Tried to stitch lots of images and have to correct some bugs of shift estimation

.gitignore

@@ -3,3 +3,4 @@ __pycache__/filesManagement.cpython-39.pyc
 __pycache__/imageTreatment.cpython-39.pyc
 __pycache__/stitching.cpython-39.pyc
 __pycache__/exceptions.cpython-39.pyc
+.DS_Store

imageTreatment.py

@@ -35,7 +35,7 @@ def apply_low_pass_filter(self, image):
 		fftimage = np.fft.fftshift(np.fft.fft2(image))
 
 		# Create low-pass filter. 
-		lowPassFilter = self.low_Pass_Filter(image=image, sigmaFilter=1)
+		lowPassFilter = self.low_Pass_Filter(image=image, sigmaFilter=10)
 
 		# Apply low-pass filters on respective cropped images. 
 		lowFFTimage = lowPassFilter * fftimage

main.py

@@ -2,7 +2,7 @@
 from imageTreatment import *
 import tifffile as tiff
 
-sourcePath = "/Users/valeriepineaunoel/Desktop/20220621-6umPolystyreneBeads-overlap10%-zoom2/LineCorrection"
+sourcePath = "/Users/valeriepineaunoel/Desktop/20220621-6umPolystyreneBeads-overlap10%-zoom2/LineCorrection/IntensityCorrection"
 tileDimensions = [6, 4]
 
 #img = ImageTreatment(sourceDir=sourcePath)
@@ -19,7 +19,7 @@
 #
 #enveloppe = img.correct_intensity_envelop()
 
-stitch = Stitching(sourceDir=sourcePath, tileD=tileDimensions, imageSize=[1024,512], isIntensityCorrection=True, isMirrored=True, isFlipped=False)
+stitch = Stitching(sourceDir=sourcePath, tileD=tileDimensions, imageSize=[1024,512], isIntensityCorrection=False, isMirrored=True, isFlipped=False)
 stitchedImage = stitch.stitching_scrapbooking_allImages()
 plt.imshow(stitchedImage)
 plt.show()

stitching.py

@@ -79,7 +79,10 @@ def calculate_shift_PCC(self, imageRef1, imageRef2) -> list:
 			npimage1 = np.asarray(imageRef1)
 			npimage2 = np.asarray(imageRef2)
 
-		reverseShift, error, disphase = phase_cross_correlation(reference_image=npimage1, moving_image=npimage2)
+		lownpImage1 = self.apply_low_pass_filter(image=npimage1)
+		lownpImage2 = self.apply_low_pass_filter(image=npimage2)
+
+		reverseShift, error, disphase = phase_cross_correlation(reference_image=lownpImage1, moving_image=lownpImage2)
 
 		# the sign of the x and/or y values of shift might need some change according to the flip or mirror state. 
 		if indexGiven:
@@ -165,8 +168,8 @@ def estimate_shift(self, index:int, stitchingSide:str) -> list:
 			movingIndex = index
 
 		elif stitchingSide == "H": 
-			referenceIndex = index
-			movingIndex = index+1
+			referenceIndex = index-1
+			movingIndex = index
 
 		else:
 			exc.define_variable(stitchingSide)
@@ -184,9 +187,9 @@ def estimate_shift(self, index:int, stitchingSide:str) -> list:
 			mbottom = 250
 
 		elif stitchingSide == "H":
-			rleft = self.imageSize[0] - 500
+			rleft = self.imageSize[0] - 900
 			rtop = 0
-			mright = 500
+			mright = 900
 			mbottom = self.imageSize[1]
 
 		else:
@@ -202,18 +205,18 @@ def estimate_shift(self, index:int, stitchingSide:str) -> list:
 		cropMoving = np.asarray(moving.crop((mleft, mtop, mright, mbottom)))
 
 		# Apply a low-pass filter on the cropped images. 
-		lowCropReference = self.apply_low_pass_filter(image=cropReference)
-		lowCropMoving = self.apply_low_pass_filter(image=cropMoving)
+		#lowCropReference = self.apply_low_pass_filter(image=cropReference)
+		#lowCropMoving = self.apply_low_pass_filter(image=cropMoving)
 
 		# Estimates shift of low-passed cropped images.
-		shift = self.calculate_shift_PCC(imageRef1=lowCropReference, imageRef2=lowCropMoving)
+		shift = self.calculate_shift_PCC(imageRef1=cropReference, imageRef2=cropMoving)
 
 		# Rescales the shift to make it correspond to the top-left coordinate (makes up for the crop).
 		if stitchingSide == "V":
 			shift[1] = shift[1] + (self.imageSize[1]-250)
 
 		if stitchingSide == "H":
-			shift[0] = shift[0] + (self.imageSize[0]-500)
+			shift[0] = shift[0] + (self.imageSize[0]-900)
 
 		return shift
 
@@ -237,29 +240,22 @@ def stitching_scrapbooking_allImages(self):
 				if x == 0:
 					if y == 0:
 						coordinates = self.calculate_coordinates_firstImage(background=tile)
-						#vCoordinates = [coordinates[0], coordinates[1]]
-						#hCoordinates = [coordinates[0], coordinates[1]]
 						vCoordinates = coordinates
 						hCoordinates = coordinates
-						print(f"COOR : {vCoordinates} and {hCoordinates}")
 					else:
 						shift = self.estimate_shift(index=i, stitchingSide="V")
 						coordinates = [vCoordinates[0] + shift[0], vCoordinates[1] + shift[1]]
-						hCoordinates = [coordinates[0], coordinates[1]]
-						vCoordinates = [coordinates[0], coordinates[1]]
+						hCoordinates = coordinates
+						vCoordinates = coordinates
 				# if not first image of the row, use the previous image to calcualte the shift
 				else:
-					shift = self.calculate_shift_PCC(imageRef1=i-1, imageRef2=i)
-					print(f"shift last : {shift}")
+					shift = self.estimate_shift(index=i, stitchingSide="H")
 					coordinates = [hCoordinates[0] + shift[0], hCoordinates[1] + shift[1]]
-					hCoordinates = [coordinates[0], coordinates[1]]
+					hCoordinates = coordinates
 
 				image = fman.read_file(filePath=self.directory + "/" + self.files[i], imageType="PIL", mirror=self.isMirrored, flip=self.isFlipped)
-				print(coordinates)
 				coords = coordinates
-				print(f"BEFORE PASTE : {coords}")
-				tile.paste(image, coordinates)
-				print(f"AFTER PASTE : {coords}")
+				tile.paste(image, (coordinates[0], coordinates[1]))
 
 				i += 1