gen_psf_motion
— Generate an impulse response of a (linearly) motion blurring.
gen_psf_motion
generates an impulse response (spatial domain)
of a blurring caused by a relative motion between the object and the camera
during exposure. The generated impulse response is output into an image of
HALCON image type 'real'. PSFwidth
and PSFheight
define the width and height of the output image.
The blurring motion moves along an even. Angle
fixes its
direction by specifying the angle between the motion direction and the
x-axis (anticlockwise, measured in degrees).
To specify different velocity behaviour five PSF prototypes can be
generated. Type
switches between the following prototypes:
reverse ramp (crude model for acceleration)
reverse trapezoid (crude model for high acceleration)
square pulse (exact model for constant velocity), this is default
forward trapezoid (crude model for deceleration)
forward ramp (crude model for high deceleration)
(default value is 3.)
The blurring affects all part of the image uniformly.
Blurring
controls the extent of blurring. It specifies the
number of pixels (lying one after another) that are affetcetd by the
blurring. This number is determined by velocity of the motion and
exposure time. If Blurring
is a negative number, an adequate
blurring in reverse direction is simulated. If Angle
is a
negative number, it is interpreted clockwise. If Angle
exceeds
360 or falls below -360, it is transformed modulo(360) in an adequate number
between [0..360] resp. [-360..0].
The result image of gen_psf_motion
encloses an spatial
domain impulse response of the specified blurring. Its representation
presumes the origin in the upper left corner. This results in the
following disposition of an NxM sized image:
first rectangle (“upper left”): (image coordinates xb = 0..(N/2)-1, yb = 0..(M/2)-1)
- conforms to the fourth quadrant of the Cartesian coordinate system, encloses values of the impulse response at position x = 0..N/2 and y = 0..-M/2
second rectangle (“upper right”): (image coordinates xb = N/2..N-1, yb = 0..(M/2)-1)
- conforms to the third quadrant of the Cartesian coordinate system, encloses values of the impulse response at position x = -N/2..-1 and y = -1..-M/2
third rectangle (“lower left”): (image coordinates xb = 0..(N/2)-1, yb = M/2..M-1)
- conforms to the first quadrant of the Cartesian coordinate system, encloses values of the impulse response at position x = 1..N/2 and y = M/2..0
fourth rectangle (“lower right”): (image coordinates xb = N/2..N-1, yb = M/2..M-1)
- conforms to the second quadrant of the Cartesian coordinate system, encloses values of the impulse response at position x = -N/2..-1 and y = M/2..1
This representation conforms to that of the impulse response parameter of
the HALCON-operator wiener_filter
. So one can use
gen_psf_motion
to generate an impulse response for
Wiener filtering a motion blurred image.
Psf
(output_object) image →
object (real)
Impulse response of motion-blur.
PSFwidth
(input_control) integer →
(integer)
Width of impulse response image.
Default value: 256
Suggested values: 128, 256, 512, 1024
Typical range of values: 1
≤
PSFwidth
PSFheight
(input_control) integer →
(integer)
Height of impulse response image.
Default value: 256
Suggested values: 128, 256, 512, 1024
Typical range of values: 1
≤
PSFheight
Blurring
(input_control) real →
(real)
Degree of motion-blur.
Default value: 20.0
Suggested values: 5.0, 10.0, 20.0, 30.0, 40.0
Angle
(input_control) integer →
(integer)
Angle between direction of motion and x-axis (anticlockwise).
Default value: 0
Suggested values: 0, 45, 90, 180, 270
Type
(input_control) integer →
(integer)
PSF prototype resp. type of motion.
Default value: 3
List of values: 1, 2, 3, 4, 5
gen_psf_motion
returns 2 (H_MSG_TRUE) if all parameters are correct.
simulate_defocus
,
gen_psf_defocus
simulate_motion
,
wiener_filter
,
wiener_filter_ni
simulate_motion
,
simulate_defocus
,
gen_psf_defocus
,
wiener_filter
,
wiener_filter_ni
Anil K. Jain:Fundamentals of Digital Image Processing, Prentice-Hall
International Inc., Englewood Cliffs, New Jersey, 1989
M. Lückenhaus:“Grundlagen des Wiener-Filters und seine Anwendung
in der Bildanalyse”; Diplomarbeit;
Technische Universität München, Institut für Informatik;
Lehrstuhl Prof. Radig; 1995.
Kha-Chye Tan, Hock Lim, B. T. G. Tan:“Restoration of Real-World
Motion-Blurred Images”;S. 291-299 in: CVGIP Graphical Models and
Image Processing, Vol. 53, No. 3, May 1991
Foundation