Fixed some bugs in rubbersheeting and runInterferogram
vbrancat
parent
37a510fd2d
commit
532cfa085b
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@ -31,14 +31,14 @@ def write_xml(fileName,width,length,bands,dataType,scheme):
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return None
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def compute_FlatEarth(self,width,length):
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def compute_FlatEarth(self,ifgFilename,width,length,radarWavelength):
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from imageMath import IML
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import logging
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# If rubbersheeting has been performed add back the range sheet offsets
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info = self._insar.loadProduct(self._insar.slaveSlcCropProduct)
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radarWavelength = info.getInstrument().getRadarWavelength()
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#radarWavelength = info.getInstrument().getRadarWavelength()
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rangePixelSize = info.getInstrument().getRangePixelSize()
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fact = 4 * np.pi* rangePixelSize / radarWavelength
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@ -55,7 +55,7 @@ def compute_FlatEarth(self,width,length):
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rng2 = np.zeros((length,width))
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# Open the interferogram
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ifgFilename= os.path.join(self.insar.ifgDirname, self.insar.ifgFilename)
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#ifgFilename= os.path.join(self.insar.ifgDirname, self.insar.ifgFilename)
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intf = np.memmap(ifgFilename+'.full',dtype=np.complex64,mode='r+',shape=(length,width))
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for ll in range(length):
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@ -126,7 +126,8 @@ def computeCoherence(slc1name, slc2name, corname, virtual=True):
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return
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# Modified by V. Brancato on 10.09.2019 (added self)
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def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks):
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# Modified by V. Brancato on 11.13.2019 (added radar wavelength for low and high band flattening
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def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks,radarWavelength):
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objSlc1 = isceobj.createSlcImage()
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IU.copyAttributes(imageSlc1, objSlc1)
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objSlc1.setAccessMode('read')
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@ -192,7 +193,7 @@ def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks):
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objCrossmul.crossmul(objSlc1, objSlc2, objInt, objAmp)
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# Remove Flat-Earth component
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compute_FlatEarth(self,intWidth,lines)
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compute_FlatEarth(self,resampInt,intWidth,lines,radarWavelength)
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# Perform Multilook
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multilook(resampInt+'.full', outname=resampInt, alks=azLooks, rlks=rgLooks) #takeLooks(objAmp,azLooks,rgLooks)
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@ -206,7 +207,7 @@ def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks):
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return imageInt, imageAmp
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def subBandIgram(self, masterSlc, slaveSlc, subBandDir):
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def subBandIgram(self, masterSlc, slaveSlc, subBandDir,radarWavelength):
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img1 = isceobj.createImage()
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img1.load(masterSlc + '.xml')
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@ -226,7 +227,7 @@ def subBandIgram(self, masterSlc, slaveSlc, subBandDir):
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interferogramName = os.path.join(ifgDir , self.insar.ifgFilename)
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generateIgram(self,img1, img2, interferogramName, azLooks, rgLooks)
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generateIgram(self,img1, img2, interferogramName, azLooks, rgLooks,radarWavelength)
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return interferogramName
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@ -259,9 +260,9 @@ def runSubBandInterferograms(self):
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slaveHighBandSlc = os.path.join(coregDir , os.path.basename(slaveSlc))
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##########
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interferogramName = subBandIgram(self, masterLowBandSlc, slaveLowBandSlc, self.insar.lowBandSlcDirname)
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interferogramName = subBandIgram(self, masterLowBandSlc, slaveLowBandSlc, self.insar.lowBandSlcDirname,self.insar.lowBandRadarWavelength)
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interferogramName = subBandIgram(self, masterHighBandSlc, slaveHighBandSlc, self.insar.highBandSlcDirname)
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interferogramName = subBandIgram(self, masterHighBandSlc, slaveHighBandSlc, self.insar.highBandSlcDirname,self.insar.highBandRadarWavelength)
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def runFullBandInterferogram(self):
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logger.info("Generating interferogram")
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@ -295,8 +296,11 @@ def runFullBandInterferogram(self):
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os.makedirs(ifgDir)
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interferogramName = os.path.join(ifgDir , self.insar.ifgFilename)
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generateIgram(self,img1, img2, interferogramName, azLooks, rgLooks)
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info = self._insar.loadProduct(self._insar.slaveSlcCropProduct)
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radarWavelength = info.getInstrument().getRadarWavelength()
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generateIgram(self,img1, img2, interferogramName, azLooks, rgLooks,radarWavelength)
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###Compute coherence
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@ -61,9 +61,11 @@ def resampleSlc(self,masterFrame, slaveFrame, imageSlc2, radarWavelength, coregD
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if not self.doRubbersheetingRange:
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print('Rubber sheeting in range is turned off, flattening the interferogram during resampling')
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flatten = True
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print(flatten)
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else:
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print('Rubber sheeting in range is turned on, flattening the interferogram during interferogram formation')
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flatten=False
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print(flatten)
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# end of Modification
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rObj.flatten = flatten
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@ -168,6 +168,7 @@ def runRubbersheet(self):
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# filtAzOffsetFile to it.
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resampleOffset(filtAzOffsetFile, geometryAzimuthOffset, sheetOffset)
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print("I'm here")
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return None
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@ -2,6 +2,9 @@
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# Author: Heresh Fattahi
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# Copyright 2017
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#
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# Modified by V. Brancato
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# Included offset filtering with no SNR
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#
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import isce
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import isceobj
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@ -20,28 +23,36 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
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off_rg = ds.GetRasterBand(2).ReadAsArray()
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ds = None
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off_az_copy = np.copy(off_az)
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off_rg_copy = np.copy(off_rg)
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# Remove missing values from ampcor
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off_rg[np.where(off_rg < -9999)]=0
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off_az[np.where(off_az < -9999)]=0
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# Compute MAD
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off_azm = ndimage.median_filter(off_az,filterSize)
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off_rgm = ndimage.median_filter(off_rg,filterSize)
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metric_rg = np.abs(off_rgm-off_rg)
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metric_az = np.abs(off_azm-off_az)
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# Store the offsets in a complex variable
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off = off_rg + 1j*off_az
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idx = np.where((metric_rg > 3) | (metric_az > 3))
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# Mask the azimuth offsets based on the MAD
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mask = off_masking(off,filterSize,thre=3)
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xoff_masked = np.ma.array(off.real,mask=mask)
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yoff_masked = np.ma.array(off.imag,mask=mask)
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# Remove missing values in the offset map
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off_az_copy[np.where(off_az_copy<-9999)]=np.nan
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off_az_copy[idx]=np.nan
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# Delete unused variables
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mask = None
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off = None
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# Remove residual noisy spots with a median filter on the azimuth offmap
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yoff_masked.mask = yoff_masked.mask | \
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(ndimage.median_filter(xoff_masked.filled(fill_value=0),3) == 0) | \
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(ndimage.median_filter(yoff_masked.filled(fill_value=0),3) == 0)
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# Fill the offsets with smoothed values
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off_az_filled = fill_with_smoothed(off_az_copy,filterSize)
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# Fill the data by iteratively using smoothed values
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data = yoff_masked.data
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data[yoff_masked.mask]=np.nan
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# Median filter the offsets
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off_az_filled = fill_with_smoothed(data,filterSize)
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# Apply median filter to smooth the azimuth offset map
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off_az_filled = ndimage.median_filter(off_az_filled,filterSize)
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# Save the filtered offsets
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@ -63,9 +74,19 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
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img.scheme = 'BIP'
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img.renderHdr()
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return None
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return
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def off_masking(off,filterSize,thre=2):
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# Define the mask to fill the offsets
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vram = ndimage.median_filter(off.real, filterSize)
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vazm = ndimage.median_filter(off.imag, filterSize)
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mask = (np.abs(off.real-vram) > thre) | (np.abs(off.imag-vazm) > thre) | (off.imag == 0) | (off.real == 0)
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return mask
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def fill(data, invalid=None):
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"""
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Replace the value of invalid 'data' cells (indicated by 'invalid')
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@ -139,11 +160,11 @@ def fill_with_smoothed(off,filterSize):
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loop = 0
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cnt2=1
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while (loop<100):
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while (cnt2!=0 & loop<100):
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loop += 1
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idx2= np.isnan(off_2filt)
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cnt2 = np.sum(np.count_nonzero(np.isnan(off_2filt)))
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print(cnt2)
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if cnt2 != 0:
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off_filt= convolve(off_2filt,kernel,boundary='extend',nan_treatment='interpolate')
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off_2filt[idx2]=off_filt[idx2]
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@ -10,9 +10,10 @@ import isce
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import isceobj
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from osgeo import gdal
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from scipy import ndimage
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from astropy.convolution import convolve
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import numpy as np
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import os
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from astropy.convolution import convolve
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def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
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# Masking the offsets with a data-based approach
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@ -23,27 +24,36 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
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off_rg = ds.GetRasterBand(2).ReadAsArray()
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ds = None
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off_az_copy = np.copy(off_az)
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off_rg_copy = np.copy(off_rg)
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# Compute MAD
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off_azm = ndimage.median_filter(off_az,filterSize)
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off_rgm = ndimage.median_filter(off_rg,filterSize)
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metric_rg = np.abs(off_rgm-off_rg)
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metric_az = np.abs(off_azm-off_az)
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idx = np.where((metric_rg > 3) | (metric_az > 3))
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# Remove missing data in the offset map
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off_rg_copy[np.where(off_rg_copy<-9999)]=np.nan
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off_rg_copy[idx]=np.nan
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# Remove values reported as missing data (no value data from ampcor)
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off_rg[np.where(off_rg < -9999)]=0
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off_az[np.where(off_az < -9999)]=0
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# Store the offsets in a complex variable
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off = off_rg + 1j*off_az
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# Fill the offsets with smoothed values
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off_rg_filled = fill_with_smoothed(off_rg_copy,filterSize)
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# Mask the offset based on MAD
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mask = off_masking(off,filterSize,thre=3)
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# Median filter the offsets
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xoff_masked = np.ma.array(off.real,mask=mask)
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yoff_masked = np.ma.array(off.imag,mask=mask)
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# Delete not used variables
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mask = None
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off = None
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# Remove residual noisy spots with a median filter on the range offmap
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xoff_masked.mask = xoff_masked.mask | \
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(ndimage.median_filter(xoff_masked.filled(fill_value=0),3) == 0) | \
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(ndimage.median_filter(yoff_masked.filled(fill_value=0),3) == 0)
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# Fill the range offset map iteratively with smoothed values
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data = xoff_masked.data
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data[xoff_masked.mask]=np.nan
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off_rg_filled = fill_with_smoothed(data,filterSize)
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# Apply the median filter on the offset
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off_rg_filled = ndimage.median_filter(off_rg_filled,filterSize)
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# Save the filtered offsets
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@ -64,8 +74,17 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
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img.dataType = 'FLOAT'
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img.scheme = 'BIP'
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img.renderHdr()
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return
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def off_masking(off,filterSize,thre=2):
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vram = ndimage.median_filter(off.real, filterSize)
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vazm = ndimage.median_filter(off.imag, filterSize)
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mask = (np.abs(off.real-vram) > thre) | (np.abs(off.imag-vazm) > thre) | (off.imag == 0) | (off.real == 0)
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return mask
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return None
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def fill(data, invalid=None):
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"""
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@ -95,11 +114,11 @@ def fill_with_smoothed(off,filterSize):
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loop = 0
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cnt2=1
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while (loop<100):
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while (cnt2 !=0 & loop<100):
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loop += 1
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idx2= np.isnan(off_2filt)
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cnt2 = np.sum(np.count_nonzero(np.isnan(off_2filt)))
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print(cnt2)
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if cnt2 != 0:
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off_filt= convolve(off_2filt,kernel,boundary='extend',nan_treatment='interpolate')
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off_2filt[idx2]=off_filt[idx2]
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@ -255,3 +274,6 @@ def runRubbersheetRange(self):
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