JPH0227284A - Laser radar image processing system - Google Patents

Abstract

PURPOSE:To effectively reduce the noise on a distance image measured by laser radar by performing speckle noise processing using reflected beam and blur noise processing using a parametric Wiener filter. CONSTITUTION:When the resolving power of laser radar is sufficiently smaller than one pixel, a point image 42 obtained by removing a speckle is used with respect to the image of the point object 41 measured by the laser radar. When the distance resolving power of the laser radar is larger than one pixel, a step object 43 is measured at first to obtain a step image 44. This image 44 is subjected to differentiation and Fourier transform while a component vertical to a stepping direction is extracted from the Fourier transform value to calculate a unidirectional component 45 of a blur function. By this method, step images in various directions are measured on an image and the directional components of respective blur functions are calculated and reconstituted to make it possible to specify a blur function 46.

Description

DETAILED DESCRIPTION OF THE INVENTION Field of Industrial Application The present invention relates to a laser radar image processing system that performs image quality improvement processing on a distance image measured by a laser radar.

Conventional technology Laser radar obtains information about the distance and brightness of the object by irradiating the object with laser light and measuring the reflected light. Distance image information can be obtained.

The principle of laser radar is to obtain distance information by irradiating an object with laser light and measuring the reflected light. Therefore, the characteristics of the irradiated light become noise on the measured image. From this point of view, the two types of noise that have a large effect due to the characteristics of laser light are blurring noise caused by the divergence angle of laser light, and noise caused by interference between laser lights because laser light is coherent. There is also speckle noise generated by

In conventional laser radar image processing systems, filters such as bypass filters and median filters are used for image noise such as speckle noise. Also, blur noise is dealt with using a Wiener filter.

Problems to be Solved by the Invention However, correction using a bypass filter or the like is merely a restoration of the image, and has not been able to fundamentally solve the problem of noise. Furthermore, application of the Wiener filter to blur noise has not yielded significant results because it is difficult to derive a blur function due to the influence of speckle noise.

The present invention solves the above-mentioned problems of the prior art, and is based on a distance image measured by a laser radar.
An object of the present invention is to provide a laser radar image processing system that can remove noise.

Means for Solving the Problems The present invention as claimed in claim 1 provides a method for detecting and processing a distance image measured by a laser radar that irradiates an object with modulated laser light and detects and processes the laser reflected light reflected from the object. Speckle noise processing that removes speckle noise using the intensity value of the reflected light obtained in synchronization with the distance information obtained from the phase difference between the reflected light and the laser irradiation light. The invention according to claim 2, characterized by the above object, is characterized in that the invention according to claim 1 is characterized in that, in the invention according to claim 1, the blurring noise on the image is reduced by using a Wiener filter to target the image subjected to the speckle noise processing. The above objective is achieved by removing.

In the above configuration, the present invention calculates speckle noise existing on a distance image measured by a laser radar and removes the noise by using information on reflected light intensity. In addition, the blur function is used to remove speckle noise from images of point objects measured by laser radar (provided that the resolution of the laser radar is sufficiently smaller than one pixel). By using the point image obtained by , blurring noise can be more effectively reduced by a parametric Wiener filter.

EXAMPLE An example of the present invention will be described below with reference to the drawings.

An outline of the present invention will be explained below. The present invention uses mitigation means described below for the above two types of noise on the distance image.

Distance information is calculated from the phase difference between the irradiated light and the reflected light, but the intensity value of the detected reflected light can vary greatly due to noise caused by laser light interference called speckle. Become.

On the other hand, in order to detect the phase difference with the phase detector currently used for boat fishing, it is necessary to raise the reflected light intensity value to a constant value, but when increasing this intensity value, there is a delay in the phase information of the signal. occurs. Due to this phase delay, speckle-dependent noise occurs on the distance image (hereinafter referred to as distance speckle noise). This distance speckle noise can be calculated from a function of reflected light intensity and noise amount (hereinafter referred to as a distance noise function) that can be determined in advance using a method described later. By using this function and the intensity value of the reflected light detected in synchronization with the distance information, the amount of distance speckle noise is calculated and corrected from the sequentially measured distance information.

・・・・・・・・・(1) F (u,su; restored image G(u,v); image containing noise H(u,su; blur function 5n(u,v); noise spectrum Density 5f (u, v
); Spectral density r of the ideal image; Processing parameters Blur noise is dealt with using a parametric Wiener filter. Since the blur function used here is determined from the measurement image processed by the distance speckle noise processing described above, it is more accurate and can enhance the effectiveness of the filter.

By using these two methods together, the above problem can be effectively solved.

FIG. 1 is a block diagram of one embodiment of the present invention. Distance image 12 simultaneously measured by laser radar 11
and the reflected light intensity image 13 are each stored in the image storage device 14.

Each of the stored images is appropriately input into the image processing device 15 and becomes a target of the speckle noise processing means 16 and the blurring noise processing means 17.

Hereinafter, speckle noise processing will be explained based on FIGS. 2 and 3. Since it is easy to apply to two-dimensional scanning, a description will be given below based on a diagram for one-dimensional scanning using a laser radar. FIG. 2 shows a method for deriving a distance noise function from the intensity of reflected light. A plane perpendicular to the optical axis of the irradiated light is measured using a laser radar. At that time, if there is no noise, the distance information should be constant and should be like the ideal signal 21 in the approximation when the scanning angle of the laser radar is sufficiently small, but in reality, the reflected light in the figure The distance signal 22 is measured with distance speckle noise included.

Similarly, the intensity information is measured as the reflected light intensity signal 23, including speckle noise.

Here, if we analyze the data of the ideal signal 21, the reflected light distance signal 22, and the reflected light intensity signal 23 so that the horizontal axis is the reflected light intensity and the vertical axis is the distance noise amount, we can obtain the distance noise function 24. You can ask for it. Next, the third method of reducing speckle noise using this distance noise function 24 will be described.
This will be explained based on the diagram.

A reflected light distance signal 32 and a reflected light intensity signal 33 are manually supplied to the speckle noise processing section 31. This reflected light intensity signal 33 is input to the aforementioned distance noise function 34,
Distance noise 35 is calculated.

The distance noise 35 is removed from the reflected light distance signal 32 to obtain a primary restored signal 36. The distance signal referred to here refers to information about each pixel on the distance image, and by performing this processing for each pixel, an image (first restored image 36) from which speckle noise has been removed from the distance image is created. You will be able to get it.

Next, blur noise processing will be explained based on FIGS. 4 and 5. FIG. 4 shows a method for deriving a blur function from a measured image. For the blur function, if the resolution of the laser radar is sufficiently small to even one pixel, speckle noise is removed using the method described earlier for the image of the point object 41 measured by the laser radar. The point image 42 obtained by this method can be used. If the distance resolution of the laser radar is greater than one pixel, first, the step object 43 is measured to obtain the step image 44. The unidirectional component 45 of the blur function can be obtained by differentiating and Fourier-transforming this step image 44 and extracting a component perpendicular to the step direction from the Fourier-transformed value. From this, the blur function 46 can be specified by measuring step images having various directions on the image, finding and reconstructing the directional components of each blur function. Next, the fifth
The blur noise processing section 51 will be explained based on the figure. The primary restored image 52 obtained by speckle noise removal is processed by a parametric Wiener filter 53 of formula (1) in a blur function processing unit 51 to reduce blur noise, and is converted into a final restored image. It becomes 54. At this time,
According to the state of the restored image 54, optimization processing of the parametric Wiener filter 53 is performed using the processing parameter ".

Effects of the Invention As described above, the present invention effectively eliminates noise on distance images measured by laser radar by performing speckle noise processing using reflected light and blurring noise processing using a parametric Wiener filter. can be reduced to

[Brief explanation of the drawing]

FIG. 1 is a block diagram of a laser radar image processing system according to an embodiment of the present invention, and FIG. 2 is a graph showing a method for deriving a distance noise function from the reflected light intensity of the system.
FIG. 3 is a block diagram of the speckle noise processing section of the system, FIG. 4 is an image diagram showing a method for deriving the blur function of the system, and FIG. 5 is a block diagram of the blur noise processing section. 23 , 32 ・Reflected light distance signal, 23 , 33...
・Reflected light intensity signal, 24, 35... distance noise function,
36, 52... Primary restored image, 53... Parametric Wiener filter.

Claims (2)

[Claims] (1) The reflected light and the laser irradiation are applied to a distance image measured by a laser radar that irradiates an object with modulated laser light and detects and processes the laser reflected light reflected from the object. Laser radar image processing characterized by comprising a speckle noise processing means for removing speckle noise by using the intensity value of the reflected light obtained in synchronization with the distance information obtained from the phase difference of light. system. (2) The laser radar image processing system according to claim 1, wherein blurring noise on the image subjected to the speckle noise processing is removed using a Wiener filter.