JPH0670144A - Improved method for frequency-modulated half tone - Google Patents

Abstract

PURPOSE: To provide a method for screening continuous color tone images. CONSTITUTION: A non-processed image pixel is selected according to a random spatial filling two-dimensional curve, a regenerative value H(i,j) to be used for recording the image pixel on a recording medium 80 is determined from a color tone value P(i,j) of the non-processed image pixel, an error value E(i,j) is calculated based on the difference between the color tone value of the non- processed image pixel and the regenerative value, and the error value is added to the color tone value of the non-processed image pixel by a block 70. Next, the color tone value is replaced with the provided total value or the color tone value of each non-processed image pixel to distribute the error value is replaced with the total of the color tone value of the non-recessed image pixel and the part of error so that the error value can be distributed over more than two of the non-processed image pixels. These steps are repeatedly processed until all the image pixels are processed by a counter 8.

Description

Detailed Description of the Invention

[0001]

FIELD OF THE INVENTION This invention relates to a method of halftoning a continuous tone image. More particularly, this method relates to an improved method of frequency modulation screening.

[0002]

2. Description of the Related Art Most reproduction methods can reproduce a small number of image tones. For example, offset printing can only print with two tonal values: inked or uninked. Halftoning and screening methods are used to reproduce images with continuous tones.

The halftoning method transforms the density values into a geometric distribution of printable binary dots. The eye cannot see the individual halftone dots, only the corresponding "spatial integrated" density values.

2 used in the field of graphic arts
The main classes of species of halftoning methods have been reported.
These two methods are known as "amplitude modulation screening" and "frequency modulation screening".

According to the amplitude modulation screening method, the halftone dots, which represent a particular tone, are arranged in a fixed geometric grid. By varying the size of the halftone dots, different tones of the image can be simulated. Therefore, this method can also be called a "dot size modulation screening method".

According to the frequency modulation screening method, not the size of the halftone dots but the distance between the halftone dots is modulated. This method is well known in the field of low resolution plain paper printers, but high end printing methods such as offset printing have received little attention. Perhaps it is due to the drawbacks discussed below.

Both classes of halftoning methods are used in combination with digital film recorders. A typical digital film recorder is composed of a scanning laser beam that exposes a photosensitive material with high resolution. A "grid" that allows the laser beam to be switched on or off determines the resolution, which is usually a pitch of 1/1800 inch. The light-sensitive material may be a photographic film, from which a printing plate is later produced by photolithography. The smallest addressable unit on a recorder is often referred to as a "microdot,""recorderelement," or "rel."

Each of these two classes of halftoning methods has some variations, each of which is outlined and its advantages and disadvantages are discussed. The most important characteristics of the screening method or halftoning method for faithfully reproducing a continuous tone image are as follows. 1) Rendering properties: More specifically, not only the ability to represent the full range of tones, but also the spatial details of the original image content without introducing artifacts such as moire, textures and noise. Performance. 2) Algorithmic generated halftone dot photoengraving property: This property is used in different steps of producing a printing plate in a photoengraving process in which the halftone dots are recorded, transcribed or reproduced in a uniform manner. Decide what to do. 3) Halftone behavior on an offset printing press. 4) Speed performance achievable with this method.

The amplitude modulation screening method has the major advantages that it can be easily implemented as a high-speed algorithm for electronically screening an image, and has excellent photolithographic reproduction characteristics. However, a significant drawback of the amplitude modulation screening method is that it creates unwanted patterns in the halftoned image. Due to their cause, these patterns are called original moire, color moire and internal moire.

Original moire is due to geometrical interactions between the periodic elements in the original material and the halftone screen itself. To easily understand this problem, it is convenient to use the Fourier transform. One analysis is Jour
nal of the Optical Societ
y of America, Vol. 65, No. 6, 716-72
0, 1975 D.C. Kermisch and P.M.
G. Roetling's paper "Fourier Spe"
ctrum of Halftone Images ”
Has been done in.

Solutions for reducing the original moire include, for example, US Pat. No. 5,130,821 and European Patent No. 3693.
02 and 488324. However, these solutions do not completely solve the above problems.

Color moiré is due to interference between the halftones of different color separations of an image. To alleviate this problem, it has been proposed to use screen angles that are 60 ° shifted from each other for different color separations. Several issues have been disclosed regarding the problem of making screens at such or near angles (e.g., U.S. Pat. Nos. 4,419,690 and 4,350).
No. 996, No. 4924301 and No. 51555.
No. 99). It has also been announced to use other combinations of angle, frequency or relative phase of the halftone dot pattern for different color separations to overcome the problem of color moiré (eg US Pat. No. 44430).
60, 4,537,470, and EP 501126).

Internal moiré is a pattern due to geometric interactions with the addressable grid in which halftones are produced. Methods to reduce internal moire typically eliminate or "smear" the periodically maximizing phase error as a result of the frequency and angular relationship between the halftone screen and the addressable grid in which the moire is represented. It is based on introducing random elements. An example of such a method is described in US Pat.
No. 456924, No. 4499489, No. 4700
No. 235, No. 4918622, No. 5150428
And International Patent Application Publication No. WO090 / 04898.

Since none of the variations of the dot size modulation screening method can completely eliminate the moire problem, dot modulation screening methods have been proposed to further alleviate this problem.

Although various dot frequency modulation screening methods have been previously disclosed, they can be classified into the following subclasses. 1) A method based on thresholding between two points. 2) Diffusion of errors by scanning (and transforming) row by row, column by column. 3) Propagation of error due to Hilbert scanning (and deformation). 4) Special method.

A special method is disclosed in West German Patent No. 2931092 and also in US Pat. No. 4,485,397.

The most typical two-point thresholding method is "B
dier matrix of Bayer, B .;
E. , "An optimum method for
two level rendition of c
ongoing-tonepictures ”, P
roc. IEEE International Co
nference on Communication
s, Conference Record, 26-
11 page, 26-15 page, 1973). This Bayer dither matrix is
Having a size of a power of two, and thresholded for increasing levels of density, all halftone dots are "as far away as possible from the halftone used to represent low density levels. "There are thresholds arranged in a manner like this. There are several changes in the order of the thresholds in the dither matrix, which can be found in “Lipp
Known as "eland Kurland" dither matrix and "Jarvis" dither matrix (Stoffels, JC, Mor.
eland J. F. , “A survey of
Electronic Techniques for
Pictorial Production ”,
IEEE Transactions on Com
communications, COM-29, No. 12,
December 1981, pp. 1898-1925).

Another point-to-point thresholding method is "Blue Noise" instead of the Bayer dither matrix.
Mask ". This is US Pat. No. 5,111,310.
No. This Blue Noise Ma
sk is obtained by iterative optimization (filtering) (for the next threshold "layer") during the Fourier transform of the threshold matrix.

The halftone dot pattern produced by the Bayer dither matrix contains a strong periodic component that is visible as a "texture" and its corresponding power spectrum is clearly "pointed". This can also cause moire problems similar to dot size modulation algorithms. However, compared to the dot size modulation method, the energy of the periodic dither component "spreads" much more uniformly over different harmonics and most of the component has a relatively high frequency, so the aliasing it produces is disturbing. Much smaller.

The "Blue Noise Mask" threshold matrix distributes halftone dots and the two-dimensional power spectrum of the dots is "pointless" rather than "continuous". Therefore, this method does not suffer from the problem of periodic aliasing that occurs with the dot size modulation method or the Bayer dither matrix.

The continuous character of the power spectrum of the Blue Noise Mask method has already suggested that at least some energy is also present in the very low frequency bands of the spectrum. Low-
The presence of this energy in the visible-frequency is the reason why the tints represented in this way appear grainy. The relationship between "granularity" and the shape of the frequency spectrum is discussed in detail by Urichney Robert (Urichney Robert, "Digit").
al Halftoning ”, MIT Press
Cambridge Massachusetts,
1987, ISBN 0-262-210909-
6).

The halftones of the Bayer dither matrix do not behave very well on offset presses. The tone curve is "bumpy" and is strongly dependent on the manner in which the printer is operated, especially in the tonal range where halftone dots begin to connect. This problem is the same for dot size modulated halftones with extremely high ruling.

The "Blue Noise Mask" halftone performs much better. The range where the halftone dots connect is spread over the entire tone scale, and although the press gain is high, it is stable and easy to control. The "Blue Noise Mask" method is performed at the same time,
Seen as a method of using a continuous range of screen rulings helps to understand the above.

All point-to-point thresholding methods have a fast process of actual halftoning once the threshold matrix has been calculated, ie, as fast as the fastest form of dot size modulation method. Has the advantage of However, the two-point thresholding method has the limitation that the distribution of higher density halftone dots must be made "on top" of the distribution of lower density values. This makes it impossible to optimize the halftone dot distribution at each individual density level.

Perhaps the best known of all "dot frequency modulation" methods is the error diffusion algorithm. Images are processed row-by-row, column-by-column, and the resulting error of binarizing image data during rendering (or quantization in more general situations) is one or more errors. "Spread" to unprocessed pixels. Depending on how this error is diffused (how many pixels are weighted) it is possible to distinguish between several algorithms, usually named by the inventor. The best known is the Floyd and Steinberg algorithm (Floyd, RW and L. Steinb.
erg, “An adaptivegorith
m for spatial grayscale ”,
Proc. (SID, 17/2, 75-77)
However, in addition to that, Jarvis, Judith and Nink filters (Jarvis, JF, C.I.
N. Judice, and W.M. H. Nink
e, 1976, "Anew technique"
for displaying continuous
one pictures on bilevel
displays ”, IEEE Tran. on
Commun. , COM-24, 891-898.
Page); Stucky's filter (Stucki, P.,
1979, "MECCA, -a multiple
error collecting computer
tion algorithm for bilive
lhardcopy reproduction ”,
Research Report RZ1060, I
BM Research Laboratory, Zu
rich, Switzerland; and Stevenson, RL;
and G.D. R. Arce, 1985, "Bi
nary Display of hexagonal
ly sampled continuous ton
e images ", J. Opt. Soc. A.
m. , Vol. 2, No. 7, pp. 1009-1013).

There are many variations on the basic error diffusion algorithm described above. A simple variant consists of processing the pixels in a "zigzag" sequence. That is, the direction of error diffusion is from left to right in "even" rows and from right to left in "odd" rows (or vice versa). Urichney (Urichney Rober
t, “Digital Halftoning”,
MIT PressCambridge Massac
husetts, 1987, ISBN 0-262-
21009-6) is a method of reducing the "worm-like" texture that occurs at a lightness level of about 50%, and is a random perturbed w.
has announced the use of the error diffusion method in combination with (eight). One important variation associated with the present invention is the diffusion of errors with one randomly selected weight. In this variant, the error is distributed to exactly one unprocessed pixel, which is randomly chosen in the vicinity of the pixel to be processed.

Instead of perturbing the weights, it is also possible to perturb the threshold with which the pixel values are compared for binarization. Another method for reducing insect-like effects is US Pat.
No. 130823 and No. 5150429.

In US Pat. No. 5,130,819, the error diffused is the error averaged over a small region of already processed pixels instead of the local error in the position of only one pixel.

The error diffusion method is designed to minimize both local and global errors between the original image content and halftones, and thus is a frequency modulation method based on thresholding. When compared, it has better rendering characteristics. It is excellent in expressing details, and the particles that can be seen in light colors are small. However, in some cases, a form of "edge enhancement" is introduced, which is not always desirable.

The printing characteristics of the standard error diffusion method are less desirable. This can be explained by the relationship between the total dot perimeter vs. floyd and the integrated dot area for the Steinberg algorithm. At low densities, individual halftone dots are not connected and the dot perimeter increases in proportion to the number of dots and the integrated dot area. At a given tint, halftone dots start connecting, and the total dot perimeter grows less than the integral dot area. However, at about 50%, the algorithm produces a checkerboard-like pattern whose perimeter is very high relative to the integrated dot area. Above 50%, the same behavior repeats symmetrically. The inventors of the present invention have found that the transfer of ordered halftone dots distribution transitions from less than 50% to about 50% or more causes the press gain to be irregular, and the irregularity is greatly affected by the press setting. They found that the gradation and neutral balance became unstable. This situation is superior in that respect to the variations of the standard error diffusion algorithm, which suppresses the above tendency and produces texture at a wash level of about 50%.

The class of error diffusion methods is inherently slower than the dot size modulation and point-to-point thresholding methods based on the above methods because of the need to calculate and diffuse the error. The error diffusion method with a larger weight is slower than the error diffusion method with a smaller weight.

All of the above error diffusion algorithms have in common that the order of processing the pixels is linear, ie left to right or vice versa and top to bottom or vice versa. Witten and Neal in their literature (Witten Ian H., and R
adford M.D. Neal, "Using Pean"
o Curves for Bilevel Disp
lay of Continuous-Tone Im
ages ”, IEEE CG & A, May 1982, 4
7-52), another method is adopted. The problem of their invention was to change the order of pixel processing itself. That is, in their method, the error is always propagated in one order from the previous pixel to the next pixel, following a path known as the "Peano Curve". "Digital Halftoni
ng with Space Filling Cur
ves ”, Luiz Velho, Jonas de
Miran Gomes, ACM Compu
Other curves can also be used, such as the "Hilbert Curve" shown in FIG. 1, as suggested in ter Graphics, Vol. 25, No. 4, 1991. All these curves
It has the characteristic of being a "space-filling defined fractal curve".

The rendering properties of the Hilbert and Peano scanning method are comparable to those of the Floyd and Steinberg algorithm, but can be achieved faster than the fastest error diffusion algorithm (the error diffusion algorithm with one weight). This is because it is not necessary to store the sum of the errors propagated by the next order pixel value. Alternatively, this sum can be used immediately to determine the halftone value, after which the new error is calculated. This achievable high speed makes the error propagation algorithm very attractive for processing high resolution images.

Unfortunately, the Hilbert and Peano scanning method has the same problems as the Floyd and Steinberg algorithm in that it tends to produce strong patterns and textures for a given integrated dot area.
As shown in Figure 2, when these textures appear,
Change the outer circumference of the dot irregularly along the color scale,
Moreover, when these light colors are printed by an offset printing machine, irregularities occur in the gradation and neutral balance.

[0035]

SUMMARY OF THE INVENTION It is an object of the present invention to provide an improved method of screening continuous tone images using a frequency modulation screening method.

Other objects of the invention will be apparent from the following description.

According to the present invention there is provided a method of screening continuous tone images; selecting an unprocessed image pixel according to a randomized space-filling two-dimensional curve and then selecting that unprocessed image pixel as follows: , I.e., from the tonal value of the unprocessed image pixel, determine a playback value used to record the image pixel on a recording medium, such as photographic film or a display, and the tonal value of the unprocessed image pixel and the playback An error value is calculated based on the difference from the value, so that the unprocessed image pixel becomes a processed image pixel, the error value is added to the tonal value of the unprocessed image pixel, and then obtained Replacing the tone value with a total value, or replacing the tone value of each unprocessed image pixel to which the error value is distributed with the sum of the tone value of the unprocessed image pixel and the error portion. Thus, there is provided a method of screening a continuous tone image comprising distributing the error value over two or more unprocessed image pixels and repeating the above steps until all image pixels have been processed. It

The present invention is illustrated by way of example, but the following figures do not limit the invention.

According to the method according to the invention, the pixels of the continuous tone image are halftoned in the order described in the randomized space-filling two-dimensional curve. Pixel halftoning in this order determines the halftone value that is closest to the continuous tone pixel value, calculates the difference between the continuous tone pixel value and the halftone value, and then at least part of the error is This is accomplished by adding to one or more pixels in the following order.

Diffusing or propagating an error gives the algorithm rendering characteristics that are comparable to known error diffusion or propagation algorithms. The randomization of pixel processing paths avoids the generation of patterns and textures that degrade halftone printability. If the error is propagated only to the next pixel in the order of halftoning, performance equal to error propagation along the Peano scan can be achieved.

The term "randomized space-filling two-dimensional curve" means a two-dimensional curve connecting all image pixels, which is deterministic in principle, but the deterministic character of this curve is Subdivided by randomizing the curve at the points. A particularly advantageous randomized space-filling two-dimensional curve is the randomized space-filling deterministic fractal curve.

Randomized space-filling two-dimensional curves can be obtained in a number of ways. For example, image pixels are processed by selecting each pixel randomly, whenever a new unprocessed pixel needs to be selected.

According to another method, the image is divided into several matrices of pixels of the raw image. Each image pixel in the matrix is then processed by selecting it randomly until all are selected. When one matrix is processed, the next is processed, and so on until all matrices have been processed. The order in which the matrices are processed is again random or in a particular order, for example left to right and top to bottom.

Another variation of the above method is to recursively subdivide the image into sub-matrices until the size of the matrix matches the pixels. At each subdivision,
The order in which the matrices are processed can be randomly determined.

According to yet another method, the order of selecting pixels is described in a two-dimensional space-filling deterministic fractal curve, such as a Hilbert curve or a Peano curve, where there is no predetermined point to subdivide the deterministic structure. Be randomized.

[0046]

The present invention will be described with reference to the following embodiments with reference to the drawings, but the invention is not limited thereto.

FIG. 4 shows a circuit for implementing the new halftoning method in combination with a binary recording device. First the different building blocks of this circuit will be described, and then their operation.

Block 20 is a memory block containing the continuous tone pixel values of the image. Generally, these values are 8-bit values and are composed of N rows and M columns. Block 3
0 is a memory block having the same layout as the block 20, in which halftoned pixel values are stored. In the case of binary recorders, all halftoned pixel words have a length of 1 bit. The block 80 is a device capable of recording the information of the block 30 on the substrate. The block 70 is an arithmetic unit capable of calculating the sum of the pixel value P (i, j) and the error E at the output of the delay register 60. The conversion of continuous tone pixel values to halftoned pixel values is performed at block 40. This conversion is based on thresholding operation.
That is, if the continuous tone value at point (i, j) is less than the value of 128, the "0" value is stored in the halftone memory, otherwise the value of "1" is stored.
In block 50, an arithmetic unit capable of calculating the continuous tone value at point 42, ie the sum of the original continuous tone value and the error, and the error between the halftoned pixel values and storing it in the delay register 60. Is included. Block 8 is a counter that orders the processing of N ^* M pixels of the image. Block 10 is an LUT with N ^* M entries (one for each image pixel) and a unique combination of row and column addresses that matches one pixel position in the image. Two methods of calculating such a table will be described later. Block 5 is the clock.

The operation of this diagram will be described. With each clock pulse, the counter 8 is incremented and a new pair of coordinates (i (n), j (n)) is obtained from the block 10. These coordinates are used as an address value for the pixel memory 20, and the continuous tone pixel value P (i (n), j
(N)) is obtained. This pixel value immediately becomes the error E (i
(N-1), j (n-1)), but this pixel value has been stored in the register 60 after the first halfstone step, and the total value of both is stored in the block. Within 40, the threshold 41 is compared. As a result of performing the thresholding operation, the value H (i (n), written to the halftone pixel memory at the position (i (n), j (n)) is written.
j (n)) is determined. At the same time, the new error E (i
(N), j (n)) is P (i (n), j (n)) and H
Calculated from the difference of (i (n), j (n)) and then stored in delay register 60. The circuit sets counter 8 to 1
, Which is initialized by setting the error to 128, and the operation is stopped when the counter reaches the level of N ^* M. The halftone memory 30 is then read row by row and column by column, the contents of which are recorded by the recorder 8.
0 is recorded on the substrate.

The circuit of FIG. 4 requires a large amount of memory.
That is, sufficient memory is needed to contain the LUT with N ^* M entries containing the full continuous tone image, the full halftoned image, and the sequence of address values to control the order of pixel processing. Therefore, another method is disclosed which requires only small memory. By subdividing the image into bands that are processed and recorded one at a time, memory requirements can be reduced. FIG. 5 shows the diagram for a band with 4 lines.

The circuit of FIG. 5 is an extension of the circuit of FIG. However, the circuit of FIG.
0 and the halftone memory block 30 contain only 4 lines of image data. Therefore, LUT10 has 4
^* Contains only coordinate pairs for M data entries.
Therefore, LUT 10 contains only coordinate pairs for 4 ^* M data entries. Pixel counter 8 and LUT1
A modulo 4 ^* M arithmetic unit 9 is arranged between the addressing unit of 0 and the addressing unit of 0. The block 11 moves the image data from the mass storage device 12, for example, a hard disk to the pixel memory 20. The block 11 also comprises a detector 13 which signals when the output of the arithmetic unit 9 is equal to zero.

The operation of the circuit of FIG. 5 is as follows. When the output of the arithmetic unit 9 is zero, the block 11 stores the image data of 4 lines from the mass storage unit 12 to the pixel memory 2
Move to 0. These 4 ^* M pixels are then halftoned according to the method of the present invention. After 4 ^* M clock pulses, the new set of 4 line image pixels is moved from the mass storage device 12 to the pixel memory 30. The 4 ^* M halftoned pixels contained in the memory 30 are also recorded on the substrate by the recording device (80).

Two methods are provided to obtain the contents of block 10 of FIG.

The first method is based on the randomization of the Hilbert path. The Hilbert path is a two-dimensional "fractal" curve that can be obtained by a recursive program. FIG. 1 shows some recursion of the process of generating a 32 × 32 point Hilbert path. Table 1 at the end shows some of the C programs that can be used to obtain such a route. The randomization of this path is linear. That is, this path goes from point to point,
At every point in the path, it is randomly determined whether to switch currents to the next point. This randomization process can be performed one or more times. FIG. 6 shows the Hilbert curve after randomization. FIG. 7 shows a graph of total perimeter vs. integral dot area obtained from a Hilbert scan with two randomizations. Compared to FIG. 2, the graph of FIG. 7 is very smooth and has no peaks at about 50% light level. FIG. 8 shows that no texture or patterning occurs along the tonal scale.

In the second method, the rectangular matrix is recursively subdivided into smaller sub-matrices. In every subdivision, a random permutation order number is assigned to every submatrix. This process is stopped when the subdivision reaches the level of individual matrix elements. An example is shown in FIG. In FIG. 9, 3
2x32 matrix is 2x with 16x16 elements
It is recursively subdivided into two matrices, after which all submatrices are again subdivided into 8x8 element 2x2 submatrices. Then all of these matrices are again subdivided into 2x2 individual matrix elements. Table 2 at the end shows the C program that implements this process, while FIG. 9 shows the routes obtained with that program. The total dot perimeter vs. dot area graph from this method, shown in FIG. 10, is very smooth with no apparent texture. Tests confirmed that the halftone exhibited the above attributes and that the print was very stable within a wide range of press parameters. The printer reported that the neutral balance and gradation were stable, and the gradation became significantly smoother.
There were no tonal jumps at a particular tonal level and good shadow detail was easily achieved. There was no moire, and the details were far superior to the dot size modulation method.

The above method of obtaining paths is absolutely arranged to produce a square image or matrix of parts of an image. The actual state is hardly such a state. Three solutions are available to control this problem: In the first solution, the original continuous tone image is
It is "padded" along its longest edge with a zero value until it is square. In the second method, the path is calculated by the size of the longest side of the rectangular image. Points on the path that do not match the image pixel location simply jump over as they pass through that path. In the third solution, the image is, for example, 16 × 1.
It is divided into square parts such as 6 elements. Randomized paths are obtained for one of these square sections using one of the methods described above. After that, the route is connected. This method still requires that the dimensions of the image be a multiple of the dimensions of the square portion, but these squares are relatively small (16 × 16 in our example).
So the above does not really pose a limitation.

Obviously, there are many variations on the embodiments provided herein. In one variation, a device that records multiple levels rather than two can be used (eg, a device such as a thermal sublimation printer, slide recorder, electrophotographic printer, etc.). The thresholding operation shown in FIG. 4 is then replaced by thresholding with multiple thresholds. The halftone value depends on between which two thresholds the continuous tone pixel value lies. For performance and adaptability, the address value matches the sum of error and pixel value,
On the other hand, an LU whose content contains the corresponding halftone value
It is best to perform the thresholding operation in block 40 by T.

In another variation, the error resulting from the difference between the continuous tone pixel and the halftoned pixel value is diffused to one or more unprocessed pixels instead of being propagated only to the next pixel in the processing order. To be done.

As a further modification, the error E in FIG. 4 is obtained by comparing the current pixel P (i (n), j (n)) with the halftone value H (i (n), j of the current pixel. Not obtained from the difference with (n)), but when obtained as a weighted average value from the error of one or more processed pixels. A circuit for doing this is disclosed in FIG.

FIG. 11 shows a more sophisticated version of the circuit of FIG. The differences are the first set of k shift registers 43 in which the unprocessed pixels are delayed k times, the second set of 1 shift registers 63 in which the difference between the continuous tone value and the halftoned value is delayed once, and the half The addition of a third set of K shift registers 33 in which the coordinate values addressing the tone memory 30 are delayed k times. Furthermore, E (i) of the weighted average value derived from the output of the shift register 63
(N−k), j (n−k)) is obtained, and this average value is k
An arithmetic unit 65 that distributes to the output of the shift register 43 is provided.

Each cycle of clock 5, the data in shift registers 33, 43 and 63 is shifted by one position and counter 8 is incremented by one. This is done in three general operations, which the inventors of the present invention call "halftoning", "error combining" and "error distribution".

First, halftoning will be described. The new value of the counter 8 is the coordinate pair i (n) of the memory block 10,
address j (n), then pixel P of pixel memory 20
Address (i (n), j (n)). The latter value is
It is used as an input to the shift register 33. The output of the same shift register 33 then has a value Q (i) based on (but not necessarily equal to) this pixel value P (i (n-k), j (n-k)) which has been delayed k times. (N-
k), j (n−k)). This value Q (i (n-
k), j (n−k)) is compared with the threshold value 41, and based on this comparison, the halftone value H (i (n−k), j).
(N−k)) is determined and written in the cell 31 at the address (i (n−k), j (n−k)) of the halftone memory 30. The latter address is obtained by delaying the address value coming from the memory block 10 by the shift register 33 k times.

Next, the "error synthesis" part will be described. Value Q
(I (n−k), j (n−k)) and H (i (n−k),
j (n−k)) difference d (i (n−k), j (n−k))
Is calculated by the arithmetic unit 50, and the shift register 6
3 inputs are added. The difference value d (i (n−k−1),
j (n−k−1)), d (i (n−k−2), j (n−)
k-2)). ． ． d (i (n−k−1), j (n−k−)
1) is given. From these 1 values, the multiplier w
(1), w (2). ． ． The error value E (i (n−k), j (n−k)) is combined by w (1) and the arithmetic unit 65. This error value E (i (n−k), j (n−k))
Denotes the weighted average value of the error introduced as a result of the previous quantization over a region of one half-toned pixel.

The last step is the error E (i (n-
k), j (n−k)) are distributed to the unprocessed pixel values. First, the error E (i (n-
k), j (n−k)) with weights v (1), v (2). ． ．
This is done by multiplying v (k) and then adding the resulting values to the respective outputs of k of the cells of the shift register 43. Thus, the error E (i (n-
k), j (n−k)) are spread over the range of k values in the shift register 43.

The circuit of FIG. 11 can be modified to process an image of a band in a manner similar to that described in FIG.

It will be apparent to those skilled in the art that the above halftoning method can be implemented in hardware or software.

[0067]

[Table 1]

[Table 2]

[Table 3]

[Table 4]

[Table 5]

[Table 6]

[Table 7]

[Brief description of drawings]

FIG. 1 shows a Hilbert curve.

FIG. 2 shows dot perimeter vs. tone value (0 = minimum density, 256 = maximum density) for halftoning, where the pixels have been processed in Hilbert curve order.

FIG. 3 shows a halftoned tone scale obtained by processing image pixels in the order in which the Hilbert curve is drawn.

FIG. 4 is a schematic explanatory diagram of a circuit for implementing the halftoning method of the present invention.

FIG. 5 is a schematic explanatory diagram of a circuit that processes a band image.

FIG. 6 shows a randomized Hilbert curve.

FIG. 7 shows dot perimeter vs. tone value (0 = minimum density, 256 = maximum density) for halftoning, with pixels processed in the order of a randomized Hilbert curve.

FIG. 8 shows a halftoned tone scale obtained by processing image pixels in the order that the randomized Hilbert curve draws.

FIG. 9 shows the order in which image pixels are processed when the image is recursively subdivided into a matrix.

FIG. 10 shows dot perimeter vs. tone value (0 = minimum density, 256 = maximum density) for halftoning, where the pixels are in the order obtained by recursively subdividing the image into a matrix. Is being processed by.

FIG. 11 is a schematic explanatory diagram of a circuit that implements the halftoning method of the present invention, in which the weighted average of the differences between the tone values of at least two image pixels and their corresponding replay values is It is diffused in many pixels.

[Explanation of symbols]

5 clock 8 pixel counter 9 modulo 4 ^* M arithmetic unit 10 LUT 12 mass storage device 13 detector 20 pixel value memory 30 halftone pixel value memory 31 cell 40 halftone device 41 threshold 33, 43 k shift register 63 1 shift register 60 delay register 50, 65, 70 arithmetic unit 80 recorder

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Jean Fischer Day 6242 Kronberg, Tallstraße 3 (72) Inventor Paul De La Basita, Septerrato, Belgium Motosale 27 Agfa Gewert Namrose Rose Bennaught Inside the chap

Claims (10)

[Claims] 1. A method of screening continuous tone images; selecting raw image pixels according to a randomized space-filling two-dimensional curve, and then selecting the raw image pixels,
As follows, that is, from the tone value of the unprocessed image pixel, determine the reproduction value used to record the image pixel on the recording medium, the tone value and the reproduction value of the unprocessed image pixel An error value is calculated based on the difference, so that the unprocessed image pixel becomes a processed image pixel, the error value is added to the tonal value of the unprocessed image pixel, and then with the obtained total value. The error by replacing the tonal value or by replacing the tonal value of each of the unprocessed image pixels to which the error value is distributed with the sum of the tonal value of the unprocessed image pixel and the portion of the error. A method of screening a continuous tone pixel comprising distributing values over two or more unprocessed image pixels and repeating the above steps until all image pixels have been processed. 2. The method of claim 1, wherein the continuous tone image is subdivided into a matrix of unprocessed image pixels and the image pixels in the matrix are processed before the next matrix is processed. 3. The method of claim 2, wherein the matrix is processed in a random sequence. 4. The subdivision of the matrix occurs recursively until the size of the matrix matches the image pixels, and at each level of subdivision a random order of processing the matrix of that level is determined. Item 2. The method according to Item 2. 5. The method of claim 1, wherein the randomized space-filling quadratic curve is a randomized space-filling two-dimensional fractal curve. 6. The method of claim 5, wherein the randomized space-filling two-dimensional fractal curve is a randomized Hilbert curve or a randomized Peano curve. 7. The method according to claim 1, wherein the determination of the reproduction value is performed by comparing the tone value of a pixel of the unprocessed image with one or more threshold values. Method. 8. The method according to claim 1, wherein the calculated error value is a weighted error value. 9. The determination of the reproduction value is performed by comparing a tone value of a pixel of the unprocessed image with a threshold value, and the determination of the tone value and the reproduction value of the pixel of the unprocessed image. 7. A method according to any one of the preceding claims, wherein the error calculated from the difference is added to the tonal value of the next unprocessed image pixel selected for processing. 10. The method according to claim 1, wherein the error is a weighted average of the differences between the tonal values of at least two image pixels and their corresponding reproduction values.