221 lines
8.7 KiB
Python
221 lines
8.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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HyTools: Hyperspectral image processing library
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Copyright (C) 2021 University of Wisconsin
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Authors: Adam Chlus, Zhiwei Ye, Philip Townsend.
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, version 3 of the License.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <https://www.gnu.org/licenses/>.
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本模块包含用于计算和应用单一（“通用”）组乘法 BRDF 校正系数的函数。系数可以按飞行线计算，也可以跨多个飞行线计算。
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"""
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from itertools import product
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from copy import deepcopy
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import numpy as np
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import ray
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from scipy.optimize import minimize
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from .kernels import calc_volume_kernel,calc_geom_kernel
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from ..misc import progbar
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from ..misc import update_brdf
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from ..masks import mask_create
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from ..plotting import universal_diagno_plot
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def universal_brdf(actors,config_dict):
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brdf_dict = config_dict['brdf']
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if brdf_dict['grouped']:
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actors = calc_universal_group(actors)
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else:
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_ = ray.get([a.do.remote(calc_universal_single) for a in actors])
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if brdf_dict['diagnostic_plots']:
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print('Exporting diagnostic plots.')
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_ = ray.get([a.do.remote(universal_diagno_plot,config_dict) for a in actors])
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def sample_kernels(hy_obj):
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'''计算并采样 BRDF 核函数
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'''
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#Sample kernel images
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geom_kernel = hy_obj.geom_kernel(hy_obj.brdf['geometric'],
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b_r=hy_obj.brdf["b/r"],
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h_b =hy_obj.brdf["h/b"])[hy_obj.mask['calc_brdf']]
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vol_kernel = hy_obj.volume_kernel(hy_obj.brdf['volume'])[hy_obj.mask['calc_brdf']]
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X = np.vstack([vol_kernel,geom_kernel,
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np.ones(vol_kernel.shape)]).T
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return X
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def subsample_mask(hy_obj):
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'''对计算掩膜进行子采样并更新
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'''
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if hy_obj.brdf['sample_perc'] < 1:
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idx = np.array(np.where(hy_obj.mask['calc_brdf'])).T
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idx_rand= idx[np.random.choice(range(len(idx)),
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int(len(idx)*(1- hy_obj.brdf['sample_perc'])),
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replace = False)].T
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hy_obj.mask['calc_brdf'][idx_rand[0],idx_rand[1]] = False
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def calc_universal_single(hy_obj):
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'''逐条飞行线计算 BRDF 系数。
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'''
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subsample_mask(hy_obj)
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X = sample_kernels(hy_obj)
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hy_obj.brdf['coeffs'] = {}
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for band_num,band in enumerate(hy_obj.bad_bands):
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if ~band:
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band = hy_obj.get_band(band_num,
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corrections = hy_obj.corrections, mask='calc_brdf')
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brdf_coeff = np.linalg.lstsq(X, band,rcond=None)[0].flatten().tolist()
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hy_obj.brdf['coeffs'][band_num] = brdf_coeff
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def calc_universal_group(actors):
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'''使用所有飞行线的合并数据计算 BRDF 系数。
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'''
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_ = ray.get([a.do.remote(subsample_mask) for a in actors])
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X = ray.get([a.do.remote(sample_kernels) for a in actors])
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X = np.concatenate(X)
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bad_bands = ray.get(actors[0].do.remote(lambda x: x.bad_bands))
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corections = ray.get(actors[0].do.remote(lambda x: x.corrections))
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coeffs = {}
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for band_num,band in enumerate(bad_bands):
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if ~band:
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y = ray.get([a.get_band.remote(band_num,mask='calc_brdf',
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corrections = corections) for a in actors])
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y = np.concatenate(y)
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coeffs[band_num] = np.linalg.lstsq(X, y)[0].flatten().tolist()
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progbar(np.sum(~bad_bands[:band_num+1]),np.sum(~bad_bands))
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print('\n')
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# 更新 BRDF 系数
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_ = ray.get([a.do.remote(update_brdf,{'key':'coeffs',
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'value': coeffs}) for a in actors])
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return actors
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def apply_universal(hy_obj,data,dimension,index):
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''' 对数据切片应用通用 BRDF 校正
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参数:
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hy_obj : Hytools 类对象。
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data (np.ndarray): 数据切片。
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index (int,list): 数据索引。
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返回:
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data (np.ndarray): BRDF 校正后的数据切片。
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'''
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if 'k_vol' not in hy_obj.ancillary:
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hy_obj.ancillary['k_vol'] = hy_obj.volume_kernel(hy_obj.brdf['volume'])
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if 'k_geom' not in hy_obj.ancillary:
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hy_obj.ancillary['k_geom'] = hy_obj.geom_kernel(hy_obj.brdf['geometric'],
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b_r=hy_obj.brdf["b/r"],
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h_b =hy_obj.brdf["h/b"])
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if ('k_vol_nadir' not in hy_obj.ancillary) or ('k_geom_nadir' not in hy_obj.ancillary):
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solar_zn = hy_obj.brdf['solar_zn_norm_radians'] * np.ones((hy_obj.lines,hy_obj.columns))
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hy_obj.ancillary['k_vol_nadir'] = calc_volume_kernel(0,solar_zn,
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0,0,hy_obj.brdf['volume'])
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hy_obj.ancillary['k_geom_nadir'] = calc_geom_kernel(0,solar_zn,
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0,0,hy_obj.brdf['geometric'],
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b_r=hy_obj.brdf["b/r"],
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h_b =hy_obj.brdf["h/b"])
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if 'apply_brdf' not in hy_obj.mask:
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hy_obj.gen_mask(mask_create,'apply_brdf',hy_obj.brdf['apply_mask'])
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brdf_bands = [int(x) for x in hy_obj.brdf['coeffs'].keys()]
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fvol, fgeo, fiso = np.array([hy_obj.brdf['coeffs'][band] for band in hy_obj.brdf['coeffs'].keys()]).T
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# 转换为浮点数
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data = data.astype(np.float32)
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if dimension == 'line':
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brdf = fvol[:,np.newaxis]*hy_obj.ancillary['k_vol'][[index],:]
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brdf+= fgeo[:,np.newaxis]*hy_obj.ancillary['k_geom'][[index],:]
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brdf+= fiso[:,np.newaxis]
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brdf_nadir = fvol[:,np.newaxis]*hy_obj.ancillary['k_vol_nadir'][[index],:]
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brdf_nadir+= fgeo[:,np.newaxis]*hy_obj.ancillary['k_geom_nadir'][[index],:]
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brdf_nadir+= fiso[:,np.newaxis]
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correction_factor = brdf_nadir/brdf
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correction_factor[:,~hy_obj.mask['apply_brdf'][index,:]] = 1
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data[:,brdf_bands] = data[:,brdf_bands]*correction_factor.T
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elif dimension == 'column':
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brdf = fvol[np.newaxis,:]*hy_obj.ancillary['k_vol'][:,[index]]
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brdf+= fgeo[np.newaxis,:]*hy_obj.ancillary['k_geom'][:,[index]]
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brdf+= fiso[np.newaxis,:]
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brdf_nadir = fvol[np.newaxis,:]*hy_obj.ancillary['k_vol_nadir'][:,[index]]
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brdf_nadir+= fgeo[np.newaxis,:]*hy_obj.ancillary['k_geom_nadir'][:,[index]]
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brdf_nadir+= fiso[np.newaxis,:]
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correction_factor = brdf_nadir/brdf
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correction_factor[~hy_obj.mask['apply_brdf'][:,index],:] = 1
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data[:,brdf_bands] = data[:,brdf_bands]*correction_factor.T
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elif dimension == 'band':
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fvol, fgeo, fiso = hy_obj.brdf['coeffs'][index]
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brdf = fvol*hy_obj.ancillary['k_vol']
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brdf += fgeo*hy_obj.ancillary['k_geom']
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brdf+=fiso
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brdf_nadir = fvol*hy_obj.ancillary['k_vol_nadir']
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brdf_nadir+= fgeo*hy_obj.ancillary['k_geom_nadir']
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brdf_nadir+= fiso
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correction_factor = brdf_nadir/brdf
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correction_factor[~hy_obj.mask['apply_brdf']] = 1
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data= data* correction_factor
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elif dimension == 'chunk':
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x1,x2,y1,y2 = index
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brdf = fvol[np.newaxis,np.newaxis,:]*hy_obj.ancillary['k_vol'][y1:y2,x1:x2,np.newaxis]
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brdf+= fgeo[np.newaxis,np.newaxis,:]*hy_obj.ancillary['k_geom'][y1:y2,x1:x2,np.newaxis]
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brdf+= fiso[np.newaxis,np.newaxis,:]
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brdf_nadir = fvol[np.newaxis,np.newaxis,:]*hy_obj.ancillary['k_vol_nadir'][y1:y2,x1:x2,np.newaxis]
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brdf_nadir+= fgeo[np.newaxis,np.newaxis,:]*hy_obj.ancillary['k_geom_nadir'][y1:y2,x1:x2,np.newaxis]
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brdf_nadir+= fiso[np.newaxis,np.newaxis,:]
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correction_factor = brdf_nadir/brdf
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correction_factor[~hy_obj.mask['apply_brdf'][y1:y2,x1:x2]] = 1
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data[:,:,brdf_bands] = data[:,:,brdf_bands]*correction_factor
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elif dimension == 'pixels':
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y,x = index
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brdf = fvol[np.newaxis,:]*hy_obj.ancillary['k_vol'][y,x,np.newaxis]
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brdf+= fgeo[np.newaxis,:]*hy_obj.ancillary['k_geom'][y,x,np.newaxis]
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brdf+= fiso[np.newaxis,:]
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brdf_nadir = fvol[np.newaxis,:]*hy_obj.ancillary['k_vol_nadir'][y,x,np.newaxis]
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brdf_nadir+= fgeo[np.newaxis,:]*hy_obj.ancillary['k_geom_nadir'][y,x,np.newaxis]
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brdf_nadir+= fiso[np.newaxis,:]
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correction_factor = brdf_nadir/brdf
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correction_factor[~hy_obj.mask['apply_brdf'][y,x]] = 1
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data[:,brdf_bands] = data[:,brdf_bands]*correction_factor
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return data
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