JPH07220072A - Method and device for image processing - Google Patents

Abstract

PURPOSE:To improve the detecting accuracy of a dot image and to perform the optimum moire elimination by preventing unrequited smoothing processing from being performed in linear arrangement. CONSTITUTION:The detecting accuracy of the dot image can be improved by computing the spatial frequency characteristic of an input image signal by a CPU 104, and detecting the presence/absence of the dot structure of an input image and the period of dot structure from the classification and accumulation result of a document image at every spatial frequency. The optimum filters is selected from cut filters with narrow band width registered on a ROM 105 according to the calculated spatial frequency characteristic of the input image, and it is set on a filtering arithmetic part 106. The filtering arithmetic part 106 performs spatial filtering processing on the input image by a set filter.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus, for example, an image processing method and method capable of easily detecting a frequency characteristic of an input image by using one-dimensional Fourier transform and performing an appropriate spatial filtering process. The present invention relates to a device.

[0002]

2. Description of the Related Art In an image processing apparatus having an image input unit such as an image reader, a copying machine and a facsimile machine,
Generally, when the image input signal is digitized, interference fringes (moire fringes) between the periodic structure of the original image and the digital sampling pitch are generated. Therefore, in the conventional image processing apparatus, in order to reduce the moire fringes, smoothing processing for blurring the original image is performed.

[0003]

However, the moire fringes are caused by the interference between the periodic structure of the original image and the digitization as described above, and the moire fringes are those in which the original image does not have the periodic structure. -The moire fringes have different shapes depending on the frequency characteristics of the periodic structure of the original image.

For this reason, the conventional image processing apparatus is often used for halftone printing such as 65 lines / mm, 85 lines / mm, 100 lines / m.
Smoothing processing is performed so that moire fringes are reduced on average for any of the original images having a period of m, 120 lines / mm, 133 lines / mm, 175 lines / mm.
Therefore, an image having no periodic structure such as a silver halide photograph or an original image component other than the spatial frequency component of the periodic structure of the original image is excessively smoothed, which causes a drawback of degrading the sharpness of the image. It was

It is also possible to use a conventional two-dimensional Fourier transform or the like as an image processing method. That is, with the recent development of computers, it has become possible to detect the frequency characteristic of a document image by the fast Fourier transform (FFT). However, in the image reader, the copying machine, the facsimile machine, etc., the load is too large in terms of calculation time, hardware scale, etc., and it is almost impossible to adopt this.

[0006]

The present invention has been made for the purpose of solving the above-mentioned problems, and has the following structure as one means for solving the above-mentioned problems. That is, it is provided with a calculating means for calculating a spatial frequency characteristic of an input image signal and an image processing means for performing a spatial filtering process on the input image, wherein the image processing means calculates the spatial filter for carrying out the spatial filtering process. It is characterized in that it is generated by the spatial frequency characteristic of the input image calculated by the means.

[0007] For example, the arithmetic means performs a one-dimensional Fourier transform for each line on the input image, and classifies the one-dimensional Fourier transform output signal for each spatial frequency to obtain a spatial frequency in the one-dimensional direction of the input image. It is characterized in that the characteristics are calculated and detected. Alternatively, the calculation means repeats the one-dimensional Fourier transform for each line sequentially in the line vertical direction, and classifies and accumulates the Fourier transform output signals for each line for each spatial frequency to obtain 1 of the input image. It is characterized in that the spatial frequency characteristic in the dimension direction is calculated and detected. Alternatively, the arithmetic means is characterized in that the Fourier transform output signal of the input image is classified for each spatial frequency, and the presence or absence of the halftone dot structure of the input image and the period of the halftone dot structure are detected from the accumulation result.

[0008]

With the above structure, the optimum image is obtained by performing the one-dimensional Fourier transform on the input image, simply detecting the spatial frequency characteristic of the original image, and performing the spatial filtering process according to the frequency characteristic of the original document. You can get a signal.

[0009]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment according to the present invention will be described in detail below with reference to the drawings. [First Embodiment] An embodiment according to the present invention will be described below as a specific example when applied to an image reader or a reader unit of a copying apparatus.

The specific operation of this embodiment is composed of two operations: an operation of detecting the frequency characteristic of an image and an operation of performing a spatial filtering process based on the detected frequency characteristic. This 2
One operation is performed with one document image input when the device has a sufficient storage unit to store the entire original image, but in the case of a device having no storage unit such as a normal image reader. In, the document image input is performed for each of the frequency characteristic detection operation and the spatial filtering operation.

The configuration of an embodiment according to the present invention is shown in FIG. In FIG. 1, reference numeral 101 denotes an image input unit including an illumination for reading a document image, a lens, an optical component such as a CCD, and an electrical component for digitizing an image signal. An image processing unit 102 performs image processing described below on the input original image signal. The image processing unit 102 controls at least a line buffer 103 that stores an input image signal for one line, and a CP that controls the entire apparatus according to the present embodiment in accordance with a control program stored in the ROM 105 described later.
It includes a U104, a ROM 105 for storing a control program of the CPU 104 and various filters described later, a filtering calculation unit 106 for performing a predetermined filtering calculation on an input image signal, and a RAM 107 for temporarily storing the processing progress by the CPU 104 and the like.

When the image processing apparatus of this embodiment is an apparatus that is used by being connected to another image input apparatus, the image input section 101 should simply be a data receiving section from another image input apparatus. You can Also, the ROM 10
In the filter area 105a of No. 5, a plurality of cut filters having a narrow band width are registered for each frequency, and a smoothing filter for eliminating moire fringes due to halftone dot originals having various numbers of lines can be selected.

As the smoothing filter, a known filter can be used as long as it is a cut filter having a narrow band width, and it is only necessary to register a cut filter having a band width which covers the frequency region to be dealt with. For example, 65 lines / mm, 85 lines / mm, which are often used for dot printing,
It is only necessary to register a smoothing filter that reduces moire fringes on average for any original image having a period of 100 lines / mm, 120 lines / mm, 133 lines / mm, 175 lines / mm.

In any case, the input image signal (original image signal) input by the image input unit 101 is output to the image processing unit 102. The operation of this embodiment having the above configuration will be described below with reference to the flowchart of FIG. First,
The frequency characteristic detection operation of the CPU 104 will be mainly described. In step S1, the image signal input to the image processing unit 102 passes through the path A and is stored in the line buffer 103 for one line. The CPU 104 uses the one-dimensional fast Fourier transform (1) for the input image signal (one-dimensional data) stored in the line buffer 103 in step S2.
Dimension FFT). FIG. 3 shows an example of the output characteristics of the one-dimensional FFT in this embodiment when the original image is a halftone image. When the original image is a halftone dot image, the frequency characteristic is as shown in FIG.

Now, as shown in FIG. 4, when halftone dots having a pitch of 1 are read at a screen angle θ, the relative cycles seen from the x-axis direction are lcos θ and lsin θ. For example, 20
In the case of a halftone dot original having 0 line and a screen angle of 30 °, the relative number of lines on the x axis is 173 lines and 100 lines. This appears as w ₁ and w _{2 in} FIG. 3 on the frequency characteristic. CPU
104 is the one-dimensional FFT shown in FIG. 3 in step S3.
The frequency of the output characteristic (frequency characteristic) is appropriately quantized to obtain the intensity for each frequency. Then, the result obtained in the subsequent step S4 is stored in the temporary RAM 107. The above processing is performed for one line stored in the line buffer 103. Subsequently, in step S5, it is checked whether or not the processing for a predetermined amount, for example, one page has been completed. When the predetermined amount of processing has not been completed, the process returns to step S1, and when the input image for one line is stored in the line buffer 103 next, the above processing is performed for the next line.

By repeating the above for each line,
The Fourier transform output intensity is accumulated in a predetermined area of the RAM 107. FIG. 5 shows an example of the intensity of the frequency characteristic shown in FIG. 3 accumulated in the RAM 107. In this manner, the processing is sequentially advanced, and when a predetermined amount of processing is completed, the processing proceeds from step S5 to step S6, and the CPU 104 causes the peak feature of FIG.
For example, the peak position W ₁ when sliced at the threshold Th,
The number of halftone dots and the screen angle of the original image are detected by W ₂ . In a succeeding step S7, a smoothing filter for eliminating the moire fringes due to the halftone dot original having this line number is preliminarily set to R.
The smoothing filter registered in the OM 105 is selected and called. In the filter area 105a of the ROM 105, a plurality of cut filters each having a narrow bandwidth are registered for each frequency as described above, and it is possible to select an appropriate filter for the frequency characteristic of the document.

As described above, the frequency detecting operation mainly by the CPU 104 and the smoothing filter selecting process for eliminating the moire fringes due to the halftone dot document in this embodiment are completed. Next, after step S10, the smoothing process using the filter selected by the above process mainly by the filtering calculation unit 106 is executed. First, in step S10, step S7
The filter selected and read out in (1) is set in the filtering calculation unit 105 as a parameter. Then, image information to be processed is sent from the image input unit 101 line by line as described above. In this case, since the data from the image input unit 101 passes through the path B and is sent to the filtering calculation unit 106, the filtering calculation unit 106 takes in the processed image data from the image input unit 101 in the subsequent step S11. Then, in step S12, first step S
Smoothing processing is executed using the filter set in 10. Then, in step S13, it is checked whether or not a predetermined amount of processing has been completed. If the predetermined amount of processing has not been completed, the process returns to step S11, and smoothing processing is performed on the image of the next line. In this way, the processing is sequentially advanced, and when the predetermined amount of smoothing processing ends, the processing ends.

When the processing for the next original is further performed, the processing from step S1 may be performed again. By the processing described above, the Moire fringe removal with high accuracy can be performed at high speed with a simple configuration. As described above, according to the present embodiment, the one-dimensional Fourier transform is performed on the input image, the spatial frequency characteristic of the original image is easily detected, and the spatial filtering process according to the frequency characteristic of the original is performed. It is possible to remove moire optimally.

[Second Embodiment] In the first embodiment described above, the output values of the Fourier transform of one line are accumulated in the vertical direction. By taking the count, it is possible to further separate the halftone dots and the line array. The second embodiment according to the present invention, which also counts the number of peaks in the vertical direction, will be described below. Also in the second embodiment, the basic configuration is the same as that of the first embodiment shown in FIG. 1 described above.

FIG. 6 is an enlarged view when the original image is a halftone dot image, and FIG. 7 is an enlarged view when the original image is a line array image. The lines in FIGS. 6 and 7 represent lines for performing the Fourier transform in the second embodiment, and as an example, j, j +.
The 1, j + 2nd line is shown. In the case of the line j, both the halftone dot shown in FIG. 6 and the line array shown in FIG. 7 have a periodic structure with AB as the period. At this time, the Fourier transform output shows the characteristic as shown in FIG. Next, consider the case of the j + 1th line. In this case, in the case of the halftone dot shown in FIG. 6, the line exists between the lattices and the periodic structure does not exist. On the other hand, in the case of the line array shown in FIG. 7, a periodic structure having a cycle of EF = AB at the intersection EF is formed. Similarly, in the line j + 2, both have a periodic structure having a period of CD = AB.

As a method of expressing such a difference in characteristics, in the second embodiment, the one-dimensional F as shown in FIG. 3 is used.
The number of times a peak appears in the output characteristic of FT is counted. Then, for example, when the number of counts (the number of appearances of peaks) is close to the sum of j, it is determined that the document has a line array. On the other hand, when the sum of j is 1/2 or less, it is determined that the original image is a halftone dot image, so that the detection accuracy of the halftone dot image is further improved. Then, in this case, by performing the spatial filtering process according to the frequency characteristic of the document with respect to the halftone image as shown in the first embodiment described above, it is possible to optimally remove moire. Moreover, it is possible to prevent unnecessary smoothing processing in the case of line arrangement and the like.
Even in this case, it is sufficient to add a very simple configuration.

[Third Embodiment] In the second embodiment described above, the output values of the Fourier transform of one line are accumulated in the vertical direction, and the number of peaks in the vertical direction is counted. Although the example of improving the detection accuracy of the halftone dot image has been described above, the present invention is not limited to the above example, and instead of counting the number of peak appearances, the same applies by counting the intervals at which peaks appear. The effect of can be obtained. A third embodiment according to the invention will be described below in which the interval at which peaks appear is counted instead of counting the number of peak occurrences.

In the halftone dot image shown in FIG. 6, the peak appearance interval is "1" (a peak appears every line), and in the line array shown in FIG. 7, the peak appearance interval is "0" ( A peak appears in each line). Therefore, in the third embodiment, the above properties are used to define the line array image when the peak appearance interval is "0" and the other halftone dot images.

By thus adding the peak appearance interval to the halftone dot image detection element, it is possible to detect the halftone dot image with high accuracy. In this case, the original document for the halftone dot image as shown in the first embodiment described above. By performing the spatial filtering processing according to the frequency characteristic of, it is possible to optimally remove moire. Moreover, it is possible to prevent unnecessary smoothing processing in the case of line arrangement and the like.

Moreover, even in this case, it is sufficient to add a very simple structure. The present invention may be applied to a system including a plurality of devices or an apparatus including one device. Further, it goes without saying that the present invention can be applied to the case where it is achieved by supplying a program to a system or an apparatus.

[0026]

As described above, according to the present invention, the spatial frequency characteristic of the original image is easily detected by performing the one-dimensional Fourier transform on the input image, and the spatial filtering processing according to the frequency characteristic of the original is performed. By carrying out, it is possible to obtain an optimum image signal. Further, by detecting the presence or absence of the halftone dot structure of the input image and the period of the halftone dot structure from the classification result for each spatial frequency of the original image and the cumulative result, it is possible to improve the detection accuracy of the halftone dot image, In such cases, it is possible to prevent unnecessary smoothing processing and optimally remove moire.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of an embodiment according to the present invention.

FIG. 2 is a flowchart showing the operation of this embodiment.

FIG. 3 is a diagram showing an example of output characteristics of a one-dimensional FFT in this embodiment.

FIG. 4 is a diagram for explaining an example of halftone dot document reading.

FIG. 5 is a diagram showing an example of intensity when the frequency characteristics shown in FIG. 3 of the present embodiment are accumulated.

FIG. 6 is an enlarged view of a case where a document image is a halftone dot image.

FIG. 7 is an enlarged view of a case where a document image is a line array image.

[Explanation of symbols]

 101 Image Input Unit 102 Image Processing Unit 103 Line Buffer 104 CPU 105 ROM 105a Filter Area 106 Filtering Operation Unit 107 RAM

Claims (8)

[Claims] 1. A calculation means for calculating a spatial frequency characteristic of an input image signal, and an image processing means for performing spatial filtering processing on the input image, wherein the image processing means carries out the spatial filtering processing. The image processing apparatus is characterized in that: is generated by the spatial frequency characteristic of the input image calculated by the calculation means. 2. The spatial frequency in the one-dimensional direction of the input image is calculated by performing a one-dimensional Fourier transform for each line on the input image and classifying the one-dimensional Fourier transform output signal for each spatial frequency. The image processing apparatus according to claim 1, wherein the characteristic is calculated and detected. 3. The calculation means inputs the one-dimensional Fourier transform for each line by sequentially repeating the calculation in the line vertical direction and classifying and accumulating the Fourier transform output signals for each line for each spatial frequency. The image processing apparatus according to claim 2, wherein the spatial frequency characteristic of the image in the one-dimensional direction is calculated and detected. 4. The calculating means detects the presence / absence of a halftone dot structure of the input image and the period of the halftone dot structure from the classification result of the Fourier transform output signal of the input image for each spatial frequency and the cumulative result. The image processing apparatus according to claim 1. 5. A calculation step of calculating a spatial frequency characteristic of an input image signal, and an image processing step of generating a spatial filter according to the spatial frequency characteristic of the input image calculated in the calculation step and performing spatial filtering processing on the input image. An image processing method comprising: 6. The spatial frequency in the one-dimensional direction of the input image is calculated by performing a one-dimensional Fourier transform for each line on the input image and classifying the one-dimensional Fourier transform output signal for each spatial frequency. The image processing method according to claim 5, wherein the characteristic is calculated and detected. 7. The input in the calculation step, wherein the one-dimensional Fourier transform for each line is sequentially repeated in the line vertical direction and the Fourier transform output signals for each line are classified and accumulated for each spatial frequency. The image processing method according to claim 6, wherein the spatial frequency characteristic of the image in the one-dimensional direction is calculated and detected. 8. The calculation step detects the presence or absence of a halftone dot structure of the input image and the period of the halftone dot structure from the result of classification and accumulation of the Fourier transform output signals of the input image for each spatial frequency. The image processing method according to claim 5.