JPS62117072A - Method for estimating dither halftone picture - Google Patents

Abstract

PURPOSE:To obtain a picture approximate to an original halftone picture by selecting the optimum scan opening for each picture element by the prescribed processing after setting plural types of scan openings together with scanning carrier out over the dither picture and counting the number of white picture elements existing within the scan opening to define this count value as the estimated halftone picture value. CONSTITUTION:The dither picture within each scan opening is compared with the binary picture obtained from a halftone picture produced based on the ratio between the white and black areas in the scan opening through a dither matrix in the scan opening for each scan opening. Thus the only scan opening is selected by the 1st selection method. While the prescribed arithmetic processing is carried out according to the white and black areas in each scan opening and the only scan opening is selected by the 2nd selection method. Thus the only scan opening is selected for each picture element of the halftone picture to be estimated by means of both the 1st and 2nd selection methods. As a result, the scale of a digital electronic circuit is reduced and at the same time the working speed of this circuit is increased.

Description

[Detailed description of the invention]

(Industrial Application Field) The present invention relates to an image processing method for dithered images. (Prior art) Output devices currently in practical use, such as display device 1
5.Many printing devices can display only two values, white and black. The 811 degree pattern method (n degree pattern method) is a method for expressing halftones in a pseudo manner using such an output device.
, dither method, etc. are known. Both the density pattern method and the dither method are types of surface gradation methods, in which the number of dots recorded within a constant area (-=7 trix) is varied. The density pattern method is a method of recording multiple dots on a portion corresponding to one pixel of a document using a threshold matrix as shown in FIG. 20 (B), and the dither method is a method shown in FIG. 20 (B). There is a method 'C' in which a portion corresponding to one pixel of a document is recorded in one dot. 3. Dithered output data is obtained as shown in the figure. This output data I4L pseudo-expresses a halftone image using white and black dots. (Problems to be Solved by the Invention) By the way, if it is possible to restore the original halftone image (corresponding to the input data in Figure 20) from such a binarized pseudo halftone image, it will be possible to In the case of an e11 degree pattern image, which is convenient because data processing can be performed and image conversion can be performed with a degree of freedom, once the pattern level arrangement is known, F52t can be immediately converted to the original halftone image. However, the resolution is low compared to the amount of information. On the other hand, a dithered image has a lower resolution in terms of distortion in the information area than a density pattern image, but it is difficult to return to the original halftone image. Therefore, it has not been possible to perform various image conversions using only dithered images.The present invention has been made in view of these points.
The purpose is to develop a device that can effectively estimate the original halftone image from a dithered image, a method for estimating halftone images from dithered images that can reduce the scale of digital electronic circuits, and that can be realized at high speed. It is about realization. (F stage for solving the problem) The present invention that solves the above-mentioned problem 4-

[Yo, di1ama1
- Set and move a multivalent scanner 1 for each pixel of the halftone image to be estimated on the dithered images created by [Scanning that satisfies the conditions] While moving the mouth in units of pixels of the dithered image ωJ, select the only scanning aperture, and create a halftone image ffl based on the ratio of the white area to the black area within the scanning aperture. In the jy method, a halftone image created based on the ratio of the white area to the black area within the scanning amount Ll is stored in the dither matrix within the scanning aperture using the dithering unit within each scanning aperture. a first selection method in which a unique scanning aperture is selected by comparing the obtained binary image for each scanning aperture;
White area and black area kL in scanning amount mouth

[The second selection method is to select the only scanning aperture by performing predetermined calculation processing (the only scanning aperture is selected for each pixel of the halftone image to be estimated using (Embodiment) Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.Here, first, as one of the systematic dither methods, an 8×8
An example will be explained in which a Bayer type matrix of 1 is used as a threshold matrix. FIG. 1 is a J-flow chart showing one embodiment of the present invention. The following will explain this flowchart 1. (1) Step (2) A plurality of types of scanning apertures are set for each pixel in a dithered image consisting of a white area and a black area. FIG. 2 is a diagram showing an example of a matrix for explaining the present invention. (A) is a 4-linal halftone image converted to digital data, (B) is an 8 x 8 pay V-shaped di 4f threshold 1 direct matrix, and (C) is a black and white 2 tin m The dithered image (binary image) of /:i ricinol image * <-r> is converted into an image (DiIJ" image @). Here, the type 1 threshold matrix is shown in Figure (B). The dither pattern is distributed to the driver 1 as shown in FIG. Sano, B is 2 lines x 4
The column size, C is 4 rows x 2 columns, D is 4 rows x 2 columns.
The scanning plane [1] has a size of 4 columns, [ has a size of 4 rows x 8 columns, F has a size of 8 rows x 4 columns, and G has a size of 8 rows x 8 columns. There is. Here, the black circles shown in each of the scanning apertures A to G are the centers of movement when moving to the dithered image in FIG. 2(c). Incidentally, while keeping J fixed, the scanning plane shown in FIG. 3 is moved on the dithered image shown in FIG. If the estimated value of the halftone image is given by the count
A1 estimated halftone images are obtained as shown in FIGS. 4(A) to 4(G). Here, (a) is based on Figure 3A, (b) is based on Figure 3B, (c) is based on Figure 3C, (2>
i, according to Figure 3, 1 [], (E), according to Figure 3
Here, we will explain how to obtain the halftone images shown in Figure 4 (1~). Now, we will explain the scanning method defined in Figure 3. As shown in Figure 5, move the surface UI G to the first l!!] position of the dithered image (the position where the center of movement is at the lower right of the 4th row, 4th column, hereinafter expressed as (4, 4)). Note that the fIF image is omitted here. In this case, it is desirable that each pixel included in the scanning plane be completely included as shown in the figure. That is, if a certain 1b It is desirable that the black value be 1-1 (:) so that it does not appear. In order to keep things confidential, the black value is shown by the r1 line. The number of white pixels in the scan amount DG is counted as 21 in the state shown in the figure. , 1) has an estimated value of 21r. Next, the scanning aperture G is moved by one pixel (in this case, 1t1), and the number of white pixels within one scanning amount G is counted as 20 as described above. Perform the same operation for accompanying. When the first row is completed, the scanning aperture G is moved by one row to the next row, and the intermediate density it constant operation is started from the lower right of the pixel whose center is (5, 4). Then, the scanning aperture is moved to the last column of the last row to obtain the halftone image estimated value, and the halftone image estimation operation is completed, and the halftone image shown in FIG. 4(g) is obtained. Next, a method for obtaining an estimated halftone image using the scanning aperture shown in FIG. 4(d) will be described. In this case, since it is necessary to align the movement center with the largest scanning aperture G, the movement start position of the scanning aperture is 4T as shown in FIG. The number of white pixels in this state is 3, and in order to match the area to G in Figure 53, it is necessary to reduce the number of white pixels in the frontage to 4 jft, so the number of self-pixels is 3X4=12. This one match,
The gain and in of the scanning aperture are said to be 4. Similarly, if we calculate the gain of each scanning scale in Fig. 3, we get
A is 4, B is 8, C is 2, [ is 2, F is 2, and G is 1. If such 8I tan is applied to the turtle by moving the scanning surface 1'' by one pixel, an estimated halftone image shown in FIG. 4(d) will be obtained. Figure 4 (a) ~. (c), <b). (f) can be considered in the same way, so the explanation will be omitted. It is also possible to relatively satisfactorily determine the Jf value of a halftone image using the method described above. , the data in FIG. 4 are diagrams showing estimated halftone images obtained in this way. Of course, in this method, the halftone image is estimated from the dithered image @((C))/)s+, which has less information than the original halftone image shown in Figure 2 (A). Therefore, as shown in FIG. 4, the image does not completely return to the orisinol halftone image. However, except where the pixel level of the original halftone image changes rapidly, a halftone image that is fairly close to the original halftone image is produced by IEI. In particular, the original intermediate Agl ii? within the scanning frontage G?
When there is no pixel level change with f<A, )11, the halftone pixel level completely matches the original halftone image value. By the way, human vision has a high tone discrimination ability in the low spatial frequency region (region where the pixel level change in the halftone image is small), but it has high tone discrimination ability in the low spatial frequency region (region where the pixel level change in the halftone image is small). It has a characteristic that it has only a low pixel level gradation discrimination ability in a large area) k'mJ. In the low spatial frequency region, a large scanning aperture is used to express high gradations, and in the high spatial frequency region, a small scanning aperture is used to achieve high resolution. By reproducing the ii image 1, it is possible to estimate the middle 11sl tone image even better than the single halftone image estimation value using the individual scans [1] shown in FIG. (2) Step ■ A 9-dither image within a specific scanning aperture and a halftone image created based on the ratio of white areas and black areas within the scanning aperture are converted into binary values obtained by the dithering 7-trix within the scanning aperture. A unique scanning aperture is selected by comparing the images in a predetermined order of scanning apertures. Next, the method of the present invention will be explained. With this method, the digital binary image is 11! Assuming that (-memories etc. are stored in the first stage)-(t), multiple types of scanning amount [-1 is set i) for the digital binary image, and the digital binary image is By performing a predetermined calculation process, one of the plurality of scanning apertures suitable for rlk is selected for each pixel, and the number of self-pixels (or the number of black pixels) within the selected scanning amount 1] is calculated. The predetermined function 1iIt81! is counted to obtain an estimated value of the halftone image. I! As such, a large aperture is selected in the low spatial frequency region (region where there are few pixel level changes in the medium 1m tone image), and a small aperture is selected in the high spatial frequency region (region where there are many pixel level changes in the halftone image). An algorithm is used. The basic idea of the invention is to choose a scan aperture that is as large as 41 degrees as long as no a degree variation within the scan aperture is observed. FIG. 7 shows the selection order of scanning apertures in the method of the invention. The scanning aperture is set to Mtp-frontage, and the process is first performed in the order of D→C-1=B→A, and the optimum scanning aperture is selected by the first method described later. If the scanning amount [1 is not selected in the first method, then the second method is used to select the optimal frontage along the route D→E−+G or D→“→G. Process (1) Here, first, D is considered as the scanning aperture. Then, selector Lj D is set at the position (5°6) in FIG. , 3), it becomes as shown in Figure 8 (A).The number of white pixels in this aperture is counted as 6.The average pixel level is 24, which is the number of white pixels multiplied by 6 and the gain of 4. Assuming that there is, each pixel is compensated by 24 as shown in (b).If the average pixel level image shown in (b) is accepted as in (c) and binarized using a threshold value matrix, it becomes as shown in (d). Here, when comparing the dithered image (A), which is the original binary image, and the re-binary image (D), they are not the same pattern. That is,
There is a mismatch. The fact that the patterns (a) and (d) are not the same pattern means that there is an original halftone image value in [d]. Therefore, in this case as well, the scanning aperture is inappropriate. Since no scanning aperture is selected in step (1) and /j, the process proceeds to step (2). if,
Here, the fact that the patterns (a) and (d) are one-way patterns means that no change in pixel level of the halftone image is detected. Therefore, the size of the scanning aperture becomes larger than D, and the process proceeds to step (2). Step <2) The scanning aperture selected in step (2) is C. Then, when the selected frontage C is superimposed on the first 11 position in FIG. 2 (c), it becomes as shown in <e). The number of self-pixels within this scanning aperture is counted as 2. Gain 8 for this self-pixel number
Assuming that the multiplied value of 16 is the average pixel level, each pixel is compensated for by 16 as shown in (v). The average pixel level image shown in (f) is taken as (g) and the threshold matrix (
When binarized with the threshold value matrix in FIG. 2 (consisting of the threshold value matrix and the second and third columns, that is, the threshold value matrix within the scanning aperture), the result is as shown in (g). Here, when comparing the original binary image D11 image (e) and the binary image (chi), they have the same pattern. That is, they match. , (E) and (H) are the same pattern, which means that there is no change in pixel level. Therefore, in this case, the scanning amount DC is appropriate. If they do not match, the process of considering the next scanning aperture B (
Proceed to 3). Step (3) In step (3), the same processing as in steps (1) and (2) is performed for the interval DB, but this processing is not necessary in this example. If they do not match, the next scanning aperture is selected, and even if they do not match, the smallest scanning aperture is selected. When the scanning aperture C is selected in this manner, the number of self-pixels within the scanning aperture C is 2 as described above. Since the gain of the scanning aperture C is 8, the image estimate value to be found is 2
It becomes X8-16. In other words, the pixel level shown in section 1) is directly used for image estimation. <3) Step (2) In step (2), check whether the scanning amount [-1 that satisfies the condition is determined or not. As explained in step (1) of step ■,
If the original binary image (a) and the re-binary image 1fi (d) match, it means that there has been no change in pixel level. Therefore, if a scan amount [1] smaller than this is selected, the size of the frontage becomes smaller and the gradation quality deteriorates, so the aperture selection process ends here. Therefore, in this case, the first method described in step (2) cannot be used, and the following second method must be used. (4) Step (2) Perform predetermined arithmetic processing on the white area and black area within the plurality of scan amounts 1) to select the only scanning aperture from Leni. First, we will use a frontage of the size D-G shown in Figure 2. Then, the number of white pixels in each interval [[ ] is calculated by d-Q. Then, we set the condition that there is no pixel change or bell change.
It is determined as follows. 12d-el≦1 (1) 12d
−r 1≦1 (2) 12e −
Li 1 ≦1 (3) 12
f −a l≦1 (4) If each of these conditions is satisfied, it is O, if not, it is X, and the width to be used according to each row r (- is determined as shown in FIG. 9). Here, the * mark in the figure indicates O or ×.For example, if formulas (1) and (2) are not satisfied, check whether formulas 3) and (4) are satisfied. The width is selected without checking if the width is satisfied, and if the formula (1) is satisfied but the formula (2) is not satisfied, the width is selected.
However, if the equation (1) is not satisfied but the equation (2) is satisfied, the aperture F is selected. If the conditions (1) to (4) are satisfied, the frontage Glfi is selected. In the above article PI, let's find the optimal width when the center position of each space between the daily frames shown in FIG. 2(c) is below the (4,4) pixel. In this case, d...3゜c =
9. Let f-8,a = 21 and r. Aki Su゛, article ('i
Let's try to find equations (1) and (2). 12d -e l-16-91-3F Equation (1) is not satisfied, and 12d-e l-16-81-2, Equation (2) is not satisfied. Therefore, the optimal frontage is found according to Figure 9, and becomes 1]. Become. , the first halftone image when D is selected as the frontage.
The value of the pixel in row 1 column 1 is estimated. Since the aperture is selected and the initial white pixel ad-3 at the time of IC is 4, the aperture gain is 4, so the halftone image shift estimated value is 3X4-12
becomes. By performing the following operations, the optimal scanning amount [=1 is set to 1 for each pixel]
Figure 10 shows the sequence of scanning 1m [1] and summarizes the explanation so far. (5) Step C: Estimating a halftone image based on the determined scanning amount. By using the first method or the second method described above, the optimum percentage of C of 14 for one pixel is determined. Then, based on the ratio of the white area to the black area within the scanning amount area, '( C6 etc. can be used to estimate a halftone image. For example, it is possible to estimate the number of white pixels within the relevant scanning amount 1 as 1 straight. Figure 11 shows t, -xiv constant intermediate Figure 4 shows the toned image.Incidentally, to explain which scanning amount [] was used for each halftone image estimation (<1.1 of the halftone estimated image), taking the case of the first row as an example, is D, (1,2
> is D, (1,3> is C, (1°4) is 8. (1,5)
is C1(1,6)/Me13, (1,7> is B, (1,8
> is C1 (1,9) is CT: Yes 4, Figure 11 (b)
4. It is a figure which shows the example of the selection frontage in L money. The estimated halftone image shown in FIG. 11(a) has a large gap in areas where there are few changes in pixel level [the halftone image is estimated using j, and a small gap in areas where there are many changes in pixel level]
The halftone image is estimated using the method, which is in line with human visual characteristics. Therefore, (1) the constant halftone image is very close to the original halftone image shown in Figure 2 (a) (Vt 1). In addition, when estimating a mid-IB1 tone image from a digital image, there are two explanations, but it is necessary to apply gradation conversion to the estimated half-tone image, apply a filter, or enlarge/reduce it. Apply the transformation, or 4 (from 2 and 1., new? k 2
Each value image can be incremented by 1. FIG. 12 is a flow 17-t showing a case where tone conversion (gradation processing m) is performed on the estimated halftone image. As shown in the figure, according to the present invention, the estimated halftone image is subjected to tone conversion, and a new binary value is generated using the C1 threshold matrix 7 for the converted halftone image. Get the image -i
As for the gradation conversion characteristic, the one shown in FIG. 13 can be considered. [l. fi is M tone conversion characteristic curve C1 horizontal axis is human power, vertical @
It has μ horns. The acceptance numbers in the figure are at the level of both prefectures. Figure 14 (A) shows the image shown in Figure 1'1 (A) in the 13th
In the figure, "I characteristic 'c' halftone image converted into gradation, (b) f in Figure 13, characteristic r tone converted halftone image, (c)
For one image shown in (a), the 8 x 8 bay A described in @
7th type Day (2 made into 2 f + I'j at Ama! Rinse)
Value image, (d) is a 2(1α double imitation) which is binarized for the image smaller than ([1).'1'' in <c) and (d)
The white pixel 90"' corresponds to the black pixel. It can be seen that the 2(1α) image differs greatly due to the difference in tone conversion characteristics. The figure shows the case where it is applied to J) 1] - d. As shown in the figure, the present invention "+it constant i"1. /'S
Filter the medium 1m tone image (= apply, filter,;
n/:: For the halftone image, a new [ILP of the binary image τ゛4] is performed using the threshold value 71-lysis. As for the filter characteristics, there is an example shown in Figure 163.
, (a) is a bypass compoly 2-shicon filter, (1
ko) 1. LIl+-passcompoly1-spider filter. The halftone image of 1t shown in Fig. 11 (a) is converted to the estimated halftone image by the characteristics shown in Fig. 16 (a) and (rl). Figure 17 (a)
, Ilf, l]), []~ba λ halftone image or lr7 L). These halftone images have λ−
1L, te, (c) (, 2nd 17' When binarized using Fiza 71 to 4), a binary image (D9'' image) as shown in 1L, 2) and (E) is obtained, respectively. is obtained.,(d),
In <E), II II II is a white pixel. "0°" corresponds to a black pixel. FIG. 18 shows a flowchart for enlarging/reducing a constant halftone image. The curve shown in the figure is estimated by the present invention. Enlarge/reduce the halftone image that has been
Using a τ threshold of 7 trix for the reduced halftone image'
C$Ji 1. ':t This is one binary image. For example, an interpolation method is used for the enlargement/reduction method L. 19(a), the 4-halftone image shown in FIG.
Halftone image enlarged 1425 times by od method
(B) is a halftone image that has been reduced by 10475 times. 9-For these halftone images, the 7゛izer 7 shown in (c)
When converted into two parts using Trix, (d) and (small) show 1, and j: Una 1? The picture detective is Vt. (d),
1t apart from (E) and 1°'' corresponds to a white pixel, and "o" corresponds to a black pixel. The dithered image is preferably a dithered image using a systematic dithering method so that one threshold value is included in each aperture with the largest area, rather than random dif or conditional dithering, and the threshold value is evenly distributed among the apertures with the smallest area. A distributed dithered image with a completely distributed threshold value is preferred, and a Bayer type dithered image with a completely distributed threshold value is particularly preferred. , J3 in the description of L, takes as an example the case where the number of white pixels in the scanning amount [C] is set to 1 in order to determine the halftone image. However, the present invention is not limited to this, and the number of black pixels may be counted. In the above description, halftones are obtained by scanning one pixel at a time, but the present invention is not limited to this, and two or more pixels or more may be scanned at a time. Furthermore, in the above description, an example is given in which there are four types of frontage for the multiple ¥1 type, but the present invention does not need to be limited to this, and any type may be used. Furthermore, the size of the scanning aperture does not need to be limited to the illustrated one, and any size can be used. (Effects of the invention) Explain in detail below! , = According to the present invention, a plurality of types of scanning apertures are set, and each image is scanned from these scanning apertures.
AffJ scans the dithered image while selecting the optimal scanning aperture through predetermined processing, counts the number of white pixels within the scanning aperture, and sets the count value as the estimated image value. An image close to a tonal image can be obtained. The estimated halftone image value obtained in this way takes human visual characteristics into consideration, so it is closer to the original halftone image. Once the halftone image is obtained, various processes such as tone conversion, enlargement/reduction, etc. can be performed.

[Brief explanation of drawings]

FIG. 1 is a diagram illustrating an embodiment of the method of the present invention.
〜, FIG. 2 is an explanatory diagram when obtaining a dithered image from an original halftone image, FIG. 3 is a diagram showing multiple types of scanning apertures,
FIG. 4 is a diagram showing an example of the estimated halftone image of each aperture obtained;
5 and 6 are explanatory diagrams of if constant for halftone images, FIG. 7 is a diagram showing the selection order of scanning amount [1], FIG. 8 is an explanatory diagram of the first method, and FIG. Fig. 10 shows the procedure for selecting a scanning aperture; Fig. 11 shows the halftone image side obtained by the present invention and an example of the selected aperture; Flowchart showing tone conversion, Figure 13 is a diagram showing tone conversion characteristics, Figure 14 shows binarization processing by tone conversion, Figure 11, Figure 15 is a flowchart for filtering, and Figure 16 shows filtering. A diagram showing the characteristics, FIG. 17 is a diagram showing binarization processing by filtering, FIG. The figure shows the conventional 2(tI
FIG. Patent Applicant: Elementary School Photography ■ Ju Co., Ltd., Representative Person
Patent Attorney 44 Shima Fuji Yogai No. 1 (A) Opening A (B) Opening B (E)
Opening E (F) Opening F4 Figure (C) Opening C (:) Opening D (G) Opening G Figure 5 Figure 6 Figure 7 Figure 9 Figure 11 (A) Figure 2 Figure 13 Figure Figure 14 '°0''゛Black painting 02
1 荊Figure 15Figure 16 Blind I7ji decoy (A) (B) (C) (D) (BO) Bypass dither acid Low pass dither both sides "1"
White Pixel Pa 1゛'' White Pixel ``o'' Black Painting ``o'' w Am Rakuten Figure 18

Claims (6)

[Claims] (1) Multiple types of scanning apertures are set and moved for each pixel of the halftone image to be estimated on the dithered image created by the dither matrix, and a predetermined condition is satisfied from among these multiple types of scanning apertures. A method of selecting a unique scanning aperture while moving the scanning aperture pixel by pixel in the dithered image, and estimating a halftone image based on the ratio of white areas to black areas within the scanning aperture. A dithered image, a halftone image created based on the ratio of the white area to the black area in the scanning aperture, and a binary image obtained by using the dither matrix in the scanning aperture are compared for each scanning aperture and uniquely obtained. A first selection method of selecting the scanning apertures of the scanning apertures and a second selection method of selecting the only scanning aperture by performing predetermined calculation processing based on the white area and black area within each scanning aperture are used together. A method for estimating a halftone image of a dithered image, characterized in that a unique scanning aperture is selected for each pixel of the halftone image to be estimated. (2) The first selection method is used mainly when selecting a small scanning aperture, and the second selection method is used mainly when selecting a large scanning aperture. Halftone image estimation method for dithered images. (3) The method for estimating a halftone image of a dithered image according to claim 1, wherein the dithered image is a systematic dithered image. (4) The method for estimating a halftone image of a dithered image according to claim 3, wherein the systematic dithered image is a dot-dispersed dithered image. (5) The method for estimating a halftone image of a dithered image according to claim 4, wherein the dot-dispersed dithered image is a Bayer dithered image. (6) The size and shape of the scanning aperture with the largest area among the plurality of types of scanning apertures are made to be equal in size and shape to the threshold matrix of the systematic dither image. A method for estimating a halftone image of a dithered image according to items 3 to 5.