JPH02113668A - Half tone correcting method - Google Patents

Abstract

PURPOSE:To carry out the optical correction of a picture at every partial picture, and to prevent the loss of a low density level at the converted picture by obtaining an optimal half tone correcting curve corresponding to a density distribution characteristic at every partial picture, and using the half tone correcting curve corresponding to each partial picture element when picture element data on the partial picture elements are respectively converted into the picture. CONSTITUTION:In a synthetic picture 3 which is composed by arranging the partial pictures 1a to 1d of the plural blocks of the objective picture, a histogram 5 concerning an input signal level and the corresponding number of the picture elements are prepared for the respective partial pictures, and a corresponding cumulative distribution curve 6 is obtained from the histogram. It is converted into a straight line or deformed, made into the half tone correcting curve 6 of the partial pictures, and when the picture element data on the respective partial pictures are converted into the picture, the half tone correction is executed with the use of the half tone correcting curve 6. Thus, the optimal correction can be executed at every partial picture, and since a block boundary part is ignored when the density distribution is checked, the loss at the low density level can be prevented.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention relates to a halftone correction method, and particularly to a method for improving or modifying the contrast of a target image so as to have arbitrary desired tone characteristics. The present invention relates to a halftone correction method by which an image can be obtained.

[Conventional technology]

Conventionally, for example, when recording an image with a biased density distribution using a hard copy device, etc., there has been a problem that the halftone function of the hard copy device cannot be effectively utilized because the contrast is low. was there. In particular, images displayed on a suitable display device (
When converting a so-called soft copy to a hard copy, the dynamic range of the hard copy device is usually much narrower than that of the corresponding display device, so the halftone function of the hard copy device can be effectively utilized. It becomes necessary to do so.

An example of a method for making effective use of such a halftone function is the method disclosed in Japanese Patent Application Laid-open No. 45876/1983. According to this method, a histogram of an input image signal is created, and its cumulative distribution curve is used as a halftone correction curve.

FIG. 5 is an exemplary diagram of the density distribution when an image is recorded based on the above conventional method. In this Figure 5, the density of the image is taken as y on the horizontal axis, and
The frequency h' (y) for each density of the image is plotted on the vertical axis, and here the density distribution of the image is shown as a straight line 51 where h'('S') = a. That is, in the example shown in FIG. 5, processing is performed such that the density distribution of the recorded image becomes -like across all density regions.

FIG. 6 is an exemplary diagram of a histogram curve 61 created for an image to be processed.

In the figure, the horizontal axis represents the density distribution of the image as X, and the vertical axis represents the histogram value h(x
) has been taken.

Further, FIG. 7 is an exemplary diagram of the transformation function y=f(x) for applying the required transformation to the target image, and is an example diagram of the transformation function y=f(x) for the image having the histogram shown in FIG. 6 above. By applying the conversion process to the ``bipod'' shown in Fig.
It is used to obtain various concentration distributions. The curve 71 shown in FIG. 7 is called a cumulative distribution curve, and is expressed as y=f (x)= h(x)dx.

Next, the operation of the above conventional example will be explained. Now, the 6th
Assuming that an image having the histodurum shown in the figure is targeted for a recording operation, a conversion process based on the conversion function f (x) shown in FIG. An image with a negative density distribution as shown in FIG. 5 is output.

[Problem to be solved by the invention]

In the conventional halftone correction method, a single pistodram is created from the density distribution of the entire image, and this is used as a conversion function. When converting a composite image in which a plurality of different partial images are arranged using this method, the following problems arise.

Figure 8 is an example of a composite image, 1a to 1d are partial images, 2
is the block boundary. Here, for example, the partial image 1a is an image with a highly concentrated distribution, and the remaining 1b+ 1c+
ld is an image whose distribution is concentrated at low density.

The first problem is that the data at the block boundary 2, which does not belong to the partial image 1 when the histogram is created, is also counted. If the block boundary portion 2 is white data, the frequency of the density O will increase in the histogram. If we consider the cumulative distribution curve in this state, the y-intercept of the curve in FIG. 7 will move considerably above the origin. This means that even at a low density level, the output value will be taken up in proportion to the larger output value, making it impossible to record near low density (white).

The second problem is that if you try to process a mixture of partial images 1a with a high density center and partial images 11) with a low density center with a single histogram, the optimal correction will not be possible for each partial image. The point is that it cannot be done. That is, the partial image 1a with the center of high density is corrected in the direction of low density, and the partial image 1tz lc, ld with the center of low density is corrected in the direction of high density. However, in this example, since the distribution of low-density parts including the block boundary part 2 accounts for a large proportion, the composite image 3 as a whole is corrected in the direction of high density. Therefore, since the partial image 1a originally has a high density center, it will be corrected in an undesirable direction.

The problems with the conventional method can be summarized as follows.

1) The block boundary portion 2 is regarded as a white pixel.As a result, the low density level after conversion is lost.

2) Optimal conversion cannot be performed for each partial image 1, resulting in undesirable correction in some cases.

This invention was made to solve the various problems mentioned above, and is also useful in preventing the loss of low density levels after correction due to viewing block boundaries as white pixels. The purpose of this invention is to obtain a halftone correction method that can perform optimal conversion for each partial image.

[Means to solve the problem]

In the halftone correction method according to the present invention, when the target image is a composite image composed of plural blocks of partial images, a histogram regarding the input signal level and the corresponding number of pixels is created for each partial image. Then, a corresponding cumulative distribution curve is obtained from the histogram, and this is used directly or transformed as a halftone correction curve for the partial image, and when converting the pixel data of each partial image 1-, into an image, The system is designed to perform halftone correction using a tone correction curve.

[Effect]

In the halftone correction method according to the present invention, when correcting a composite image, optimal correction can be performed for each partial image by examining the density distribution of each partial image separately and determining a halftone correction curve. Furthermore, since block boundaries are ignored when examining the density distribution, loss of low density levels can be prevented.

〔Example〕

An embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 is an explanatory diagram showing a halftone correction method according to an embodiment of the present invention. In the figure, 1a to 1d are partial images, 2 is a block boundary, 3 is a composite image composed of partial images 18 to 1d and block boundary 2, 4 is an input image of composite image 3, and 5 is each partial image 1a. -1d histogram, 6 is a halftone correction curve obtained from each histogram 5, and 7 is a converted image after performing halftone correction.

Further, FIG. 2 is a block diagram of a halftone correction circuit according to the method of the embodiment described in -1-. In the figure, 8 is an image memory for storing target image data. Reference numeral 9 denotes a CPU circuit that performs necessary processing on the target image data and manages the operation of the entire apparatus. 11 is a halftone correction table RAM 11 in which data for applying appropriate halftone correction to the target image is stored in a table format; 10a is provided between the image memory 8 and the halftone correction RAM II; 12 is a partial image number designation code input to the halftone correction table RAM 11;
Reference numeral 10b denotes a second multiplexer 10b, which is provided after the halftone correction table RAMII and supplies an output signal from its b terminal side to an appropriate output display means or the like. Reference numeral 13 denotes an address bus that supplies required address φ data from the CPU circuit 9 to the a terminal of the first multiplexer 10a.

Further, 14 is a data bus, and image memory 8, C
PU circuit 9, 1) terminal side of the first multiplexer 10a,
The terminals a of the second multiplexer 10b are connected to each other.

Further, FIG. 3 is a flowchart for explaining the method of this embodiment, which is carried out by the correction circuit shown in FIG. 2 above.

Next, the operation according to the method of this embodiment will be explained. Here, it is assumed that the necessary image data has already been stored in the image memory 8, and that the image data read from the image memory 8 is to be subjected to halftone correction.

First, as shown in flowchart 1 of FIG. 3, a step S1j is performed in which 10% or less of the total number of pixels of the target partial image is sampled in units of scanning lines or columns. , ), the CPU circuit 9 performs the following processing. Immediately, this CPU circuit 9 calculates the histogram 5 based on the sampled image data (S
i2) Also, perform a previous calculation to obtain a cumulative distribution curve from this sampled data. Then, by using this cumulative distribution curve as it is or by transforming it, a halftone correction table value is generated (813), and this is written into the halftone correction table RAMII (S14). In this way, the halftone correction curve 6 of the target partial image is obtained. Note that, at this time, both the eleventh and second multiplexers 10a and 10b are turned to the a side.

The processes of steps SL1 to SL4 described above are performed on all the partial images 1a to 1d making up the composite image 3.

When writing each halftone correction table value to the halftone correction table RAMII, in S14, the partial image number designation signal 12 is manipulated and written to different addresses. The processing of Sll-8 and Sll-14 is performed on all partial images 1a to
Repeat until writing of table value 1d is completed (S1
5) The operations up to this point are the process of creating a halftone correction table.
This is the preparatory stage for halftone correction. Then, in the processing after S15, image data is sequentially read out from the image memory 8, and correction is executed using the halftone correction table RAMII.

First, the first pixel data to be read out from the image memory 8 and processed is designated (S16). Then, the number of the partial image to which the pixel belongs is set in the address line of the halftone correction table RAMII by the partial image designation signal 12 (S1
7). In this state, the relevant pixel data is read out from the image memory 8, and the correction table value of the corresponding partial image written in advance in the halftone correction table RAMII is read out (S
18). The operations in S17 and 818 are performed on all the pixel data forming the composite image 3. Then, it is determined whether or not the correction of all pixel data has been completed (S19), and if it has not been completed, the next pixel data in the image memory 8 is specified (S20), and the operations 817 and S18 are repeated. In addition,
At this time, the first and second multiplexers 10a, 1
Both 0b are knocked down to the b side.

If there is a block boundary part 2 in the composite image 3 that does not belong to any of the partial images 1a to 1d, a partial image designation number 12 is provided exclusively for pixel data on the block boundary part 2, and the pixel data on the halftone correction table RAMII is It is sufficient to write data such that the input value is output as is in the corresponding area.

In the halftone correction processing operations explained so far, in order to calculate histogram 5, it is only necessary to sample 10% or less of the total number of pixels of the target image, and from among all pixels, the scanning line By uniformly sampling the characteristics of the entire image in units or rows and calculating and creating histogram 5, a characteristic that is almost the same as histogram 5 obtained from the data of the entire target image is obtained. be able to. Furthermore, if the amount of sampling is small, the time required for the processing is also short, and it has been found that sampling only 10% of all pixels is actually sufficient.

Next, the operation of the above embodiment will be further explained with reference to FIG.

In this example, the input image 4 is a composite image 3 composed of four partial images 1a to 1d, each of which has a partial image (t 1 a to
It is assumed that 1d has different density distribution characteristics as shown in histogram 5. Therefore, the halftone correction curve 6 obtained from the cumulative distribution curve also has a different shape for each partial image.

Halftone correction curve 6 corresponding to each partial image 1a to 1d
When converted, the converted image 7 consists of all partial images 1a to
The optimum correction is performed for 1d. In particular, if the cumulative distribution curve is directly used as the halftone correction curve 16, the density distribution characteristics of all the partial images 1a to 1d are converted into an image having uniform distribution characteristics as shown in FIG.

In addition, in the second embodiment, the cumulative distribution curve was used as it is as the halftone correction curve 6 of each partial image 1a to 1d, but
A modified version of this may also be used.

In addition, the example 1 is the partial image 1. a, 1b+
The case of the composite image 3 in which 1et1d are separated from each other has been explained, but this is also a partial image le as shown in FIG.
The present invention can also be applied to a composite image 3 in which tILIg overlaps.

Furthermore, the present invention can also be applied to ordinary images other than the composite image 3. This is because a normal image can be regarded as a composite image 3 consisting of only one block of partial images 1.

〔Effect of the invention〕

As described above, according to the present invention, when correcting a composite image, the density distribution of each partial image is examined separately, the optimal halftone correction curve is determined according to the density distribution characteristics of each partial image, and each When converting the pixel data on the partial pixels of the block into an image, the halftone correction curve corresponding to each partial pixel is used, so the optimal correction can be performed for each partial image. Since the border is ignored when examining the distribution, it has the effect of preventing defects at low density levels in the converted image.

[Brief explanation of the drawing]

FIG. 1 is an explanatory diagram of a halftone correction method according to an embodiment of the present invention, FIG. 2 is an illustrative diagram of a halftone correction circuit that implements the two-legged embodiment method, and FIG. 3 is an operation of the above embodiment method. FIG. 4 is a diagram showing an example of a composite image, FIGS. 5 to 7 are diagrams illustrating various curves to explain the conventional method, and FIG. 8 is a composite image of a conventional example. It is a figure showing an example. 1a to 1d are partial images, 2 is a block boundary, 3 is a composite image, 4 is an input image, 5 is a histogram, 6 is a halftone correction curve, 7 is a converted image, 8 is an image memory, 9 is C, PU
10a is a first multiplexer, 10b is a second multiplexer, 11 is a halftone correction table RAM 112 is a partial image number designation signal, 13 is an address bus, and 14 is a data bus. Note that the same reference numerals in the figures indicate the same or equivalent parts.

Claims (1)

[Claims] 1) For a digital image signal having halftones, a cumulative distribution curve is determined by sequentially accumulating the output signal level for each input signal level from a histogram regarding the input signal level and the corresponding number of pixels. In the halftone correction method using this cumulative distribution curve, if the target image is a composite image formed by arranging partial images of multiple blocks, a histogram is created for each partial image, and the corresponding cumulative distribution is calculated from the histogram. A distribution curve is obtained, a halftone correction curve is created for each partial image by directly or transformed it, and the pixel data on each corresponding partial image is converted using the halftone correction curve to perform halftone correction. A halftone correction method characterized by: