JP2848566B2 - Image processing device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Application Field] The present invention inputs data of a first region of an image, performs quantization processing on the data of the first region, and quantizes data of the first region. The present invention relates to an image processing apparatus that inputs data of a second area of an image after processing is completed, and performs quantization processing on data of the second area.

2. Description of the Related Art Conventionally, an error diffusion method, an average density approximation method, and the like have been proposed as a pseudo intermediate processing method in an image processing apparatus such as a facsimile apparatus or a digital copying machine.

The former method of error diffusion is described in R.FLOYD & L.STEINBERG,
“AN ADAPTIVE ALGORITHM FOR SPATIAL GRAY SCALE”, SI
As disclosed in D75 DIGEST, PP 36 to 37, the multi-valued image data of the pixel of interest is binarized (converted to the darkest level or the shortest level), and the binarized level and the multi-level before binarization are converted. The error with the value image data is weighted by a predetermined weight and added to the pixel data near the target pixel.

In the latter method, the average density approximation method is described in Japanese Patent Application Laid-Open No. 57-104396. A weighted average value of each of the neighboring pixels in the case of binarization is obtained, and the image data of the target pixel is binarized using the average of these two averages as a threshold.

[Problems to be Solved by the Invention] Since the above-described error diffusion method is a method for correcting an error between input image data and output data, the density of an input image and an output image processing device can be stored, and the resolution can be improved. In addition, it is possible to provide an image excellent in both gradation and gradation.

However, when correcting the error between the input image data and the output image data, many two-dimensional operations have to be performed, and there is a disadvantage that the hardware configuration becomes very complicated due to the large amount of processing. Was.

On the other hand, the average density approximation method uses the binary data after binarization, so that the hardware configuration can be simplified and the processing speed can be increased due to the extremely small amount of processing. Is possible.

However, since the binarization is performed by simply approximating the pixel of interest to the average value of the area including the pixel of interest, the number of gradations is limited, and a low-frequency characteristic peculiar to an image having a gradual density change. There was a drawback when texture was generated and image quality deteriorated.

Further, as a common feature of these methods, when a document image is divided into two or more regions, data between the divided images after processing becomes discontinuous, and the image quality deteriorates.

That is, the error diffusion method has a drawback that the error for correction is not propagated in the vicinity of the binarization start point of the divided image, and the binarization is performed by a so-called constant threshold.

On the other hand, in the average density approximation method, when calculating the average density, the halftone expression is discontinuous at the joint between the divided images after the binarization processing because the binarized data is not carried over. The disadvantage was that the image quality deteriorated.

[Means for Solving the Problems] The present invention has been made in view of the above-described problems of the related art, and can significantly reduce a processing amount for quantization, obtain a good halftone image, and The data of the first area of the image is input, the data of the first area is quantized, and after the data of the first area is quantized, the data of the second area of the image is input. It is an object of the present invention to provide an image processing apparatus capable of continuing processing of a boundary portion between a first area and a second area when quantizing data of a second area.

As one means for achieving the object, for example, the following configuration is provided. That is, the data of the first area of the image is input, the data of the first area is quantized, and after the data of the first area is quantized, the data of the second area of the image is input. An image processing apparatus for performing quantization processing on second region data, comprising: input means for inputting data of a pixel of interest; quantization data storage means for storing quantized data; and said quantization data storage means. Calculating means for calculating an average value using the quantized data of a plurality of pixels which have already been subjected to quantization processing around the pixel of interest stored in, and adding an error using the average value obtained by the calculating means as a threshold value. A quantization means for quantizing the data of the target pixel, an error storage means for storing an error generated by the quantization of the data of the target pixel to newly input data, and an error storage means. New error Error adding means for adding the data to the input data, wherein the quantized data storage means quantizes the quantized data, which is a result of the quantization of the data in the first area, by quantizing the data of the pixels in the first area. A first quantized data storage unit for storing an average value used for quantization, and a quantized data which is a quantization result of the data of the first area, and a quantized data of a pixel of the second area. The second value stored to calculate the average value used for
Wherein the error storage means stores an error generated by the quantization of the data in the first area to be added to pixel data in the first area. It is characterized by comprising a storage means, and a second error storage means for storing an error generated by quantization of the data of the first area to be added to data of a pixel of the first area.

[Operation] In the above configuration, the amount of processing for quantization can be extremely reduced, a good halftone image can be obtained, and the data of the first area of the image can be input and the data of the first area can be input. After the quantization of the data in the first area is completed, the data in the second area of the image is input and the second
In the case where the data of the region is quantized, the processing at the boundary between the first region and the second region can be continued.

Hereinafter, an embodiment according to the present invention will be described in detail with reference to the drawings.

First Embodiment First, the principle of an embodiment according to the present invention will be described with reference to FIG.

FIG. 1A is a diagram showing a multi-value density for each pixel of an input image.

In FIG. 1 (A), f (i, j) indicates multi-value density data of an input image at a target pixel position to be binarized,
The normalized value is 0 to 1. Further, pixel positions above the broken line have already been binarized, and after binarization of the target pixel, binarization processing similar to f (i, j + 1), f (i, j + 2)... Is sequentially performed. .

FIG. 1B is a diagram showing binary image data.
B (i, j) is the density (“0” or “1”) of the target pixel after binarization.
). The portion surrounded by the broken line is pixel data that has already been subjected to the binarization processing at the time of processing the target pixel, and is used for the binarization processing of the target pixel.

FIG. 1C is a diagram showing a weighting mask. R
Is an example of a weighting mask for obtaining an average density, which is represented by a 3 × 3 size matrix. Here, the weight R (0,0) = R (0, −1) = 0 for the non-binarized pixel is used.

In this embodiment, the weighted average density of the binarized image in the vicinity of the pixel of interest is determined by the following equation, where m (i, j) is used.

The target pixel f (i, j) is binarized using the average density m (i, j) and the binarization correction value E (i, j) already assigned according to a series of equations shown below. .

When f (i, j) + E (i, j)> m (i, j), B (i, j) =
1 err (i, j) = f (i, j) + E (i, j) −m (i, j) When f (i, j) + E (i, j) ≦ m (i, j), B ( i, j) =
0 err (i, j) = f (i, j) + E (i, j) -m (i, j) where f (i, j) + E (i, j) = m (i, j) = 1 B (i, j) = 1 E (i, j) = E1 (i, j) + E2 (i, j) E1 (i, j + 1) = E2 (i + 1, j) = err (i, j) / 2 FIGS. 2A and 2B show a series of equations described above.

In the equation, E (i, j) is a value one pixel before the pixel of interest (i, j), that is, the multi-value density f (i, j-1) of the pixel (i, j-1) is 2
The error that occurs when binarizing to a value density B (i, j-1),
That is, the value of the difference value 1/2 between the multi-valued density f (i, j-1) and the neighborhood average density m (i, j-1) and the pixel of interest (i, j)
One line before, that is, the multi-value density f (i) of the pixel (i−1, j).
−1, j) is binarized into a binary density B.
That is, it is the sum of half the difference value between the multi-value density f (i−1, j) and the neighborhood average density m (i−1, j).

Therefore, the binarization error E (i, j) is converted to the target pixel f (i, j).
By binarizing the corrected value in addition to j), the binarized image density can be completely stored as an average density over the entire input image.

By performing the processing in consideration of such a binarization error, the halftone reproduction ability is significantly improved as compared with the above-mentioned average density approximation method.

In the equation, E1 (i, j + 1) is the pixel of interest (i, j,
j) is the error assigned to the pixel (i, j + 1) one pixel after the pixel, and E2 (i + 1, j) is the error assigned to the pixel (i + 1, j) one line after the pixel of interest (i, j). is there.

As described above, the binarization method according to the present embodiment achieves an image reproduction capability equal to or higher than that of the conventional binarization method based on the error diffusion method, although the processing amount is extremely small. Although the error is only corrected by two adjacent pixels, the error is equivalently distributed to a plurality of pixels by obtaining an average density using a plurality of data after binarization. This is because the same effect as when the correction is performed can be obtained.

FIG. 3 is a block diagram of the image processing apparatus of this embodiment.

In FIG. 3, an input sensor unit A is composed of a photoelectric conversion element such as a CCD and a driving device that scans the photoelectric conversion element. The image data is sequentially sent to the A / D converter B. The A / D converter B converts the data of each pixel into 8-bit digital data and quantizes the data into data having 256 levels of gradation. Next, in the correction circuit C, shading correction for correcting unevenness in sensitivity of the CCD sensor of the input sensor unit A and unevenness in illuminance caused by the illumination light source is performed by digital arithmetic processing.

The data after the correction processing in the correction circuit C is sent to the binarization circuit D. In the binarization circuit D, the 8-bit multi-valued image data input from the correction circuit C is quantized into 1-bit binary data by the method of the embodiment described above.

The printer E is a printer constituted by a laser beam or an ink jet system, and controls on / off of a printing dot based on binary data sent from a binarizing circuit D to reproduce a read image on a recording sheet.

Here, in the case where the input sensor unit A is configured to perform a so-called serial type scan in which the original is read in a band shape having a width of l and a length k as shown in FIG. (For example, scan (I) and scan (I
During (I)), there is a possibility that a problem of discontinuous processing may occur.

That is, the right end of the scan (I) in the j direction is indicated by f shown in FIG.
(I, j), B (j−2, i +
This is because 1) and B (j-1, i + 1) have not been binarized yet because they are data to be binarized in the next scan (II).

For this reason, in the present embodiment, the multi-value data of the two pixels to be processed in the next scan (II) is read by overlapping, and the read multi-value data is replaced as binary data and applied.

On the other hand, if the target pixel f (i, j) is located at the left end of the scan (II) in the j direction, B (j−2, i−1),
B (i−1, j−1) and B (i, j−1) located at three pixels
Although value data is necessary, the binary data is binarized in the pre-scan (I), contrary to the above.

Therefore, in this case, when the binary data corresponding to the three pixels is binarized by the pre-scan (I) by the data storage means of the present embodiment, it is stored and replaced.

Here, in FIG. 4, at the upper end in the i direction for each scan and at the left end in the j direction of scan (I), the above-described processing is required. When the data is stored as an area, the uppermost number lines are ignored.

FIG. 5 shows a detailed block configuration of the binarizing section based on the above-described algorithm in the binarizing circuit D in this embodiment.

Hereinafter, the binarization processing based on the above-described algorithm of this embodiment will be described in detail with reference to FIG.

In FIG. 5, reference numeral 1 denotes a D-type flip-flop (F / F) 12-18 and a delay unit 11 comprising a FIFO buffer for delaying the binarized data by two lines. Is an average value calculation unit that outputs the above-mentioned average density value m at the same time while maintaining the positional relationship of the seven pixels surrounded by, and is configured by a ROM that performs data conversion based on a preset weight R. You. 2 operates only at the binarization end point, and calculates the weighted average density (addition value) for two pixels based on the multi-value data calculated by the multi-value data calculation unit 10 from the ROM of the average value calculation unit 1. This is an adder that adds a part of the weighted average density m based on the binarized data output. At this time, the binary data corresponding to the output from the multi-level data calculation unit 10, that is, the outputs of the F / Fs 12 and 15, are uniquely reset to "0" by the output of a timing generation circuit (not shown).

Reference numeral 3 denotes a binarization and error calculation unit including a comparator and a subtractor. The binarization and error operation unit 3 converts multivalued data (f + E) corrected by a predetermined error described later and a binarization result of an image based on a weighted average density m. Output. Note that this binarized result output can also be output to the delay unit 11.

The error E ₂ output from the binarization and error calculator 3 (=
E ₁ ) is output to the adder 9. In the adder 9, while correcting the multi-valued data f which is more first inputted in the error E _2.
Corrected output of from the adder 9 is input to E ₂ line memory 7, where it is delayed by one line.

On the other hand, the error E ₁ output from the binarization and error calculator 3
(= E ₂ ) is also output to the adder 5. One of the adder 5 is delayed output than E ₂ line memory 7 is a correction output of from the adder 9, i.e. has corrected data only E ₂ in the i-th line of interest is inputted, the adder in vessel 5 performs the adding error E ₁ to the correction data further correction.

In this way, the output data from the adder 5 corrected by both E ₁ and E ₂ is delayed by one pixel by the D-type F / F 4 and then input to the binarization and error calculation unit 3. The operation is repeated for each pixel.

Note that the multi-value data calculation unit 10 can be composed of two D-type F / Fs and an adder. That is, the multi-value data for one pixel belonging to the next scanning area is latched and held for each line, and the internal F / F is shifted and held according to the one-line synchronization signal. Easy to implement.

Further, the binarization result output from the binarization and error calculation unit 3 is also output to the binary connection memory 19. The binary connection memory 19 stores only the binarized data of each line end portion among the binarized outputs of the binarization and error calculation unit 3 in synchronization with the one-line period signal, and delays by one scanning period. After doing
Output to the multiplexer 30. And multiplexer 30
Is input to the F / F 18 and the delay unit 11.

This process operates only at the line start end in each scan after scan (II), and the average value calculation unit 1 treats the data as binary data located T pixels before the line binarization start point.

For this reason, in the present embodiment, the average density m can be calculated and calculated as a continuous value at the joint between the scans.

As described above, according to the present embodiment, the binary data at the connection portion of each scan is stored until the next scan is executed, and the weighted average density based on the binary data is obtained by referring to the binary data at the time of the post-scan. The data does not become discontinuous at the connection between the scans, and an image having excellent gradation and resolution can be obtained.

[Second Embodiment] In the first embodiment described above, the connection between the scans is 2
The connection processing is carried out by carrying over only the value data. However, the present invention is not limited to the above example, and various modifications can be applied as appropriate.

For example, to generate a binarization circuit D upon binarizing each line end pixel of the previous scan in as shown in Figure 6 (i.e. to be corrected each line first pixel of the next scan area) error E ₁ also By performing the carry-over correction processing, binarization can be performed more accurately.

A second embodiment according to the present invention in which the binarization circuit D is configured as shown in FIG. 6 will be described in detail below.

6, the same components as those in FIG. 5 are denoted by the same reference numerals, and detailed description thereof will be omitted.

In the second embodiment shown in FIG. 6, the error E ₁ outputted from the binarization and error computing unit 3, instead of being directly input to the adder 5, the input to the adder 5 through the multiplexer 21 It is configured to be. Also, with it, the error E ₁
Is also input to the error link memory 20, and the output from the error link memory 20 is output to one input of the multiplexer 21.

The error link memory 20 binarizes the end pixel of each line in the next scan, that is, binarizes in the j direction for each line when performing the scan (I) in FIG. The E ₁ data stored in the error link memory 20 is used to store the E ₁ error to be carried over to the next scan, that is, until the scan (II) is executed.
, And is selected by the multiplexer 21 only when the first pixel is binarized and input to the adder 5,
Only the first pixel is corrected.

By controlling in this manner, the binary data at the end of each scan is stored until the next scan is executed, and the weighted average density based on the binary data is obtained by referring to the data at the time of the post-scan. Can be corrected, the data does not become discontinuous at the connection between the scans, and an image excellent in gradation and resolution can be obtained.

[Other Embodiments] The binary connection for calculating the average value m at the time of binarization of the first pixel of each line in the next scan by holding the binary data delayed for one scan as described in the first embodiment. The memory 19 and the binarization of the same pixel described in the second embodiment, particularly the same pixel should be corrected
Error connecting memory 20 for one scan between delay hold E ₁ error data, write and read at the same timing is controlled. In addition, both data are within 8 bits in total.

Therefore, all of the above components can be configured in the same chip.

Further, in the first embodiment and the second embodiment, as shown in FIG. 7 (A), a weight mask of a 3 × 3 matrix is used. It is desirable to set the weight of the pixel adjacent to the target pixel to be small.

Therefore, when the 3 × 5 matrix weight mask shown in FIG. 7B is used, R (i−1,
j) and R (i, j-1) are 5/21 = 0.24, whereas the seventh
7B is 7/48 = 0.15, and the halftone portion can be more smoothly reproduced in binary.

When a 3 × 5 matrix weight mask shown in FIG. 7C is used, R (2, −1) = 16/255 and R (2,
-2) = 8/255, R (1, -1) = 24/225, R (1, -2)
= 16/255, and the multi-valued data used for the connection processing between the scans is mainly calculated by a shift operation, which can further simplify the hardware.

Also, when the weighted mask becomes 3 × 3 or more in the present embodiment, the multi-value data calculation unit 10 increases the calculation amount,
For example, if f is an 8-bit data length, a sufficient effect can be obtained by using the upper 2 bits or 3 bits.

Furthermore, in the above description, the calculation of the average density m is simply realized by the ROM table built in the average value calculation unit 1, but this calculation can be configured using a plurality of adders. With this configuration, it is possible to further increase the processing speed. It is needless to say that the hardware scale can be significantly reduced by incorporating it inside a gate array or the like.

In the above-described first and second embodiments, the error is equally distributed over two pixels. However, the error distribution is not limited to two pixels, and the distribution ratio is not limited to even distribution. , And arbitrary pixel distribution. or,
The average value calculation mask area and its weight are not limited.

In each of the embodiments described above, the type of input data is one (1
Although the case of (color) has been described as an example, the input data of the present invention is not limited to one color, and the input data may be three colors of red (R), green (G), and blue (B). The present invention can also be applied to a color image processing device.

As described above, according to the present embodiment, even when there is no binary data to be referred to at the time of binarization of an image edge, equivalent multi-value data at the same position is used. , A weighted average density based on the binary data can be obtained, and effective binarization can be performed from the end of the image.

Also, in the case of performing serial scanning, the binary data at the end of each scan is stored until the next scan is executed, and the weighted average density based on the binary data is obtained by referring to the data during the post-scan. Data does not become discontinuous at the connection between each scan, and an image with excellent gradation and resolution can be obtained.

[Effects of the Invention] As described above, according to the present invention, the amount of processing for quantization can be extremely reduced, a good halftone image can be obtained, and data of the first region of the image can be input. Then, the data of the first area is quantized, and after the quantization processing of the data of the first area is completed, the data of the second area of the image is input and the data of the second area is quantized. If you do
Processing at the boundary between the first area and the second area can be continued.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 (A) is a diagram showing a multi-valued image for each pixel in one embodiment of the present invention, and FIG. 1 (B) is a binarization for each pixel in this embodiment. FIG. 1 (C) is a diagram showing a weighting mask for each pixel in the present embodiment, and FIGS. 2 (A) and (B) explain the principle of binarization processing in the present embodiment. FIG. 3 is a block diagram showing the configuration of the image processing apparatus according to the present embodiment, FIG. 4 is a diagram showing binary reproduction by serial scanning in the present embodiment, and FIG. FIG. 6 is a block diagram showing details of the binarization circuit, FIG. 6 is a block diagram showing details of the binarization circuit in the second embodiment according to the present invention, and FIGS. 7A to 7C are examples of weight masks. FIG. In the figure, 1... Average value calculation unit, 2, 5, 9.
Binarization and error calculator, 4,12～18 ...... flip-flop, 7 ...... E ₂ ...... line memory, 10 ...... multivalued data calculating unit, 11 ...... delay unit, 19 ...... binary tie memory, 20 …… E ₁
Error link memory, 21, 30… Multiplexer, A…
Input sensor unit, B: A / D conversion unit, C: Correction circuit, D
.., A binarization circuit, and E, a printer.

──────────────────────────────────────────────────続 き Continuation of the front page (56) References JP-A-63-209370 (JP, A) JP-A-63-102473 (JP, A) JP-A-63-155952 (JP, A) JP-A-58-1983 186265 (JP, A) JP-A-53-136424 (JP, A) JP-A-1-276969 (JP, A) (58) Fields investigated (Int. Cl. ⁶ , DB name) H04N 1 / 40-1 / 409 H04N 1/46 H04N 1/60

Claims (1)

(57) [Claims] 1. A method according to claim 1, wherein data of a first area of the image is inputted, data of the first area is quantized, and after data of the first area is quantized, data of a second area of the image is obtained. An image processing apparatus for inputting data of a pixel of interest, a quantized data storing means for storing quantized data, and Calculating means for calculating an average value using the quantized data of a plurality of pixels which have already been subjected to the quantization process around the pixel of interest stored in the data storage means; and an error obtained by using the average value obtained by the calculating means as a threshold value. Quantization means for quantizing the data of the pixel of interest to which has been added, error storage means for storing an error generated by quantization of the data of the pixel of interest to newly input data, and the error storage means Remembered in Error adding means for adding a difference to newly input data, wherein the quantized data storage means stores quantized data, which is a result of quantization of the data of the first area, in a pixel of the first area. First quantized data storage means for storing an average value used for quantizing the data of the first area, and quantized data which is a result of quantization of the data of the first area in a pixel of the second area. And a second quantized data storage means for storing an average value used for quantization of the data of the first area. The error storage means stores an error generated by the quantization of the data in the first area in the first area. A first error storage unit that stores the data to be added to the pixel data of the first area;
The error generated by the quantization of the data in the area
And a second error storage means for storing the data to be added to the pixel data in the area of (b).