def sub_pixel_shift_test():
img = imread('../Images/Moon_Tile-024_043939_stacked_with_blurr_pp.tif',
IMREAD_GRAYSCALE)
show_image("Original image", img, fullscreen=True)
spx_shifty = 5.2
spx_shiftx = 3.5
img_resized, img_shifted = subpixel_shifted_frame(img, spx_shifty,
spx_shiftx)
# for i in range(10):
# show_image("Image resized", img_resized, fullscreen=True)
# show_image("Image shifted", img_shifted, fullscreen=True)
gauss_width_reference = 15
gauss_width_frame = 19
reference_frame_blurred_intermediate = GaussianBlur(
img_resized, (gauss_width_reference, gauss_width_reference),
0).astype(float32)
reference_frame_blurred = GaussianBlur(
reference_frame_blurred_intermediate,
(gauss_width_reference, gauss_width_reference), 0).astype(float32)
frame_blurred = GaussianBlur(img_shifted,
(gauss_width_frame, gauss_width_frame), 0)
y_ap = 170
x_ap = 200
half_box_width = 24
y_low = y_ap - half_box_width
y_high = y_ap + half_box_width
x_low = x_ap - half_box_width
x_high = x_ap + half_box_width
reference_box_second_phase = reference_frame_blurred[y_low:y_high,
x_low:x_high]
reference_box_first_phase = reference_box_second_phase[::2, ::2]
search_width = 10
shift_y_local_first_phase, shift_x_local_first_phase, success_first_phase, \
shift_y_local_second_phase, shift_x_local_second_phase, success_second_phase = \
Miscellaneous.multilevel_correlation(reference_box_first_phase, frame_blurred,
gauss_width_frame,
reference_box_second_phase, y_low, y_high, x_low, x_high,
search_width,
weight_matrix_first_phase=None, subpixel_solve=True)
print("Shift in y, first phase: " + str(shift_y_local_first_phase) +
", second phase: " + str(shift_y_local_second_phase) + ", total: " +
str(shift_y_local_first_phase + shift_y_local_second_phase))
print("Shift in x, first phase: " + str(shift_x_local_first_phase) +
", second phase: " + str(shift_x_local_second_phase) + ", total: " +
str(shift_x_local_first_phase + shift_x_local_second_phase))
def align_frames(self):
"""
Compute the displacement of all frames relative to the sharpest frame using the alignment
rectangle.
:return: -
"""
if self.configuration.align_frames_mode == "Surface":
# For "Surface" mode the alignment rectangle has to be selected first.
if self.x_low_opt is None:
raise WrongOrderingError(
"Method 'align_frames' is called before 'select_alignment_rect'"
)
# From the sharpest frame cut out the alignment rectangle. The shifts of all other frames
# will be computed relativ to this patch.
if self.configuration.align_frames_method == "MultiLevelCorrelation":
# MultiLevelCorrelation uses two reference windows with different resolution. Also,
# please note that the data type is float32 in this case.
reference_frame = self.frames.frames_mono_blurred(
self.frame_ranks_max_index).astype(float32)
self.reference_window = reference_frame[
self.y_low_opt:self.y_high_opt,
self.x_low_opt:self.x_high_opt]
# For the first phase a box with half the resolution is constructed.
self.reference_window_first_phase = self.reference_window[::
2, ::
2]
else:
# For all other methods, the reference window is of type int32.
reference_frame = self.frames.frames_mono_blurred(
self.frame_ranks_max_index).astype(int32)
self.reference_window = reference_frame[
self.y_low_opt:self.y_high_opt,
self.x_low_opt:self.x_high_opt]
self.reference_window_shape = self.reference_window.shape
elif self.configuration.align_frames_mode == "Planet":
# For "Planetary" mode compute the center of gravity for the reference image.
cog_reference_y, cog_reference_x = AlignFrames.center_of_gravity(
self.frames.frames_mono_blurred(self.frame_ranks_max_index))
else:
raise NotSupportedError("Frame alignment mode '" +
self.configuration.align_frames_mode +
"' not supported")
# Initialize a list which for each frame contains the shifts in y and x directions.
self.frame_shifts = [None] * self.frames.number
# Initialize a counter of processed frames for progress bar signalling. It is set to one
# because in the loop below the optimal frame is not counted.
number_processed = 1
# Loop over all frames. Begin with the sharpest (reference) frame
for idx in chain(reversed(range(self.frame_ranks_max_index + 1)),
range(self.frame_ranks_max_index,
self.frames.number)):
if idx == self.frame_ranks_max_index:
# For the sharpest frame the displacement is 0 because it is used as the reference.
self.frame_shifts[idx] = [0, 0]
# Initialize two variables which keep the shift values of the previous step as
# the starting point for the next step. This reduces the search radius if frames are
# drifting.
dy_min_cum = dx_min_cum = 0
# For all other frames: Compute the global shift, using the "blurred" monochrome image.
else:
# After every "signal_step_size"th frame, send a progress signal to the main GUI.
if self.progress_signal is not None and number_processed % self.signal_step_size == 1:
self.progress_signal.emit(
"Align all frames",
int(
round(10 * number_processed / self.frames.number) *
10))
frame = self.frames.frames_mono_blurred(idx)
# In Planetary mode the shift of the "center of gravity" of the image is computed.
# This algorithm cannot fail.
if self.configuration.align_frames_mode == "Planet":
cog_frame = AlignFrames.center_of_gravity(frame)
self.frame_shifts[idx] = [
cog_reference_y - cog_frame[0],
cog_reference_x - cog_frame[1]
]
# In Surface mode various methods can be used to measure the shift from one frame
# to the next. The method "Translation" is special: Using phase correlation it is
# the only method not based on a local search algorithm. It is treated differently
# here because it does not require a re-shifting of the alignment patch.
elif self.configuration.align_frames_method == "Translation":
# The shift is computed with cross-correlation. Cut out the alignment patch and
# compute its translation relative to the reference.
frame_window = self.frames.frames_mono_blurred(
idx)[self.y_low_opt:self.y_high_opt,
self.x_low_opt:self.x_high_opt]
self.frame_shifts[idx] = Miscellaneous.translation(
self.reference_window, frame_window,
self.reference_window_shape)
# Now treat all "Surface" mode cases using local search algorithms. In each case
# the result is the shift vector [dy_min, dx_min]. The search can fail (if within
# the search radius no optimum is found). If that happens for at least one frame,
# an exception is raised. The workflow thread then tries again using another
# alignment patch.
else:
if self.configuration.align_frames_method == "MultiLevelCorrelation":
# The shift is computed in two phases: First on a coarse pixel grid,
# and then on the original grid in a small neighborhood around the optimum
# found in the first phase.
shift_y_local_first_phase, shift_x_local_first_phase, \
success_first_phase, shift_y_local_second_phase, \
shift_x_local_second_phase, success_second_phase = \
Miscellaneous.multilevel_correlation(
self.reference_window_first_phase, frame,
self.configuration.frames_gauss_width,
self.reference_window, self.y_low_opt - dy_min_cum,
self.y_high_opt - dy_min_cum,
self.x_low_opt - dx_min_cum,
self.x_high_opt - dx_min_cum,
self.configuration.align_frames_search_width,
weight_matrix_first_phase=None)
success = success_first_phase and success_second_phase
if success:
[dy_min, dx_min] = [
shift_y_local_first_phase +
shift_y_local_second_phase,
shift_x_local_first_phase +
shift_x_local_second_phase
]
elif self.configuration.align_frames_method == "RadialSearch":
# Spiral out from the shift position of the previous frame and search for the
# local optimum.
[dy_min,
dx_min], dev_r = Miscellaneous.search_local_match(
self.reference_window,
frame,
self.y_low_opt - dy_min_cum,
self.y_high_opt - dy_min_cum,
self.x_low_opt - dx_min_cum,
self.x_high_opt - dx_min_cum,
self.configuration.align_frames_search_width,
self.configuration.align_frames_sampling_stride,
sub_pixel=False)
# The search was not successful if a zero shift was reported after more
# than two search cycles.
success = len(dev_r) <= 2 or dy_min != 0 or dx_min != 0
elif self.configuration.align_frames_method == "SteepestDescent":
# Spiral out from the shift position of the previous frame and search for the
# local optimum.
[dy_min, dx_min
], dev_r = Miscellaneous.search_local_match_gradient(
self.reference_window, frame,
self.y_low_opt - dy_min_cum,
self.y_high_opt - dy_min_cum,
self.x_low_opt - dx_min_cum,
self.x_high_opt - dx_min_cum,
self.configuration.align_frames_search_width,
self.configuration.align_frames_sampling_stride,
self.dev_table)
# The search was not successful if a zero shift was reported after more
# than two search cycles.
success = len(dev_r) <= 2 or dy_min != 0 or dx_min != 0
else:
raise NotSupportedError(
"Frame alignment method " +
configuration.align_frames_method +
" not supported")
# If the local search was unsuccessful, quit the frame loop with an error.
if not success:
raise InternalError("frame " + str(idx))
# Update the cumulative shift values to be used as starting point for the
# next frame.
dy_min_cum += dy_min
dx_min_cum += dx_min
self.frame_shifts[idx] = [dy_min_cum, dx_min_cum]
# If the alignment window gets too close to a frame edge, move it away from
# that edge by half the border width. First check if the reference window still
# fits into the shifted frame.
if self.shape[0] - abs(
dy_min_cum) - 2 * self.configuration.align_frames_search_width - \
self.configuration.align_frames_border_width < \
self.reference_window_shape[0] or self.shape[1] - abs(
dx_min_cum) - 2 * self.configuration.align_frames_search_width - \
self.configuration.align_frames_border_width < \
self.reference_window_shape[1]:
raise ArgumentError(
"Frame stabilization window does not fit into"
" intersection")
new_reference_window = False
# Start with the lower y edge.
while self.y_low_opt - dy_min_cum < \
self.configuration.align_frames_search_width + \
self.configuration.align_frames_border_width / 2:
self.y_low_opt += ceil(
self.configuration.align_frames_border_width / 2.)
self.y_high_opt += ceil(
self.configuration.align_frames_border_width / 2.)
new_reference_window = True
# Now the upper y edge.
while self.y_high_opt - dy_min_cum > self.shape[
0] - self.configuration.align_frames_search_width - \
self.configuration.align_frames_border_width / 2:
self.y_low_opt -= ceil(
self.configuration.align_frames_border_width / 2.)
self.y_high_opt -= ceil(
self.configuration.align_frames_border_width / 2.)
new_reference_window = True
# Now the lower x edge.
while self.x_low_opt - dx_min_cum < \
self.configuration.align_frames_search_width + \
self.configuration.align_frames_border_width / 2:
self.x_low_opt += ceil(
self.configuration.align_frames_border_width / 2.)
self.x_high_opt += ceil(
self.configuration.align_frames_border_width / 2.)
new_reference_window = True
# Now the upper x edge.
while self.x_high_opt - dx_min_cum > self.shape[
1] - self.configuration.align_frames_search_width - \
self.configuration.align_frames_border_width / 2:
self.x_low_opt -= ceil(
self.configuration.align_frames_border_width / 2.)
self.x_high_opt -= ceil(
self.configuration.align_frames_border_width / 2.)
new_reference_window = True
# If the window was moved, update the "reference window(s)".
if new_reference_window:
if self.configuration.align_frames_method == "MultiLevelCorrelation":
self.reference_window = reference_frame[
self.y_low_opt:self.y_high_opt,
self.x_low_opt:self.x_high_opt]
# For the first phase a box with half the resolution is constructed.
self.reference_window_first_phase = self.reference_window[::
2, ::
2]
else:
self.reference_window = reference_frame[
self.y_low_opt:self.y_high_opt,
self.x_low_opt:self.x_high_opt]
# This frame is processed, go to next one.
number_processed += 1
if self.progress_signal is not None:
self.progress_signal.emit("Align all frames", 100)
# Compute the shape of the area contained in all frames in the form [[y_low, y_high],
# [x_low, x_high]]
self.intersection_shape = [[
max(b[0] for b in self.frame_shifts),
min(b[0] for b in self.frame_shifts) + self.shape[0]
],
[
max(b[1] for b in self.frame_shifts),
min(b[1] for b in self.frame_shifts) +
self.shape[1]
]]
