JPS59176978A - Picture processor - Google Patents

Abstract

PURPOSE:To prevent moire by optimizing the period of a dither matrix according to a spatial frequency of an input picture to minimize the deterioration of picture quality due to dither processing. CONSTITUTION:A picture read from an original picture while being disassembled into picture elements is inputted to a density distribution measuring circuit 2, an autocorrelation function operating circuit 3, and a processor 4. The density distribution circuit 2 and the processor 4 decide an intermediate tone region including mesh points with the input picture. The auto-correlation function operating circuit 3 and the processor 4 detect the spatial frequency of the input picture. Further, the dither processing is applied to the input picture via the processor 4 by using the dither matrix selected by the processor 4.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field] The present invention relates to an image processing device that processes an image by decomposing it into pixels.

[Prior art]

2. Description of the Related Art It is known that moiré (striped patterns) occur when a halftone image such as a halftone-printed photograph is separated into pixels and read in a facsimile machine, a digital copying machine, or the like. In order to remove such moiré, a method has been adopted in which the period of a dither matrix used for dither processing of a halftone image is randomly changed, but this method has the problem of significantly lowering the image quality.

〔the purpose〕

An object of the present invention is to provide an image processing device that can minimize image quality deterioration due to dither processing and remove moiré.

〔Example〕

In the image input/output system, the spatial frequency specific to the input image (
The spatial frequency of the image reading sensor is T8, and the period of the dither matrix used for dithering is T. Then, moiré is IT knee T8,1...
(1) I T knee' Tol -
°−(2)l Ts −ToI
-・---(3) Any of the frequency components can be included.

Usually it is T8 nil To (ru is an integer), (2)
, (3) Moiré having the frequency components becomes a problem.

However, in the past, T was used regardless of the T-work. Since the image quality was randomized to reduce moiré, there was a problem in that the image quality deteriorated significantly.

Therefore, the present invention aims at T, which causes deterioration in image quality. Detects the T-shape in the halftone image quality area to be dithered without performing randomization, and selects the optimal T-shape according to the T-shape. By selecting the following, the aim is to simultaneously reduce image quality deterioration and suppress moiré.

An embodiment of the present invention will be described in detail below.

FIG. 1 shows a schematic configuration of an image processing apparatus according to the present invention.

Reference numeral 1 denotes a reading device (images, scanner) that separates the original image into pixels and reads it, and the image read here (input image) is sent to a density distribution measurement circuit 2 and an autocorrelation function calculation circuit 3.
, are input to a program-controlled processor 4.

The density distribution measurement circuit 2 and processor 4 determine a halftone area including halftone dots from the input image. The algorithm will be explained below.

When the image is divided into small regions of MXN pixels as shown in Figure 2 and the density distribution of each small region is examined, it is found that Figure 3 (a) and ( A histogram like b) is obtained. Figure 3 (
In a), the horizontal axis is the concentration level and the vertical axis is the frequency. Also the third
The horizontal axis of FIG.
)−p(i,j+1)l, and the vertical axis is the frequency. In both figures, the characteristics of the curve ■ are obtained in the halftone image area, and the characteristics of the curve ■ are obtained in the monochrome image area.

Since the curves ■ and ■ are clearly different, they can be used to determine the halftone image area.

Therefore, the following parameters b and c are determined for each small region of the input image.

Here, 5(1), 5(2), S (3n is the third
This corresponds to the area of each region shown in Figure (a) or (b).

Then, the determined parameters b, C and the judgment threshold T1゜'r
2, and when b>T and C, ,>T2, the small area is determined to be an intermediate tuning 1III image area.

11j The concentration distribution measuring circuit 2 is a circuit that obtains the histogram shown in FIG.
It is compared with T2 to determine whether it is in a halftone area.

The autocorrelation function calculation circuit 3 and processor 4 detect the spatial frequency of the input image, and the algorithm thereof is as follows.

The autocorrelation function R(k) of the input image is calculated by the following equation.

R(k) No. 2 P(i, j)・P(i, j+k)...(
6)" However, 1 (21.2, 3......, L) (Practically, L is sufficient to add).

The processor 4 searches for k that satisfies the following formula, and sets k in descending order of I(+, 2+...T kll).

R(k-1) < R(k) < R(kll)
...(7) In Figure 4, k obtained in this way is plotted on the horizontal axis,
It is a graph showing R(k> as I'k'hlll.

Processor 4 calculates the average value of the interval between k and kj + 1. The value is the spatial frequency T of the input image.

Returning to FIG. 1 again, 5 is the period T. This dither processing circuit has a plurality of different types of dither matrices, and uses the dither matrix selected by the processor 4 to perform dither processing on the input image input by the processor 4. 6 is a fixed threshold value binarization circuit that binarizes the fixed threshold value. Reference numeral 7 denotes a plotter that suppresses the binary image input from the dither processing circuit 5 or the fixed threshold value binarization circuit 6.

FIG. 5 is a flowchart showing the processing of the processor 4. The valley steps will be explained in order.

Step (2): Compute the above equations (4) and (5) to obtain parameters b and c.

Step ■: This is a step of determining whether it is a halftone image area, and b and c are set to a determination threshold T1. Compare each with T2, b
) Determine whether the condition T1c>T2 is satisfied. NO
If so, it is a black and white image area, so jump to step @.

Step ■: Calculate k that satisfies the above equation (7).

Step (2): Calculate the average value of the interval between and kt + ] to obtain the spatial frequency 1' of the input nia image.

Step ■: Period of the currently selected dither matrix ′■゛. It is determined whether the difference value 'i'o1 between the value and the spatial frequency T is smaller than the value 'r3. If NO, no moiré will appear, so jump to step ■.

Step ■: Since moiré is expected to occur, a warning is issued to the operator.

Step ■: Another period ``1'' where IT knee'ro1 is maximum. A dither matrix having the following value is selected and designated to the dither processing circuit 5. The dither processing circuit 5 has a specified period. Tisamado l) Switch to couscous.

Step ■: Current T. Select as is.

Step (2): Instructs the dither processing circuit 5 to perform dither processing on the stroke signal of the corresponding small area.

Step [phase]: Instructs the fixed-value binarization circuit 6 to perform binarization processing on the image signal of the corresponding small area.

A specific example of the concentration distribution measuring circuit 2 is shown in FIG. 5R
IL~5R1i~.i is a shift register that sequentially delays the image signal manually inputted from the reading device 1 by one line. 5hoo~S ROM are shift registers that delay the image signals outputted from the reading device 1 or the corresponding shift register 5l (11~IM) by N pixels.

Ah) 111 is an adder, '5UBI is a subtracter, REG
1 is a register.

Adder A, 1) L) 1 adds 1 to the contents of the address of register REGI corresponding to the result of addition of the input signal, and subtractor SUB 1 adds 1 to the contents of the address of register REUI corresponding to the result of subtraction of the human input signal. Subtract 1 from. As a result, the histogram shown in FIG. 3(a) is obtained in the register RE G1.

L) 1 is a delay circuit that delays the pixel signal by one pixel, DS
UI3 is a subtracter that calculates the density difference between the image signal (adjacent pixels) of the input example and output example of the delay circuit, S R41 to S R4
M is a shift register that sequentially delays the output signal of the subtracter DS[JB by one line. SR20 to S R2M are the subtracter DSUB or the corresponding shift register 5R4
1 to S) t4 This is a shift register that delays the output signal of M by N pixels.

A1) January j) IJ It is a booster and adds 1 to the contents of the address of the register It E G 2 corresponding to the mouth result of the human input signal. 5U132 is a subtracter and subtracts the human input signal. Subtract 1 from the contents of the address of register FLEu2 corresponding to the result. The histogram shown in FIG. 3(b) is stored in register ktEG2.

CN 'II' 1 is a counter, pixel clock C
1゜1 (count 〃0 calculator At) [11, AL
) 1) 2 and 3'I diagnosis SUB], 5tjB2 reset signal 6'main-f for 3'.

FIG. 7 shows the autocorrelation function (1, IJ 1-〇+"4 is a delay circuit that sequentially delays the image signal by one pixel, At) Dll to IN are the reading device 1. Both parts 1g and the corresponding delay circuits D1 to D are manually operated.
This is an adder that adds the image signals output from IN/J. A, IJ D 21~AIJI) 2N is an adder, and the adder A corresponding to the contents of the corresponding register R1
Add the output values of DDII to ADIN. The above formula (6)
RQc) is obtained in registers R1 to RN.

The number (N) of registers R1-RN should be about four ()
.

It should be noted that the above-described configuration of the algorithm and means for determining the halftone region and detecting the spatial frequency are merely examples, and may be modified as appropriate.

〔effect〕

As detailed above, the present invention does not randomize the period of the dither matrix (it optimizes the period of the dither matrix according to the spatial frequency of the input image. Therefore, according to the present invention, the period of the dither matrix is optimized according to the spatial frequency of the input image. Moiré can be prevented while minimizing image quality deterioration due to dither processing.

[Brief explanation of the drawing]

Fig. 1 shows a schematic configuration of an example of an image processing device according to the present invention, Fig. 2 is an explanatory diagram of a small area of an input image, and Fig. 3 shows the density distribution of a medium/tuned image area and a monochrome image area. A diagram showing the differences, FIG. 4 is a diagram for explaining the relationship between the autocorrelation function and all the same frequencies, FIG. 5 is a processing flow diagram of the processor, and FIG. 6 is a block diagram showing an example of a concentration distribution measurement circuit. 7th
The figure is a block diagram showing an example of an autocorrelation function calculation circuit. 2...Concentration distribution measurement circuit, 3...Autocorrelation function calculation circuit, 4...Processor, 5...Dither processing circuit. Representative Patent Attorney Makoto Suzuki A-6 Figure Sword 3 Figure 4 Fang Figure 5

Claims (1)

[Claims] Halftones for each small area of the pixel-resolved input image? t'
a means for determining the spatial frequency of the input image, a means for performing dither processing on a small area of the input image determined to be a halftone, and a means for determining the period of the dither matrix used for dither processing, An image processing device characterized by comprising means for selecting an image space j according to a wave number.