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Flexbrdf/hytools/topo/modminn.py

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+# -*- coding: utf-8 -*-
+"""
+HyTools:  Hyperspectral image processing library
+Copyright (C) 2021 University of Wisconsin
+
+Authors: Adam Chlus, Zhiwei Ye, Philip Townsend.
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, version 3 of the License.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+This module contains functions to apply the Modified topographic correction (SCS+C)
+described in the following paper:
+
+Richter, R., Kellenberger, T., & Kaufmann, H. (2009).
+Comparison of topographic correction methods.
+Remote Sensing, 1(3), 184-196.
+https://doi.org/10.3390/rs1030184
+
+Topographic correction consists of the following steps:
+
+
+"""
+import numpy as np
+
+def calc_modminn_coeffs(hy_obj,topo_dict):
+    '''
+
+    Args:
+        hy_obj (TYPE): DESCRIPTION.
+
+    Returns:
+        None.
+
+    '''
+    hy_obj.topo =topo_dict
+
+    cos_i = hy_obj.cosine_i()
+    i = np.rad2deg(np.arccos(cos_i))
+    solar_zn = hy_obj.get_anc('solar_zn',radians=False)
+
+    solar_zn_t = np.zeros(solar_zn.shape)
+    solar_zn_t[solar_zn < 45] = solar_zn[solar_zn < 45] +20
+    solar_zn_t[(solar_zn >= 45) & (solar_zn <= 55)] = solar_zn[(solar_zn >= 45) & (solar_zn <= 55)] +15
+    solar_zn_t[solar_zn > 55] = solar_zn[solar_zn > 55] +10
+
+    #Create NDVI mask to seperate vegetation
+    ir = hy_obj.get_wave(850)
+    red = hy_obj.get_wave(660)
+    ndvi = (ir-red)/(ir+red)
+    veg_mask = ndvi > 0.2
+
+    c_factors = np.ones((2,hy_obj.lines,hy_obj.columns))
+    c_factors[:] = cos_i/np.cos(np.radians(solar_zn_t))
+
+    # Non vegetation correction factor
+    c_factors[0][~veg_mask] =  c_factors[0][~veg_mask]**(1/2)
+    c_factors[1][~veg_mask] =  c_factors[1][~veg_mask]**(1/2)
+
+    # Vegetation correction factor
+    c_factors[0][veg_mask] =  c_factors[0][veg_mask]**(3/4)
+    c_factors[1][veg_mask] =  c_factors[1][veg_mask]**(1/3)
+
+    #Adjust correction factors to prevent too strong correction
+    c_factors[c_factors <.25] = .25
+    c_factors[c_factors > 1] = 1
+
+    #Correct pixels only where i > threshold
+    c_factors[0][i < solar_zn_t] = 1
+    c_factors[1][i < solar_zn_t] = 1
+
+    c_factors[0][ir == hy_obj.no_data] = 1
+    c_factors[1][ir == hy_obj.no_data] = 1
+
+    hy_obj.ancillary['mm_c_factor'] = c_factors
+
+def apply_modminn(hy_obj,data,dimension,index):
+    ''' Apply SCSS correction to a slice of the data
+
+    Args:
+        hy_obj (TYPE): DESCRIPTION.
+        band (TYPE): DESCRIPTION.
+        index (TYPE): DESCRIPTION.
+
+    Returns:
+        band (TYPE): DESCRIPTION.
+
+    '''
+
+    if 'mm_c_factor' not in hy_obj.ancillary.keys():
+        calc_modminn_coeffs(hy_obj)
+
+    #Convert to float
+    data = data.astype(np.float32)
+
+    wave_mask =hy_obj.wavelengths >=720
+
+    if dimension == 'line':
+        #index= 3000
+        #data = hy_obj.get_line(3000)
+        data[:,wave_mask] = data[:,wave_mask]*hy_obj.ancillary['mm_c_factor'][1,index,:][:,np.newaxis]
+        data[:,~wave_mask] = data[:,~wave_mask]*hy_obj.ancillary['mm_c_factor'][0,index,:][:,np.newaxis]
+
+    elif dimension == 'column':
+        #index= 300
+        #data = hy_obj.get_column(index)
+        data[:,wave_mask] = data[:,wave_mask]*hy_obj.ancillary['mm_c_factor'][1,:,index][:,np.newaxis]
+        data[:,~wave_mask] = data[:,~wave_mask]*hy_obj.ancillary['mm_c_factor'][0,:,index][:,np.newaxis]
+
+    elif dimension == 'band':
+        #index= 50
+        #data = hy_obj.get_band(index)
+        if hy_obj.wavelengths[index] >=720:
+            cf_index = 1
+        else:
+            cf_index = 0
+        data = data * hy_obj.ancillary['mm_c_factor'][cf_index]
+
+    elif dimension == 'chunk':
+        #index = 200,501,3000,3501
+        x1,x2,y1,y2 = index
+        #data = hy_obj.get_chunk(x1,x2,y1,y2)
+        data[:,:,wave_mask]  = data[:,:,wave_mask]*hy_obj.ancillary['mm_c_factor'][1,y1:y2,x1:x2][:,:,np.newaxis]
+        data[:,:,~wave_mask] = data[:,:,~wave_mask]*hy_obj.ancillary['mm_c_factor'][0,y1:y2,x1:x2][:,:,np.newaxis]
+
+    elif dimension == 'pixels':
+        #index = [[2000,2001],[200,501]]
+        y,x = index
+        #data = hy_obj.get_pixels(y,x)
+        data[:,wave_mask] = data[:,wave_mask]*hy_obj.ancillary['mm_c_factor'][1,y,x][:, np.newaxis]
+        data[:,~wave_mask] = data[:,~wave_mask]*hy_obj.ancillary['mm_c_factor'][0,y,x][:, np.newaxis]
+    return data