JP4113335B2 - Image processing apparatus, method, and program - Google Patents

Description

となる。
【００５８】
ここで、
ｈ(-1,-1)＝1/16、ｈ(-1,0)＝2/16、ｈ(-1,1)＝1/16
ｈ(0,-1)＝2/16、ｈ(0,0)＝4/16、ｈ(0,1)＝2/16
ｈ(1,-1)＝1/16、ｈ(1,0)＝2/16、ｈ(1,1)＝1/16
である。ｈ(K,L)は、平滑化を行うフィルタの係数である。このフィルタの係数は,平滑化特性を示せば任意に設定できるが、当該実施形態ではハードウエアでの処理を考慮して３×３の範囲において２のべき乗で表現できる係数に設定した。
【００５９】
原画像の要素色濃度分布が図７に示すとおりであったとすると、平滑化後の画像は、図８に示すように濃度変化の割合が全体的に小さくなる。
【００６０】
次に、平滑化前後の画素の差Diffを、
Diff＝Ｒin(0,0)−Ｒ_SM(0,0) … (5)
から計算する（ステップ６４）。
【００６１】
そして、修正した差Diff’を、
Diff≧0の場合には
Diff’＝Diff … (6)
とし、
Diff’＜0の場合には、
Diff’＝0 … (7)
とする（ステップ６６）。式(6)および式(7)を用いてDiffを修正するのは、差Diffを正の値に限定するためである。このようにDiffを正の値に限定することによって、濃度が薄く（値が大きく）なる方向の強調だけを行えるようになる。
【００６２】
通常のアンシャープマスキング処理を行うと、文字などのエッジ部がシャープになるととともに、網点画像の場合にモアレが発生してしまう。しかし、当該実施形態によるアンシャープマスキング処理によれば、網点画像の場合におけるモアレの発生を抑制することができる。すなわち、濃度が薄くなることによる網点画像でのパターンの変化は、濃度が濃くなることによるパターンの変化と比較して人間の感覚上あまり気にならないからである。
【００６３】
図９に、平滑化前後の要素色濃度分布を示し、図１０に、修正後の要素色濃度分布を示す。
【００６４】
最終的なアンシャープマスキング処理は、修正した差Diff’を原画像に加えて、
Ｒ_USM(0,0)＝Ｒ_in(0,0)＋Ｃ_USM・Diff’ … (8)
によって求められる。式(8)において、Ｃ_USMは、アンシャープマスキング処理の強さを制御するための定数であり、予め設定しておく。当該実施形態では、一例としてＣ_USM＝２とする。また、結果としてＲ_USM(0,0)にオーバーフローが生じる場合には、Ｒ_USM(0,0)の最大値を２５５までに限定する処理をもうける。図１１に、最終的なアンシャープマスキング処理を施した後の要素色濃度分布を示す。
【００６５】
黒強調処理
次に、図１２乃至図１４を参照して、黒強調処理部２０ｅによって実行される黒強調処理制御プログラムを説明する。
【００６６】
黒強調処理は、(1)黒領域を抽出する処理と、(2)抽出領域を強調する処理と、を備える。
【００６７】
図１２に、抽出する黒領域の概念を説明するための図を示す。図１２の立方体の斜線で囲まれた領域が黒領域であり、ＲＧＢ空間としてみれば、輝度・彩度ともに小さな領域である。Ｂが一定の平面によるＲＧＢ空間の切断面を考えると、Ｂが小さいとき黒領域は左上に存在し、Ｂが大きくなるにしたがって黒領域は徐々に小さくなる。ＲＧＢ空間で輝度・彩度とも小さい領域が黒領域であることを用いて、原画像に対して輝度および彩度を計算して、輝度および彩度の加重平均を用いて黒量を計算し、黒領域を抽出する。図１２の概念図のように、Ｂが大きくなるにしたがって、三角形として存在する黒領域が徐々に小さくなることが確認できる。
【００６８】
図１３に、黒強調処理部２０ｅによって実行される黒強調処理制御プログラムを説明するためのフローチャートを示す。ここで、黒強調処理対象画素を、
｛Ｒin’(0,0),Ｇin’(0,0),Ｂin’(0,0)｝ … (9)
とし、黒強調処理終了後の画素を、
｛Ｒ_BK(0,0),Ｇ_BK(0,0),Ｂ_BK(0,0)｝ … (10)
とする。
【００６９】
図１３に示すように、当該実施形態における黒強調処理（図３のステップ５０における処理）では、黒強調処理対象画素のＲＧＢ値から、輝度I(0,0)および彩度相当量S(0,0)を

によって計算する(ステップ８０および８２)。式(12)において、除算を行わずに彩度相当量を計算しているので、ハードウエアの負担を軽減することができる。
【００７０】
次に、式(11)および式(12)から計算される輝度I(0,0)および彩度相当量S(0,0)から、以下の式(13)および式(14)：
Dr(0,0)＝２５５−I(0,0) … (13)
Gr(0,0)＝２５５−S(0,0) … (14)
から暗さDr(0,0)およびグレー度Gr(0,0)を計算する。そして、計算された暗さDr(0,0)およびグレー度Gr(0,0)を用いて、以下の式(15)：
BK(0,0)＝C_BK｛α・Dr(0,0)＋(１−α)・Gr(0,0)｝ … (15)
0≦α≦1
から黒量BK(0,0)を計算する（ステップ８４）。式(15)において、C_BKは、黒量の抽出を制御するための定数であり、値が大きい程、多くの黒量を抽出する。また、αは、黒量において暗さとグレー度との相対的重みを制御するための定数であり、値が大きい程、輝度（暗さ）を重視して黒量を算出する。この２つの定数は、いずれも予め設定しておく。当該実施形態では一例としてC_BK＝1、α＝0.75とする。
【００７１】
黒量を計算した後、シャドウ部の強調処理を行い（ステップ８６）、シャドウ部を強調した画素のＲＧＢ値と処理対象画素のＲＧＢ値との混合によって処理終了画素のＲＧＢ値を計算する（ステップ８８）。このとき、抽出した黒量によって混合の割合を変化させる。この処理では、ＲＧＢに対して等しく行われるため、以下の説明では代表してＲについて説明する。
【００７２】
Ｒに関してシャドウ部を強調した画素R_SHD(0,0)は、
R_SHD(0,0)＝(２・Ｒin’(0,0)／255)²・128， 0≦Ｒin’(0,0)≦128 … (16)
R_SHD(0,0)＝Ｒin’(0,0)， 128≦Ｒin’(0,0)≦255 … (17)
によって計算される。式(16)および式（17）による変換は、0≦Ｒin’(0,0)≦128においてγ関数を用いて入力値を変換して出力し、128≦Ｒin’(0,0)≦255において入力値をそのまま出力するものであり、シャドウ部の強調を行うことができる。式(16)および式（17）による変換を図１４に示す。なお、ハードウエアとして実装する場合には、式(16)を
R_SHD(0,0)＝(Ｒin’(0,0))²／128， 0≦Ｒin’(0,0)≦128 … (18)
と近似する。これは、式(16)が255による除算を含んでおり、ハードウエアに負担がかかり好ましくないので、255による除算を含まないようにするためである。式(15)の黒量および式(16)並びに式(17)のシャドウ強調画素を用いて、黒強調処理の最終的処理画素R_BK(0,0)は、
R_BK(0,0)＝{BK(0,0)・R_SHD(0,0)}／255＋{１−BK(0,0)／255}・Ｒin’(0,0)… (19)
を近似した式
R_BK(0,0)＝{BK(0,0)・R_SHD(0,0)＋(255−BK(0,0))・Ｒin’(0,0)}／256 … (20)
から計算する。式(20)は、シャドウ部を強調した画素と黒強調処理対象画素との混合によって処理終了画素を計算するものであり、この際、抽出した黒量に応じて、混合の割合を変化させている。式(20)において近似式を用いているのは、式(19) が255による除算を含んでおり、ハードウエアに負担がかかり好ましくないので、255による除算を含まないようにするためである。
【００７３】
他の実施形態
図１６に示すように、図１に示す画像処理装置からなる画像処理部２０ａと、スキャナ部１０ａと、プリンタ部３０ａと、を有するスキャナプリンタコピー（ＳＰＣ）に対しても本願発明による画像処理を適用することができる。なお、スキャナ部１０ａのハードウエアにおいて、上記解像度変換処理を行うように構成すると、他のハードウエア（画像処理部２０ａおよびプリンタ部３０ａ）の負担を軽減することができる。
【００７４】
さらに、図１７に示すように、アプリケーション１０ａから生成される画像データに対しても本願発明による画像処理を適用することができる。
【００７５】
【図面の簡単な説明】
【図１】本発明の一実施形態にかかる画像処理制御方法を適用した画像処理システムを示す機能ブロック図である。
【図２】本発明の一実施形態にかかる画像処理装置の具体的ハードウエア構成例を示す概略ブロック図である。
【図３】画像処理装置によって実行される画像処理制御プログラムの第１実施例を説明するためのフローチャートである。
【図４】アンシャープマスキング処理の対象となる近傍画素を説明するための図である。
【図５】処理対象画素を移動させて行く状態を示す図である。
【図６】アンシャープマスキング処理部２０ｄによって実行されるアンシャープマスキング処理制御プログラムを説明するためのフローチャートである。
【図７】アンシャープマスキング処理の概念を説明するための図（１）である。
【図８】アンシャープマスキング処理の概念を説明するための図（２）である。
【図９】アンシャープマスキング処理の概念を説明するための図（３）である。
【図１０】アンシャープマスキング処理の概念を説明するための図（４）である。
【図１１】アンシャープマスキング処理の概念を説明するための図（５）である。
【図１２】黒領域の概念を説明するための図である。
【図１３】黒強調処理部２０ｅによって実行される黒強調処理制御プログラムを説明するためのフローチャートである。
【図１４】シャドウ部強調のための変換カーブを示す図である。
【図１５】解像度変換部２０ｇによって実行される解像度変換処理制御プログラムを説明するためのフローチャートである。
【図１６】本発明の他の実施形態にかかる画像処理制御方法を適用した画像処理システムを示す機能ブロック図である。
【図１７】本発明の他の実施形態にかかる画像処理制御方法を適用した画像処理システムを示す機能ブロック図である。
【図１８】画像処理装置によって実行される色補正処理制御プログラムの第２実施例を説明するためのフローチャートである。
【符号の説明】
１０ 画像入力装置
１１ａ スキャナ
１１ｂ デジタルスチルカメラ
１１ｃ ビデオカメラ
１２ コンピュータ本体
１２ａ オペレーティングシステム
１２ｂ ディスプレイドライバ
１２ｃ プリンタドライバ
１２ｄ アプリケーション
１３ａ フロッピーディスクドライブ
１３ｂ ハードディスク
１３ｃ ＣＤ−ＲＯＭドライブ
１４ａ モデム
１５ａ キーボード
１５ｂ マウス
１７ａ ディスプレイ
１７ｂ カラープリンタ
２０ 画像処理装置
２０ａ 色補正処理部
２０ｂ 色変換部
２０ｃ 二値化部
２０ｄ アンシャープマスキング処理部
２０ｅ 黒強調処理部
２０ｆ 指示部
３０ 画像出力装置[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image processing apparatus, method, and recording medium that perform enhancement processing after resolution conversion.
[0002]
[Prior art]
2. Description of the Related Art Conventionally, in a scanner / printer / copier having a scanner as an input device and a printer as an output device, resolution conversion is performed twice when performing enlarged copy. Then, when enhancement processing such as black character enhancement processing is performed, resolution conversion is performed before and after the enhancement processing.
[0003]
[Problems to be solved by the invention]
However, performing resolution conversion after enhancement processing is one of the causes of moiré.
[0004]
SUMMARY An advantage of some aspects of the invention is to provide an image processing apparatus, a method, and a recording medium that can reduce the occurrence of moire.
[0005]
[Means for Solving the Problems]
In view of the above problems, the invention described in claim 1 is an image processing apparatus having a data generation unit and a printer unit, and is based on the input resolution of the data generation unit, the output resolution of the printer unit, and the enlargement / reduction ratio. A resolution conversion means for performing conversion processing and an enhancement processing means for performing enhancement processing after the resolution conversion processing are provided, and after the enhancement processing, printing processing is performed with substantially the same size.
[0006]
According to the image processing apparatus having the data generation unit and the printer unit configured as described above, the resolution conversion unit converts the resolution based on the input resolution of the data generation unit, the output resolution of the printer unit, and the enlargement / reduction ratio. Processing is performed. After the resolution conversion process is performed, the enhancement process unit performs the enhancement process. After the enhancement process, the printing process is performed with substantially the same size.
[0007]
The invention according to claim 2 is the image processing apparatus according to claim 1, wherein the data generation unit includes the resolution conversion unit.
[0008]
Further, the invention described in claim 3 is the image processing apparatus according to claim 1 or 2, wherein the data generation unit includes a scanner unit.
[0009]
According to a fourth aspect of the present invention, there is provided the image processing device according to any one of the first to third aspects, wherein the resolution conversion process is accompanied by a smoothing process.
[0010]
Furthermore, the invention described in claim 5 is the image processing apparatus according to claim 1 or 2, wherein the binarization process in the printer unit is an error diffusion process.
[0011]
The invention according to claim 6 is the image processing apparatus according to any one of claims 1 to 5, wherein the enhancement processing means reduces the density for each element color component based on the image data. A sharpness enhancement process for enhancing the sharpness by correcting the element color component in the direction is performed.
[0012]
The invention described in claim 7 is the image processing device according to any one of claims 1 to 6, wherein the enhancement processing means is configured to perform black enhancement processing based on the image data.
[0013]
The invention according to claim 8 is the image processing apparatus according to claim 6 or 7, wherein the sharpness enhancement process is a process for obtaining a difference between before and after smoothing of the color image data in a predetermined area; And processing for enhancing sharpness when the difference is positive.
[0014]
Furthermore, the invention described in claim 9 is the image processing apparatus according to any one of claims 6 to 8, wherein the sharpness enhancement processing includes processing for adjusting a degree of enhancing sharpness. The
[0015]
The invention according to claim 10 is the image processing apparatus according to any one of claims 7 to 9, wherein the black enhancement processing is performed on a black region.
[0016]
Furthermore, the invention according to claim 11 is the image processing apparatus according to claim 10, wherein the black region is obtained based on a luminance equivalent value and a saturation equivalent value.
[0017]
The invention described in claim 12 is the image processing apparatus according to any one of claims 7 to 11, wherein the black enhancement processing includes processing for enhancing a shadow portion.
[0018]
Furthermore, the invention described in claim 13 is the image processing apparatus according to any one of claims 6 to 12, wherein the black enhancement process is performed after the sharpness enhancement process. .
[0019]
The invention according to claim 14 is the image processing apparatus according to any one of claims 6 to 13, wherein the sharpness enhancement process or the black enhancement process is selectable.
[0020]
Furthermore, the invention described in claim 15 is an image processing method using a data generation unit and a printer unit for performing resolution conversion based on the input resolution of the data generation unit, the output resolution of the printer unit, and the enlargement / reduction ratio. And an enhancement processing step for performing enhancement processing after the resolution conversion processing. After the enhancement processing, printing processing is performed with substantially the same size.
[0021]
According to a sixteenth aspect of the present invention, there is provided a program for causing a computer to execute image processing using a data generation unit and a printer unit, the input resolution of the data generation unit, the output resolution of the printer unit, and the enlargement / reduction ratio. A program for causing a computer to execute resolution conversion processing for performing resolution conversion, enhancement processing after resolution conversion processing, and printing processing for performing printing at substantially the same size after the enhancement processing.
[0022]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.
[0023]
FIG. 1 is a functional block diagram illustrating an image processing system to which an image processing control method according to an embodiment of the present invention is applied. FIG. 2 is a schematic block diagram illustrating a specific hardware configuration example of an image processing apparatus. ing.
[0024]
Image processing device
In FIG. 1, the image processing apparatus 20 performs image processing on the image input signal supplied from the scanner 10, and outputs the color image data subjected to the image processing to the printer 30. Here, the image input signal represents the strength of each color of the color image while separating the color image for each predetermined element color, and is represented by gray when it is a chromatic color and mixed at a predetermined ratio. It consists of a neutral color and black.
[0025]
The image processing apparatus 20 includes a resolution conversion unit 20g that performs a desired resolution conversion based on an instruction from the instruction unit 20f; performs a desired color correction process based on an instruction from the instruction unit 20f, and inputs RGB gradation data A color correction processing unit 20a for converting (the image input signal) into R′G′B ′ gradation data; and the R′G′B ′ gradation data as CMY ((cyan, magenta, yellow), or A color conversion unit 20b for converting to CMYK obtained by adding black to this, or CMYKcm obtained by adding light cyan (c) light magenta (m) to this; and the converted CMY (or CMYK or CMYKcm) And a binarization unit 20c that performs gradation conversion of gradation data into binary data. In this embodiment, the binarization process is performed by an error diffusion method. The binarization processing by the error diffusion method diffuses the density error generated for each pixel to the surrounding unprocessed pixels, and for each pixel, the density error diffused from the processed pixel is displayed in the image of the pixel. This is a method of determining dot on / off by reflecting it in data. According to such a method, density error can be minimized, high-quality halftone processing can be realized, interference can be suppressed as compared with the case where dither processing is used, and moiré is generated. Can be reduced.
[0026]
Furthermore, the color correction processing unit 20a includes an unsharp masking processing unit 20d that performs unsharp masking processing based on an instruction from the instruction unit 20f, and a black enhancement processing unit 20e that performs black enhancement processing based on an instruction from the instruction unit 20f. , And is configured. Details of the processing of the unsharp masking processing unit 20d and the black enhancement processing unit 20e will be described later.
[0027]
Hardware configuration
In the present embodiment, the scanner 11a as the image input device and the digital still camera 11b output RGB (green, blue, red) gradation data as image data, and the printer 17b as the image output device 30 includes: CMY (cyan, magenta, yellow) as gradation data, CMYK obtained by adding black to this, or CMYKcm binary data obtained by adding light cyan (c) light magenta (m) thereto are required as input. The display 17a requires RGB gradation data as an input. On the other hand, the computer 12 includes an operating system 12a, a printer 17b, and a printer driver 12c and a display driver 12b corresponding to the display 17a. The image processing application 12d is controlled by the operating system 12a, and executes predetermined image processing together with the printer driver 12c and the display driver 12b as necessary. Therefore, a specific role of the computer 12 as the image processing apparatus 20 is to perform RGB processing on the input RGB gradation data after performing a desired resolution conversion process and then performing a high-speed and high-quality black character enhancement process. Gradation data is created, converted into binary data of CMY (or CMYK or CMYKcm) via the printer driver 12c, and printed on the printer 17b.
[0028]
Image processing control program
The image processing control program according to the present invention is normally recorded and distributed on a recording medium such as a floppy disk or a CD-ROM in a form readable by the computer 12. The program is read by a media reader (CD-ROM drive 13c, floppy disk drive 13a, etc.) and installed in the hard disk 13b. The CPU is configured to read out a desired program from the hard disk 13b as appropriate and execute a desired process. The image processing control program itself according to the present invention also forms part of the present invention.
[0029]
The modem 14a is connected to a public telephone line and is connected to an external network via the public communication line so that software and data can be downloaded.
[0030]
Hereinafter, an image processing control program executed by the image processing apparatus 20 will be described with reference to FIGS. 3 and 18. In this embodiment, a case where the image input device is a scanner and the image output device is a printer will be described.
[0031]
First embodiment
A first embodiment of the image processing control program executed by the image processing apparatus 20 will be described with reference to FIG.
[0032]
First, based on the value input via the instruction unit 20f of the image processing apparatus 20 shown in FIG. 1, the resolution conversion unit 20g executes resolution conversion processing described in detail later (step 40).
[0033]
When the unsharp masking process is instructed via the instruction unit 20f of the image processing apparatus 20 shown in FIG. 1 after the resolution conversion process (step 42, Yes), the unsharp masking process unit of the color correction processing unit 20a. 20d executes an unsharp masking process which will be described in detail later (step 44). The unsharp masking process is a process of outputting one pixel for a pixel input in a 3 × 3 range. FIG. 4 is a diagram for explaining neighboring pixels to be subjected to unsharp masking processing. As described above, in this embodiment, the values of i and j are integers in the range of −1 ≦ i ≦ 1 and −1 ≦ j ≦ 1, and the number of reference pixels is set to 9, so that even faster calculation processing is possible. As a result, the capacity of the memory used for the calculation can be further reduced.
[0034]
On the other hand, when the unsharp masking process is not instructed via the instruction unit 20f (step 42, No), the unsharp masking processing unit 20d of the color correction processing unit 20a does not perform the unsharp masking process and is illustrated in FIG. The pixel located at the center of the pixel in the 3 × 3 range is output as it is (step 46).
[0035]
Next, when black enhancement processing is instructed via the instruction unit 20f (step 48, Yes), the black enhancement processing unit 20e of the color correction processing unit 20a executes black enhancement processing which will be described later in detail (step). 50). The black enhancement process is a process of outputting one pixel with respect to one pixel input.
[0036]
On the other hand, when the black enhancement processing is not instructed via the instruction unit 20f (No in Step 48), the black enhancement processing unit 20e of the color correction processing unit 20a outputs one pixel as it is without performing the black enhancement processing ( Step 52).
[0037]
The unsharp masking process in steps 42 to 46 and the black enhancement process in steps 48 to 52 are independent processes. For example, when the load on the entire process is large, only one of the processes can be used. . However, it is preferable to perform both processes in view of the effect of the black character enhancement process. It is also possible to perform the unsharp masking process in steps 42 to 46 and the black enhancement process in steps 48 to 52 in the reverse order, but in the unsharp masking process, pixels in the 3 × 3 range are secured. In view of performing unsharp masking processing, it is not necessary to provide a black emphasis processing pixel storage memory when performing black emphasis processing after unsharp masking processing as shown in FIG. preferable.
[0038]
According to this embodiment, since the unsharp masking process and the black enhancement process are performed after the resolution conversion process, the occurrence of moire can be reduced.
[0039]
In performing the processing of steps 42 to 52, the above processing is performed for all the pixels while moving the target pixel as shown in FIG.
[0040]
Second embodiment
Hereinafter, a second embodiment of the image processing control program executed by the image processing apparatus 20 will be described with reference to FIG.
[0041]
In the first embodiment, the unsharp masking process and the black enhancement process can be selected. However, in the second embodiment, the adjustment amount of the unsharp masking process strength is set after the resolution conversion process is completed. Then, unsharp masking processing and black enhancement processing are automatically performed.
[0042]
As shown in FIG. 18, first, based on the value input via the instruction unit 20f of the image processing apparatus 20 shown in FIG. 1, the resolution conversion unit 20g executes a resolution conversion process described in detail later (step 53).
[0043]
Then, after the resolution conversion process, the adjustment amount C of the intensity of the unsharp masking process, which will be described in detail later, via the instruction unit 20f of the image processing apparatus 20 shown in FIG. _USM Is set (step 54), the unsharp masking processing unit 20d of the color correction processing unit 20a executes unsharp masking processing described in detail later (step 56). As in the first embodiment, the unsharp masking process is a process of outputting one pixel for a pixel input in a 3 × 3 range. By setting the number of reference pixels to 9 as shown in FIG. Furthermore, it is possible to perform a calculation process at a higher speed and to further reduce the capacity of the memory used for the calculation.
[0044]
After the unsharp masking process, the black enhancement processing unit 20e of the color correction processing unit 20a executes a black enhancement process that will be described in detail later (step 58). Similar to the first embodiment, the black enhancement process is a process of outputting one pixel with respect to one pixel input.
[0045]
As in the first embodiment, the unsharp masking process in step 56 and the black enhancement process in step 56 are independent processes. For example, when the load on the entire process is large, only one of the processes is used. You can also However, it is preferable to perform both processes in view of the effect of the black character enhancement process. The unsharp masking process in step 56 and the black enhancement process in step 58 can be processed in the reverse order. However, the unsharp masking process secures pixels in a 3 × 3 range and performs unsharp masking. In view of performing the processing, it is preferable to perform the black enhancement processing after the unsharp masking processing as shown in FIG. 18 because it is not necessary to provide a black enhancement processing pixel storage memory, and is preferable in terms of hardware configuration.
[0046]
In performing the processing in steps 56 and 58, the above processing is performed for all the pixels while moving the target pixel as shown in FIG.
[0047]
Resolution conversion process
Next, a resolution conversion processing control program executed by the resolution conversion unit 20g will be described with reference to FIG. In this embodiment, it is assumed that the output resolution A [dpi] of the printer 30 can be selected from 360 dpi and 720 dpi, and the input resolution C [dpi] of the scanner 10 can be selected from 400 dpi and 800 dpi.
[0048]
As shown in FIG. 15, first, the output resolution A [dpi] is selected from 360 dpi or 720 dpi via the instruction unit 20f (step 90), and the document enlargement / reduction ratio B [%] is input (step 92). .
[0049]
When the input resolution C [dpi] is selected from 400 dpi or 800 dpi via the instruction unit 20f (step 94), the bilinear enlargement / reduction ratio D [dpi]
D [dpi] = (A [dpi] / C [dpi]) × B [%]
(Step 96), and the process ends.
[0050]
In this way, when converting from the input image size to the output image size, the image size conversion can be performed by a single conversion process. The reason for using bilinear for resolution conversion processing is that an image after bilinear resolution conversion is smoother than an image by other resolution conversion processing, and as a result of this smooth resolution conversion, the occurrence of moire can be reduced. Because.
[0051]
If the resolution conversion processing is performed in the scanner hardware, the burden on other hardware (image processing apparatus, printer) can be reduced.
[0052]
Unsharp masking process
Next, an unsharp masking processing control program executed by the unsharp masking processing unit 20d will be described with reference to FIGS.
[0053]
FIG. 6 shows a flowchart for explaining an unsharp masking processing control program executed by the unsharp masking processing unit 20d. FIGS. 7 to 11 are diagrams for explaining the concept of unsharp masking processing.
[0054]
As shown in FIG. 6, in the unsharp masking process in the present embodiment (the process in step 44 in FIG. 3), the processes for RGB are sequentially performed. In this embodiment, the processing is performed in the order of R → G → B, but this order is an example, and the processing can be performed in another order. In addition, since each processing content is the same, in the following description, R will be described as a representative.
[0055]
Here, the pixel to be processed is
{Rin (0,0), Gin (0,0), Bin (0,0)}… (1)
And the scope of processing is
{Rin (i, j), Gin (i, j), Bin (i, j)} (2)
And However, i and j are integers in the range of −1 ≦ i ≦ 1 and −1 ≦ j ≦ 1. Also, after unsharp masking processing,
{R _USM (0,0), G _USM (0,0), B _USM (0,0)}… (3)
And
[0056]
When the unsharp masking process in step 44 is started, first, the processing flag is set to red (step 60), and the processing target range (3 × 3 range) shown in FIG. 4 is set. Smoothing is performed (step 62). R after smoothing _SM If (0,0), the smoothing process is
[0057]
[Expression 1]

It becomes.
[0058]
here,
h (-1, -1) = 1/16, h (-1,0) = 2/16, h (-1,1) = 1/16
h (0, -1) = 2/16, h (0,0) = 4/16, h (0,1) = 2/16
h (1, -1) = 1/16, h (1,0) = 2/16, h (1,1) = 1/16
It is. h (K, L) is a coefficient of a filter that performs smoothing. The coefficient of this filter can be arbitrarily set as long as the smoothing characteristic is shown, but in this embodiment, the coefficient is set to a coefficient that can be expressed by a power of 2 in the range of 3 × 3 in consideration of processing by hardware.
[0059]
Assuming that the element color density distribution of the original image is as shown in FIG. 7, the density change rate of the image after smoothing is generally reduced as shown in FIG. 8.
[0060]
Next, the pixel difference Diff before and after smoothing
Diff = Rin (0,0) -R _SM (0,0)… (5)
(Step 64).
[0061]
And the corrected difference Diff '
If Diff ≧ 0
Diff '＝ Diff… (6)
age,
If Diff '<0,
Diff '= 0 ... (7)
(Step 66). The reason why the Diff is corrected using the equations (6) and (7) is to limit the difference Diff to a positive value. By limiting Diff to a positive value in this way, it is possible to perform enhancement only in the direction of decreasing density (increasing value).
[0062]
When normal unsharp masking processing is performed, edges of characters and the like become sharp and moire occurs in the case of a halftone image. However, according to the unsharp masking process according to this embodiment, it is possible to suppress the occurrence of moire in the case of a halftone image. In other words, the change in the pattern in the halftone dot image due to the decrease in density is less noticeable in human sense than the change in the pattern due to the increase in density.
[0063]
FIG. 9 shows the element color density distribution before and after smoothing, and FIG. 10 shows the element color density distribution after correction.
[0064]
The final unsharp masking process adds the modified difference Diff 'to the original image,
R _USM (0,0) = R _in (0,0) + C _USM ・ Diff '… (8)
Sought by. In equation (8), C _USM Is a constant for controlling the strength of the unsharp masking process and is set in advance. In this embodiment, as an example, C _USM = 2. As a result, R _USM If overflow occurs at (0,0), R _USM A process for limiting the maximum value of (0,0) to 255 is provided. FIG. 11 shows the element color density distribution after the final unsharp masking process.
[0065]
Black enhancement processing
Next, a black enhancement processing control program executed by the black enhancement processing unit 20e will be described with reference to FIGS.
[0066]
The black enhancement processing includes (1) processing for extracting a black region and (2) processing for enhancing the extraction region.
[0067]
FIG. 12 is a diagram for explaining the concept of the black region to be extracted. A region surrounded by a diagonal line of the cube in FIG. 12 is a black region, and when viewed as an RGB space, both the luminance and the saturation are small regions. Considering the cut surface of the RGB space with a constant plane of B, when B is small, the black area exists at the upper left, and as B increases, the black area gradually decreases. Using the fact that the region where both luminance and saturation are small in the RGB space is a black region, calculating the luminance and saturation for the original image, calculating the black amount using the weighted average of luminance and saturation, Extract black areas. As shown in the conceptual diagram of FIG. 12, it can be confirmed that the black area existing as a triangle gradually decreases as B increases.
[0068]
FIG. 13 shows a flowchart for explaining a black enhancement processing control program executed by the black enhancement processing unit 20e. Here, the black enhancement processing target pixel is
{Rin '(0,0), Gin' (0,0), Bin '(0,0)}… (9)
And the pixel after the black enhancement process is
{R _BK (0,0), G _BK (0,0), B _BK (0,0)}… (10)
And
[0069]
As shown in FIG. 13, in the black enhancement processing in the present embodiment (the processing in step 50 of FIG. 3), the luminance I (0,0) and the saturation equivalent amount S (0) are calculated from the RGB values of the black enhancement processing target pixel. , 0)

(Steps 80 and 82). In equation (12), the saturation equivalent amount is calculated without performing division, so the burden on hardware can be reduced.
[0070]
Next, from the luminance I (0,0) and saturation equivalent S (0,0) calculated from the equations (11) and (12), the following equations (13) and (14):
Dr (0,0) = 255-I (0,0) (13)
Gr (0,0) = 255-S (0,0) (14)
Then, the darkness Dr (0,0) and the gray degree Gr (0,0) are calculated. Then, using the calculated darkness Dr (0,0) and gray degree Gr (0,0), the following equation (15):
BK (0,0) = C _BK {Α · Dr (0,0) + (1-α) · Gr (0,0)} (15)
0 ≦ α ≦ 1
From this, the black amount BK (0,0) is calculated (step 84). In formula (15), C _BK Is a constant for controlling the extraction of the black amount, and the larger the value, the more black amount is extracted. Α is a constant for controlling the relative weight between the darkness and the gray level in the black amount, and the larger the value, the more important the luminance (darkness) is calculated and the black amount is calculated. Both of these two constants are set in advance. In this embodiment, as an example, C _BK = 1 and α = 0.75.
[0071]
After calculating the black amount, the shadow portion is emphasized (step 86), and the RGB value of the processing end pixel is calculated by mixing the RGB value of the pixel with the shadow portion emphasized and the RGB value of the processing target pixel (step 86). 88). At this time, the mixing ratio is changed according to the extracted black amount. Since this processing is performed equally for RGB, R will be described as a representative in the following description.
[0072]
Pixel R with enhanced shadow area for R _SHD (0,0) is
R _SHD (0,0) = (2 ・ Rin '(0,0) / 255) ² ・ 128, 0 ≦ Rin '(0,0) ≦ 128 (16)
R _SHD (0,0) = Rin ′ (0,0), 128 ≦ Rin ′ (0,0) ≦ 255 (17)
Calculated by In the conversion according to the equations (16) and (17), the input value is converted and output using a γ function in 0 ≦ Rin ′ (0,0) ≦ 128, and 128 ≦ Rin ′ (0,0) ≦ 255. The input value is output as it is, and the shadow portion can be emphasized. FIG. 14 shows the conversion according to the equations (16) and (17). When implemented as hardware, Equation (16) is
R _SHD (0,0) = (Rin '(0,0)) ² / 128, 0 ≦ Rin '(0,0) ≦ 128 (18)
And approximate. This is because Equation (16) includes division by 255, which is not preferable because it imposes a burden on the hardware and is not included. The final processing pixel R of the black enhancement processing using the black amount of Equation (15) and the shadow enhancement pixel of Equation (16) and Equation (17). _BK (0,0) is
R _BK (0,0) = {BK (0,0) ・ R _SHD (0,0)} / 255+ {1-BK (0,0) / 255} · Rin '(0,0) ... (19)
Approximated
R _BK (0,0) = {BK (0,0) ・ R _SHD (0,0) + (255−BK (0,0)) ・ Rin '(0,0)} / 256… (20)
Calculate from Equation (20) calculates the processing end pixel by mixing the pixel with the shadow portion emphasized and the black enhancement processing target pixel. At this time, the mixing ratio is changed according to the extracted black amount. Yes. The reason why the approximate expression is used in the expression (20) is that the expression (19) includes division by 255, which is not preferable because it imposes a burden on hardware and is not included.
[0073]
Other embodiments
As shown in FIG. 16, the image processing according to the present invention is also applied to the scanner printer copy (SPC) having the image processing unit 20a comprising the image processing apparatus shown in FIG. 1, the scanner unit 10a, and the printer unit 30a. Can be applied. If the resolution conversion processing is performed in the hardware of the scanner unit 10a, the burden on other hardware (image processing unit 20a and printer unit 30a) can be reduced.
[0074]
Furthermore, as shown in FIG. 17, the image processing according to the present invention can be applied to image data generated from the application 10a.
[0075]
[Brief description of the drawings]
FIG. 1 is a functional block diagram showing an image processing system to which an image processing control method according to an embodiment of the present invention is applied.
FIG. 2 is a schematic block diagram illustrating a specific hardware configuration example of an image processing apparatus according to an embodiment of the present invention.
FIG. 3 is a flowchart for explaining a first embodiment of an image processing control program executed by the image processing apparatus;
FIG. 4 is a diagram for explaining neighboring pixels to be subjected to unsharp masking processing;
FIG. 5 is a diagram illustrating a state in which a processing target pixel is moved.
FIG. 6 is a flowchart for explaining an unsharp masking process control program executed by an unsharp masking processor 20d.
FIG. 7 is a diagram (1) for explaining the concept of unsharp masking processing;
FIG. 8 is a diagram (2) for explaining the concept of unsharp masking processing;
FIG. 9 is a diagram (3) for explaining the concept of unsharp masking processing;
FIG. 10 is a diagram (4) for explaining the concept of unsharp masking processing;
FIG. 11 is a diagram (5) for explaining the concept of unsharp masking processing;
FIG. 12 is a diagram for explaining the concept of a black region;
FIG. 13 is a flowchart for explaining a black enhancement processing control program executed by a black enhancement processing unit 20e.
FIG. 14 is a diagram illustrating a conversion curve for enhancing a shadow portion.
FIG. 15 is a flowchart for explaining a resolution conversion processing control program executed by a resolution conversion unit 20g.
FIG. 16 is a functional block diagram showing an image processing system to which an image processing control method according to another embodiment of the present invention is applied.
FIG. 17 is a functional block diagram showing an image processing system to which an image processing control method according to another embodiment of the present invention is applied.
FIG. 18 is a flowchart for explaining a second embodiment of the color correction processing control program executed by the image processing apparatus;
[Explanation of symbols]
10 Image input device
11a scanner
11b Digital still camera
11c video camera
12 Computer body
12a operating system
12b Display driver
12c Printer driver
12d application
13a Floppy disk drive
13b hard disk
13c CD-ROM drive
14a modem
15a keyboard
15b mouse
17a display
17b color printer
20 Image processing device
20a Color correction processor
20b Color converter
20c binarization part
20d Unsharp masking processing section
20e Black enhancement processing section
20f indicator
30 Image output device

Claims (14)

An image processing apparatus having a data generation unit and a printer unit,
Resolution conversion means for performing resolution conversion processing based on the input resolution of the data generation unit, the output resolution of the printer unit and the enlargement / reduction ratio;
Enhancement processing means for performing enhancement processing after resolution conversion processing;
With
The binarization process in the printer unit is an error diffusion process,
The enhancement processing means performs a sharpness enhancement process for enhancing the sharpness by correcting the element color component in a direction in which the density decreases for each element color component based on the image data.
Image processing device.   The image processing apparatus according to claim 1, wherein a data generation unit includes the resolution conversion unit.   The image processing apparatus according to claim 1, wherein the data generation unit includes a scanner unit.   The image processing apparatus according to claim 1, wherein the resolution conversion process includes a smoothing process. An image processing apparatus according to any one of claims 1 to 4, wherein
An image processing apparatus in which the enhancement processing means performs black enhancement processing based on image data. The image processing apparatus according to claim 1, wherein:
The sharpness enhancement process
Processing for obtaining a difference between before and after smoothing of the color image data in a predetermined area;
Processing to emphasize sharpness when the difference is positive;
An image processing apparatus. The image processing apparatus according to any one of claims 1, 5 and 6,
The sharpness enhancement process
An image processing apparatus including a process for adjusting a degree of enhancing sharpness. The image processing apparatus according to any one of claims 5 to 7,
An image processing apparatus in which the black enhancement processing is performed on a black region. The image processing apparatus according to claim 8,
An image processing apparatus in which the black area is obtained based on a luminance equivalent value and a saturation equivalent value. An image processing apparatus according to any one of claims 5 to 9,
An image processing apparatus, wherein the black enhancement process includes a process of enhancing a shadow portion. The image processing apparatus according to any one of claims 1 and 5 to 10,
An image processing apparatus that performs the black enhancement process after the sharpness enhancement process. The image processing apparatus according to any one of claims 1 and 5 to 11,
An image processing apparatus capable of selecting the sharpness enhancement process or the black enhancement process. An image processing method using a data generation unit and a printer unit,
A resolution conversion step for performing resolution conversion based on the input resolution of the data generation unit, the output resolution of the printer unit, and the enlargement / reduction ratio;
An emphasis processing step for performing emphasis processing after resolution conversion processing;
With
The binarization process in the printer unit is an error diffusion process,
The enhancement processing step performs a sharpness enhancement process for enhancing the sharpness by correcting the element color component in a direction in which the density decreases for each element color component based on the image data.
Image processing method. A program for causing a computer to execute image processing using a data generation unit and a printer unit,
Resolution conversion processing for performing resolution conversion based on the input resolution of the data generation unit, the output resolution of the printer unit, and the enlargement / reduction ratio;
Enhancement processing after resolution conversion processing,
Is a program for causing a computer to execute
The binarization process in the printer unit is an error diffusion process,
The enhancement process performs a sharpness enhancement process for enhancing the sharpness by correcting the element color component in a direction in which the density decreases for each element color component based on the image data.
program.

Images