stretched.astype(np.uint8)
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def process_bil_files(input_folder):
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"""
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处理BIL文件：读取10、60、160波段并导出为PNG
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参数:
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input_folder: 包含BIL文件的输入文件夹
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"""
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# 读取BIL文件
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img = envi.open(input_folder.replace('.bil', '.hdr'), input_folder)
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# 读取指定波段（10, 60, 160）
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# 注意：波段索引从0开始，所以10波段是索引9，以此类推
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band_10 = img.read_band(9)
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band_60 = img.read_band(59)
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band_160 = img.read_band(159)
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# 应用2%线性拉伸到每个波段
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band_10_stretched = linear_stretch_2_percent(band_10)
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band_60_stretched = linear_stretch_2_percent(band_60)
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band_160_stretched = linear_stretch_2_percent(band_160)
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# 创建RGB图像（分别对应10,60,160波段）
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rgb_img = np.stack([band_10_stretched, band_60_stretched, band_160_stretched], axis=-1)
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# 将NumPy数组转换为PIL图像
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# 确保值在0-255范围内并转换为uint8类型
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rgb_img_pil = Image.fromarray((rgb_img).astype(np.uint8))
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return rgb_img_pil
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