JP2898321B2 - Halftone estimation method for dither image - Google Patents

Description

Detailed Description of the Invention [Table of Contents] Overview Industrial application field Conventional technology Problems to be solved by the invention Means to solve the problem Action Embodiment Effect of the invention [Overview] Pseudo halftone display Regarding the halftone estimation method of a dither image in which the original halftone image is estimated from the dither image, with the aim of reducing the estimation error by considering the correlation with the surrounding pixels, the original image dithered with the dither matrix ,
A pixel input unit that captures image data of an input pixel corresponding to the size of the dither matrix, and an average that determines an average density of a pixel of interest based on the number of black pixels included in the input pixel captured by the pixel input unit Concentration calculating means;
Estimation range determining means for determining an estimation range which is a density range of halftone data based on a threshold value corresponding to the pixel of interest in the dither matrix, the average density obtained by the average density calculation means and the pixel data of the pixel of interest, The image processing apparatus may further include a halftone estimating unit that performs halftone estimation based on pixel data corresponding to a plurality of pixels located in the vicinity of the pixel of interest and a threshold value in a dither matrix corresponding to the plurality of pixels within the estimation range determined by the determining unit. To be configured.

[Industrial applications]

The present invention relates to a dither image halftone estimating method for estimating an original halftone image from a pseudo halftone-displayed dither image.

At present, image input / output devices such as facsimile machines and scanners are increasingly targeting not only characters and line drawings but also pseudo halftone images such as dither images. By extracting information such as resolution and gradation from general binary images including these pseudo halftone images and faithfully reproducing halftone images, dither images can also be obtained by conventional multivalued image processing. For example, high-frequency emphasis, edge detection, enlargement, reduction, and the like can be easily realized.

[Conventional technology]

As a conventional halftone estimation method for a pseudo halftone image such as dither, Japanese Patent Application Laid-Open No. 62-3381, "Method of Reconstructing Gray Level Image from Dither Image" is known. . This method estimates a halftone from the number of black pixels in a dither matrix.

Another conventional example of the halftone estimation method is disclosed in
No. 61-288567, "Method of estimating halftone image of dither image", and JP-A-61-288568, "Method of estimating halftone image of binary image". According to this method, a plurality of scanning apertures are prepared, and any one of the scanning apertures is selected based on the coincidence or disagreement with the dot pattern in the scanning aperture, or any one of the scanning apertures is selected according to the arrangement of pixels in the scanning aperture. This is a method of estimating and estimating a halftone in accordance with the number of black pixels in the selected opening.

[Problems to be solved by the invention]

By the way, in the above-described method, a plurality of pixels in the dither matrix correspond to one pixel of the halftone image, and the entire image is smoothed. There was a problem of being large.

In the method of (1), the prepared dot pattern of the scanning aperture is obtained by dithering an image having a uniform density using a dither matrix. However, there is a problem that the estimation error becomes large because of the small size. In addition, the smaller the scanning aperture, the less the correlation with the surrounding pixels, so that the reliability of the obtained halftone estimation result decreases.

The present invention has been made in view of such a point, and an object of the present invention is to provide a halftone estimation method of a dither image in which an estimation error is reduced by considering a correlation with peripheral pixels. I have.

[Means for solving the problem]

FIG. 1 is a principle block diagram of a dither image halftone estimation method according to the present invention.

In the figure, a pixel input unit 111 captures pixel data of input pixels corresponding to the size of the dither matrix from an original image dither-processed by the dither matrix.

The average density calculating unit 121 obtains the average density of the pixel of interest based on the number of black pixels included in the input pixels captured by the pixel input unit 111.

The estimation range determination unit 131 determines an estimation range that is a density range of halftone data based on the threshold value corresponding to the target pixel in the dither matrix, the average density calculated by the average density calculation unit 121, and the pixel data of the target pixel. .

The halftone estimating means 141 performs the halftone based on the pixel data corresponding to a plurality of pixels located in the vicinity of the pixel of interest and the threshold value in the dither matrix corresponding to the plurality of pixels within the estimation range determined by the estimation range determining means 131. Make an estimate.

Therefore, as a whole, after determining the average density based on the pixel data corresponding to the size of the dither matrix, the halftone estimation range of the pixel of interest is determined, and further, the halftone estimation range is determined according to the state of the pixels located in the vicinity. It is configured to perform.

(Operation)

The pixel data of the input pixel corresponding to the size of the dither matrix is fetched by the pixel input unit 111, and the average density of the pixel of interest based on the number of black pixels included in these input pixels is obtained by the average density calculation unit 121. Since the dither image expresses the target pixel having a certain halftone by a plurality of pixels corresponding to the dither matrix, if the density change of the image before the dither processing is large, the intermediate pixel of the target pixel before the dither processing is displayed. The difference between the tone and the average density calculated by the average density calculation means 121, that is, the estimation error increases. The estimation range determination unit 131 calculates an average density corresponding to the target pixel, a threshold value in the corresponding dither matrix, and an estimation range that is a density range of the halftone data according to the above-described estimation error based on the pixel data of the target pixel. decide. Further, the halftone estimating means 141 calculates the intermediate value of the pixel of interest based on the state of the pixel located near the pixel of interest (the state of the pixel data and the threshold in the corresponding dither matrix) within the range of the estimated halftone. Key estimation is performed.

In the present invention, after determining the average density based on the pixel data corresponding to the size of the dither matrix, considering the estimation error by determining the estimation range that is the density range of the halftone data of the pixel of interest, Further, halftone estimation is performed in accordance with the state of the pixels located in the vicinity, thereby taking into account the correlation between neighboring pixels.

〔Example〕

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 2 shows a configuration of an embodiment to which a dither image halftone estimation method of the present invention is applied. FIG. 3 shows an outline of an operation procedure of the halftone estimation processing in the embodiment.

In FIG. 2, reference numeral 211 denotes a pixel input circuit, 221 denotes an average density calculation circuit, and 231 denotes a halftone estimation circuit.

The pixel input circuit 211 captures an image of organized dither read by a facsimile machine, a scanner, or the like (FIG. 3, step S1). For example, an input image subjected to dither processing by a 4 × 4 Bayer dither matrix shown in FIG. 4 is targeted.

In the pixel input circuit 211, 311, 313, 315, and 317 each represent a shift register. Each shift register shifts the binary data of each pixel sequentially input, and
It is output as parallel data of bits (for four pixels). Accordingly, the four shift registers 311 to 317 output binary data of 16 pixels corresponding to the above-described 4 × 4 dither matrix.

The average density calculation circuit 221 calculates the average density of 16 pixels corresponding to the dither matrix based on the 16-bit data output from the pixel input circuit 211 (FIG. 3, step
S2).

FIGS. 5A, 5B and 5C show the relationship between the input pixel group (16 pixels) and the average density calculation pixel determined by the input pixel group. As shown in the figure, the average density of one pixel is determined based on an input pixel group consisting of 16 pixels.

Actually, the average density calculation circuit 221 is stored in an average density calculation ROM.
223, the output of the pixel input circuit 211 is used as an address input, and the number of black pixels in the dither matrix is obtained at a time to obtain an average density.

The halftone estimation circuit 231 performs a first-stage process (step S3 in FIG. 3) according to the magnitude of the estimation error on the average density obtained by the average density calculation circuit 221 and a second process based on the processing result. The halftone estimation is performed by performing the step processing (FIG. 3, step S4).

Hereinafter, the first-stage process and the second-stage process will be separately described.

(I) First Step Processing FIG. 6 shows an outline of the first step. In the figure,
“D” is a halftone estimated value that is finally obtained by the halftone estimation circuit 231, “average density D _ij is an average density of a pixel of interest output from the average density calculation circuit 221, and“ threshold T _ij ”is The threshold value in the dither matrix corresponding to the pixel of _interest , the “threshold value T _kl ” is the threshold value in the dither matrix corresponding to the reference pixel, the “pixel value B _ij is the input pixel data corresponding to the pixel of interest, “Value B _kl ” indicates input pixel data corresponding to the reference pixel. “T _MAX ” indicates the maximum value of the threshold value in the dither matrix, and “T _MIN ” indicates the minimum value of the threshold value in the dither matrix.

(I-1) Case of T _ij ≦ D _ij When the threshold value T _ij of the target pixel is equal to or lower than the average density D _{ij of the target} pixel (FIG. 6A), the cases are classified as follows.
In the second stage, conditions for performing the processing are set.

When the pixel value B _ij of the pixel of _interest is “0”, the original halftone data before dithering is predicted to be at a level lower than the threshold, and the halftone estimated value D of the pixel of _{interest is} higher than the threshold T _ij . It is assumed to be small (D <T _ij ). This state is referred to as “condition 1”.

When the pixel value B _{ij of the target} pixel is “1”, the original halftone data before dithering is predicted to be at a level higher than the threshold, and the halftone estimated value D of the target pixel is equal to or larger than the threshold T _ij. (D ≧ T _ij ). This state is referred to as “condition 2”.

(I-2) Case of T _ij > D _ij When the threshold value T _ij of the target pixel is larger than the average density D _{ij of the target} pixel (FIG. 6 (b)), the cases are classified as follows, The conditions for performing the processing in stages are set.

When the pixel value B _ij of the pixel of _interest is “0”, the original halftone data before dithering is predicted to be at a level lower than the threshold, and the halftone estimated value D of the pixel of _{interest is} higher than the threshold T _ij . It is assumed to be small (D <T _ij ). This condition is called "condition 4"
And

When the pixel value B _ij of the pixel of _interest is “1”, the original halftone data before dithering is predicted to be at a level higher than the threshold, and the halftone estimated value D of the pixel of _{interest is} higher than the threshold T _ij . It is assumed to be small (D ≧ T _ij ). This state is referred to as “condition 3”.

After the conditions 1 to 4 are determined in this way, the second stage processing is performed on the nearest reference pixel group (8 pixels) surrounding the target pixel. FIG. 6C shows the positional relationship between the reference pixel group and the pixel of interest, taking the pixel value B as an example (the same applies to the threshold value T).
(B) shows the relationship between the reference pixel group and the pixel of interest.

(Ii) Second Stage Processing FIG. 7 shows the processing contents of each condition determined in the above first stage. Hereinafter, each of the conditions 1 to 4 will be described.

(Ii-1) Condition 1 First, the halftone estimation operation in the case of Condition 1 (T _ij ≦ D _ij and B _ij = 0) will be described.

First, the number of reference pixels satisfying “T _kl <T _ij and B _kl = 1” is counted, and the number is set as p.

Next, the number of reference pixels satisfying “T _kl <T _ij and B _kl = 0” is counted, and the number is set as q.

The following halftone estimation result is obtained based on the magnitude relationship between the numbers p and q.

If p ≧ q, it is determined that the halftone of the target pixel is close to the threshold _Tij , and the threshold _Tij of the target pixel is set as the halftone estimated value.

If p> q, it is determined that the halftone of the target pixel is smaller than the threshold value _Tij , and the minimum or average threshold value of the reference pixel group corresponding to the above is set as the halftone estimated value.

(Ii-2) Condition 2 Next, the halftone estimation operation in the case of Condition 2 (T _ij ≦ D _ij and B _ij = 1) will be described.

First, the number of reference pixels that satisfy “T _ij <T _kl ≦ _Dij and B _kl = 0” is counted, and the number is set as p.

Next, “T _ij <T _kl ≦ D _ij and B _kl = 1” or “T _kl > D _ij
The number of reference pixels satisfying “B _ij = 0” is counted, and the number is set as q.

Next, the number of reference pixels satisfying “T _kl > D _ij and B _kl = 1” is counted, and the number is set as r.

The following halftone estimation result is obtained based on the magnitude relationship between the numbers p, q, and r.

When the value of p is the maximum, the halftone of the pixel of interest is equal to the threshold T _ij
, And the threshold value _Tij of the pixel of _interest is set as the halftone estimated value.

If the value of q is the maximum, the halftone of the pixel of interest is the average density
It is determined that it is close to D _ij , and the average density D _ij is used as a halftone estimated value.

When the value of r is the maximum, the halftone of the pixel of interest is the average density
It is determined that the value is larger than D _ij, and the minimum value or the average value of the threshold values of the reference pixel group corresponding to the above is set as the halftone estimated value.

(Ii-3) Condition 3 Next, the halftone estimation operation in the case of Condition 3 (T _ij > D _ij and B _ij = 1) will be described.

First, the number of reference pixels satisfying “T _kl > T _ij and B _kl = 0” is counted, and the number is set as p.

Next, the number of reference pixels satisfying “T _kl > T _ij and B _kl = 1” is counted, and the number is set as q.

The following halftone estimation result is obtained based on the magnitude relationship between the numbers p and q.

If p ≧ q, it is determined that the halftone of the target pixel is close to the threshold _Tij , and the threshold _Tij of the target pixel is set as the halftone estimated value.

If p> q, it is determined that the halftone of the pixel of interest is a value larger than the threshold value _Tij , and the reference pixel group corresponding to the above is set to the maximum value or the average value of the threshold values.

(Ii-4) Condition 4 Next, the halftone estimation operation in the case of Condition 4 (T _ij > D _ij and B _ij = 0) will be described.

First, the number of reference pixels satisfying “D _ij ≦ T _kl <T _ij and B _kl = 1” is counted, and the number is set as p.

Next, “D _ij ≦ T _kl <T _ij and B _kl = 0” or “T _kl <D _ij
The number of reference pixels satisfying “B _ij = 1” is counted, and the number is set as q.

Next, the number of reference pixels satisfying “T _kl <D _ij and B _kl = 0” is counted, and the number is set as r.

The following halftone estimation result is obtained based on the magnitude relationship between the numbers p, q, and r.

When the value of p is the maximum, the halftone of the pixel of interest is equal to the threshold T _ij
, And the threshold value _Tij of the pixel of _interest is set as the halftone estimated value.

If the value of q is the maximum, the halftone of the pixel of interest is the average density
It is determined that it is close to D _ij , and the average density D _ij is used as a halftone estimated value.

When the value of r is the maximum, the halftone of the pixel of interest is the average density
It is determined that the value is smaller than D _ij, and the maximum value or the average value of the threshold values of the reference pixel group corresponding to the above is set as the halftone estimated value.

When the numbers p, q, and r under the conditions 2 and 4 are the same, the priority order is set to, for example, q, p, and r, and the average density is preferentially selected.

FIG. 8 shows a specific example of the above-described halftone estimation operation.
Now, assume that halftone estimation is performed when input pixel data corresponding to the dither matrix shown in FIG. The pixel of interest corresponds to the threshold value 6, and the reference pixel group corresponds to the eight threshold values around it.

FIG. 9B shows that the average density D _ij = 8 and the pixel value B _ij =
1 is shown. “T _ij ≦ D _ij and B _ij = 1”
Therefore, Condition 2 is satisfied. Further, in condition 2, since p = 0, q = 4, and r = 0, the value of p is the maximum, and the average density D _ij (= 8) is used as the halftone estimated value.

FIG. 3C shows an average density density D _ij = 5,
The case where the pixel value B _ij = 1 is shown. Since “T _ij > D _ij and B _ij = 1” is satisfied, the condition 3 is satisfied. Further, since p = 1 and q = 3 and p <q in condition 3, the maximum value 16 (or an average value) of the threshold value T _kl of the reference pixel corresponding to the condition 3 is set to the halftone estimated value. And

FIG. 9 shows a detailed configuration of the halftone estimation circuit 231. In the figure, reference numeral 911 denotes a threshold value generating circuit, 921 and 923 denote registers (R), 931 and 933 and 937 denote comparators, 935 and 951 denote multiplexers (MPX), and 941 denote halftone judgment circuits.

The threshold value generating circuit 911 generates each threshold value of the target pixel and the reference pixel. The register 921 stores the threshold value T _{ij of the} pixel of _interest.
The register 923 holds the maximum value or the minimum value of the threshold value _Tkl of the reference pixel under each condition shown in FIG.

Further, the comparator 931 calculates the average density D _{ij of the} pixel of _interest and the threshold T _ij ,
Compares with T _kl, comparators 933 performs the comparison with the threshold value T _kl reference pixel group with threshold T _ij of the pixel of interest. The comparator 937, in order to obtain the maximum value or the minimum value of the threshold T _kl reference pixels, it is compared with the threshold T _kl reference pixel group sequentially introduced and the contents held in the register 923.

Further, the multiplexer 935 is for selecting a desired pixel value from the pixel value B _ij and the pixel value B _kl of the reference pixel group, and the pixel values B _ij and B _kl are input from the pixel input circuit 211. The halftone judging circuit 941 outputs a control signal to the multiplexer 951 based on the outputs of the comparators 931, 933 and 937 and the multiplexer 935 in accordance with the conditions shown in FIG. The multiplexer 951 responds to the control signal to _output the average density D _ij ,
Maximum or minimum value of threshold _Tij and threshold _Tkl (average value when average value is used instead of maximum or minimum value)
, And outputs it as a halftone estimated value D.

When the threshold T _ij of the pixel of interest is output from the threshold value generating circuit 911, and compares the average density D _ij with the threshold T _ij In the comparator 931. The multiplexer 935 selects and outputs the pixel value Bij of the pixel of interest, and the halftone determination circuit 941 determines which condition shown in FIG. 7 is true based on the outputs of the comparator 931 and the multiplexer 935. Perform the first stage processing.
The threshold value _Tij of the pixel of _interest is _stored in the register 921.

When the threshold value T _{kl of the} reference pixel is sequentially output (one by one) from the threshold value generation circuit 911, the comparator 933 outputs the register 921
_Is compared with the threshold value T _ij held in the step S 1. Also,
The multiplexer 935 selects and outputs the pixel value B _kl of the corresponding reference pixel, and the halftone determination circuit 941 outputs p,
The number of q and r is counted, and a control signal created based on the magnitude relation is input to the multiplexer 951.

As described above, the pixel input circuit 211 fetches the pixel data of the number corresponding to the size of the dither matrix including the target pixel, and obtains the average density of the target pixel based on the pixel data by the average density calculation circuit 221. . Then, the halftone estimating circuit 231 performs the first-stage processing based on the magnitude relationship between the obtained average density and the corresponding threshold value in the dither matrix and whether the pixel of interest is a white pixel or a black pixel. Is limited to some extent, a final halftone estimated value is obtained based on the threshold value and the pixel value of the reference pixel group by the second stage processing.

Therefore, by obtaining the halftone estimated value based on the average density obtained from the input pixel data corresponding to the size of the dither matrix, the pixel data of the target pixel and the reference pixel, and the corresponding threshold state, the peripheral pixel , It is possible to perform halftone estimation in consideration of the correlation of

In the embodiment of the present invention, eight pixels near the pixel of interest are set as the reference pixel group. However, the range of the reference pixels can be arbitrarily selected in consideration of the size of the dither matrix. For example, when performing halftone estimation of an image dithered with an 8 × 8 dither matrix, neighboring pixels in a wider range may be used as reference pixels.

〔The invention's effect〕

As described above, according to the present invention, after calculating the average density based on the pixel data corresponding to the size of the dither matrix, the estimation range which is the density range of the halftone data of the pixel of interest is determined, By performing halftone estimation based on the state of the pixel, the estimation error can be reduced in consideration of the correlation with surrounding pixels.

[Brief description of the drawings]

FIG. 1 is a block diagram showing the principle of the method for estimating the halftone of a dither image according to the present invention. FIG. 2 is a block diagram of an embodiment to which the method for estimating the halftone of a dither image according to the present invention is applied. FIG. 4 is an explanatory view of a 4 × 4 Bayer dither matrix, FIG. 5 is an explanatory view of a correspondence relationship between an input image and an average density calculation pixel, and FIG. 6 is a first stage of one embodiment. FIG. 7 is an explanatory diagram of a second stage process of one embodiment. FIG. 8 is an explanatory diagram of a specific example of a halftone estimating operation of one embodiment. FIG. 9 is a halftone estimating circuit. FIG. In the figure, 111 is a pixel input means, 121 is an average density calculating means, 131 is an estimation range determining means, 141 is a halftone estimating means, 211 is a pixel input circuit, 221 is an average density calculating circuit, and 223 is an average density calculating ROM. 231 is a halftone estimating circuit, 311,313,315,317 are shift registers, 911 is a threshold value generating circuit, 921,923 are registers, 931,933,937 are comparators, 935,951 are multiplexers, and 941 is a halftone determining circuit.

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Claims (1)

(57) [Claims] An original image dithered by a dither matrix is included in pixel input means for inputting pixel data of an input pixel corresponding to the size of the dither matrix, and is included in the input pixel input by the pixel input means. Average density calculating means for calculating the average density of the pixel of interest based on the number of black pixels; a threshold value corresponding to the pixel of interest in the dither matrix; the average density determined by the average density calculating means; Estimation range determining means for determining an estimation range that is a density range of halftone data based on data, and pixel data corresponding to a plurality of pixels located near the pixel of interest within the estimation range determined by the estimation range determination means. And halftone estimating means for performing halftone estimation based on threshold values in the dither matrix corresponding to the plurality of pixels. A halftone estimating method for a dither image, characterized in that: