JP4124576B2 - Threshold array determination method for gradation image creation and gradation image data creation apparatus - Google Patents

Description

このことは、作成途中スーパーセル閾値テンプレート３６Ｍに配置すべき閾値Ｔ、換言すれば、スーパーセル閾値テンプレート３６中に配置されている閾値Ｔ＝１、閾値Ｔ＝２、…閾値Ｔ＝２５５が、それぞれ５５個あることを意味している。
【００８２】
なお、この実施の形態においては、理解の容易化のために作成途中スーパーセル閾値テンプレート３６Ｍの閾値Ｔの配列がＴ＝１からＴ＝１２８まで決定されており、次に、５５個（１つ以上）の次階調の閾値Ｔ＝１２９の配置位置（同値１つ以上の閾値の配置位置）を決定する際の動作について説明する。
【００８３】
この場合、ステップＳ５（便宜的にＡ過程という。）において、網の形状を損なわないように、次階調の同値複数の閾値の配置位置の候補位置を複数箇所選択する。ここで、候補位置は、次に黒化する候補の画素位置に対応するので、黒化候補画素という。
【００８４】
この黒化候補画素の数をｍとするとき、ｍ＝Ｎｄｏｔ＋α、たとえば、Ｎｄｏｔ×２＝１１０個に選択する。余裕度αを大きくすれば、閾値配列の自由度が増加するが、網の黒化形状が、この例ではスクエアからくずれていく。
【００８５】
図４は、その黒化候補画素の選択手順例を示している。
【００８６】
すなわち、ステップＳ５−１では、図５に模式的に示すように、たとえば、大きさを±１で規格化した各網点５０の中心Ｏから未処理画素までの距離値、換言すれば、未だ閾値が配置されていない画素位置までの距離値を所望の形状であるスクエアに合致した次の（２）式の距離関数Ｄ（ｘ，ｙ）により求める。
【００８７】
Ｄ（ｘ，ｙ）＝１−（|ｘ|＋|ｙ|） …（２）
この模式的に描いた図５において、中心Ｏを含む四角形５１の内側までの閾値配列が決まっていた場合に、次に、四角形５２の辺の付近の未処理画素までの距離値を距離関数Ｄ（ｘ，ｙ）により求めることになる。
【００８８】
なお、距離関数Ｄ（ｘ，ｙ）は、黒化部分が円形で太る網点形状である場合には、次の（３）式で表されるものを用いればよい。
【００８９】
Ｄ（ｘ，ｙ）＝１−（ｘ²＋ｙ²） …（３）
距離関数Ｄ（ｘ，ｙ）は、いわゆるスポット関数に対応する。
【００９０】
次いで、ステップＳ５−２では、ステップＳ５−１で求めた距離値の中、最小値である最小値ｍｉｎＤ（ｘ，ｙ）を求める。
【００９１】
ステップＳ５−３では、最小値ｍｉｎＤ（ｘ，ｙ）の配置位置が未処理画素であるかどうか、換言すれば、閾値が決定されていないかどうかを確認し、未処理画素でなかった場合には、ステップＳ５−２にもどり、未処理画素であった場合には、ステップＳ５−４において黒化候補画素とする。
【００９２】
次いで、ステップＳ５−５においては、ステップＳ５−４までに決定した黒化候補画素数が黒化候補画素数ｍ＝Ｎｄｏｔ＋α（ここでは、ｍ＝１１０）に等しくなったかどうかを判定し、黒化候補画素数ｍに満たない場合には、黒化候補画素数ｍとなるまでステップＳ５−２〜ステップＳ５−５の処理を繰り返す。
【００９３】
黒化候補画素数ｍが、黒化候補画素数ｍ＝Ｎｄｏｔ＋αに合致したとき、黒化候補画素選択部４１は、黒化候補画素数ｍの各画素位置を黒化画素決定部４６に転送通知する。
【００９４】
次に、以下に説明するステップＳ６〜ステップＳ９の処理（便宜的にＢ過程という。）を繰り返し行うことにより複数の黒化候補画素（複数箇所の候補の閾値）の配列位置を決定する。
【００９５】
すなわち、ステップＳ６の処理において、既に決まっている閾値配列が格納されている作成途中スーパーセル閾値テンプレート３６Ｍにより階調画像である２値網点画像データＨを比較部３２により作成する。２値網点画像データＨを作成する画像データＧの値は、Ｇ＝１２８とされる。すなわち、閾値Ｔ＝１２９の配置位置を決定する場合に、既に決まっている閾値Ｔ＝１〜１２８の閾値配列を表す２値網点画像データＨを作成するときには、画像データ発生部３０から画像データＧの値として、一定値Ｇ＝１２８がスーパーセル閾値サイズ分比較部３２へ供給される。
【００９６】
図６は、画像データＧがＧ＝１２８であるとき、作成途中スーパーセル閾値テンプレート３６Ｍを用いて比較部３２により作成された２値網点画像データＨにより表される網点画像を模式的に示している。
【００９７】
ここでは、網パーセントが５０％の平網となっており、比較部３２により得られた１個のスーパーセルに係る１１９画素×１１９画素分の２値網点画像データＨによる網点画像（ビットパターンと考えることができる。）を示している。ここで、網点の基本周波数は、ほぼスクリーン線数に等しく、６．８９（ｃ／ｍｍ：サイクル／ｍｍ）と考えることができる。
【００９８】
この図６から２値網点画像データＨは、ｘｙ平面上で定義される座標上のデータ、すなわち位置空間上のデータ（ｚ軸のデータと考えることができる。）が、値０（非黒化）または値１（黒化）をとるデータであることが理解される。
【００９９】
図６において、例として描いた１個の網点５０内には、約１０９（１４５² ／１３．９² ）個の画素が含まれる。なお、ステップＳ５の処理において、黒化候補画素選択部４１において選択決定し、黒化画素決定部４６に格納されている黒化候補画素数ｍ（ｍ＝１１０個）の画素位置は、図６中、非黒化画素となっているいずれかの位置である。
【０１００】
次に、ステップＳ７（第１の過程）では、２値網点画像データＨの低周波成分を特別な処理により低周波成分抽出部４５により抽出する。そのため、このステップＳ７では、まず、２値網点画像データＨを、二次元のＦＦＴ４０により高速フーリエ変換して、周波数空間上の情報信号であるデータＤ１に変換する。
【０１０１】
図７は、図６に示す位置空間上の２値網点画像データＨに対応する、高速フーリエ変換後の周波数空間上のデータＤ１のＦＦＴパワー図を示している。ｘ軸とｙ軸は、周波数（ｃ／ｍｍ）を示し、ｚ軸はパワーを示している。
【０１０２】
この図７の周波数空間上のデータＤ１において、中心座標（ｘ，ｙ）＝（０，０）における値が約０．５のパワーＰ１は、平網と仮定したときの網パーセントの５０％に対応する基本成分であり、ノイズ（雑音）ではない。また、ｘｙ平面上、中心座標（ｘ，ｙ）＝（０，０）から各４５°方向上の座標（ｘ，ｙ）＝（５，５）、（−５，５）、（−５，−５）、（５，−５）付近の座標位置に存在する値０．２程度のパワーＰ２〜Ｐ５も、網の基本周波数６．８９（ｃ／ｍｍ）に対応するパワーであり、ノイズではない。なお、例えば、パワーＰ２が存在する正確なｘ、ｙ座標は、値５ではなく、６．８９÷√２＝４．８７として計算することができる。
【０１０３】
モアレ縞は、網の周波数以下の周波数で発生する干渉縞であることを考えると、これら４点の座標（ｘ，ｙ）＝（５，５）、（−５，５）、（−５，−５）、（５，−５）で囲まれた領域Ｑ（図５のハッチング領域も参照）内に存在する周波数成分がモアレ縞と関係するノイズ成分（低周波成分）であることが理解される。
【０１０４】
図９は、領域Ｑを含む部分の図７のＦＦＴパワー図の拡大図である。領域Ｑ内に小さいながらも凹凸、すなわちパワー成分が存在することが分かる。
【０１０５】
次に、この領域Ｑ以外の高周波成分を除去するために、領域Ｑに対応する遮断周波数を有する低域通過フィルタ４２を作用させ、領域Ｑ内の低周波成分を含むデータＤ２を抽出する。換言すれば、周波数空間上のデータＤ１から網点の基本周波数成分より低周波の低周波成分データＤ２を抽出する。なお、このとき、直流成分であるパワーＰ１も除去しておく。この直流成分の阻止をも考慮した場合に、低域通過フィルタ４２は正確には帯域通過フィルタであるが、低周波ノイズ成分を含むデータを通過させるという意味で便宜上低域通過フィルタといっている。
【０１０６】
実際上、モアレ縞は人間が知覚するものであるから、ＦＦＴ４０により２値網点画像データＨを高速フーリエ変換した後のデータＤ１中、領域Ｑ以外の高周波成分を低域通過フィルタ４２により除去する際に、図１０に示す人間の視覚特性６５により重み付けした後、低域通過フィルタ４２をかけて低周波成分を抽出するようにしている。図１０に示すように、人間の視覚特性６５は、周波数０．８（ｃ／ｍｍ）近傍で最大感度を有する特性である。
【０１０７】
次いで、ＩＦＦＴ４４は、低域通過フィルタ４２により抽出された低周波成分データＳ２を逆フーリエ変換して位置空間（実空間）上の低周波成分データＬにする。
【０１０８】
図１１は、位置空間上における１１９画素×１１９画素領域上に鳥瞰図的に表した低周波成分データＬを立体的に示している。すなわち、もとの画像上で低周波の濃度のうねりが３次元図形上の山や谷で抽出されていることが理解される。
【０１０９】
なお、この図１１においては、図１０に示す人間の視覚特性（人間の視覚周波数特性）６５に基づく重み付けをかけていることから、ＩＦＦＴ４４によるフーリエ逆変換後の低周波成分データＬが人間の目に視認しやすいように、換言すれば、コンピュータによる大きさ（強さ）の判別がし易くなるように重み付けられた図形となっている。
【０１１０】
人間の視覚周波数特性のモデルについては、著者J.Sullivan, L.Ray,and R.Millerによる文献「Design of minimum visual modulation halftone patterns」IEEE Trans. Syst. Man Cybern., vol21,No.1,33-38(1991)にも詳しく述べられている。
【０１１１】
また、人間の視覚特性をかけて低周波成分を抽出する方式においても、上記説明した、周波数空間上のフィルタリング計算だけでなく、実空間上のコンボリューション演算でも抽出することができる。
【０１１２】
この低周波成分データＬは、低周波成分抽出部４５から黒化画素決定部４６に供給される。
【０１１３】
そこで、ステップＳ８（第２の過程）において、黒化画素決定部４６は、まず、この１１９画素×１１９画素の低周波成分データＬと、図６に示した１１９画素×１１９画素の２値網点画像データＨとを対比し、黒化候補画素数ｍ＝１１０の黒化候補画素位置に対応する各非黒化画素位置における低周波成分データＬを図１１から算出する。
【０１１４】
次いで、黒化画素決定部４６は、ステップＳ９（第３の過程）において、ステップＳ８で算出した各非黒化画素位置における低周波成分データＬの中、最も、値の小さい（低周波成分データのパワー値が弱い、換言すれば、低周波成分強度の最も弱い）黒化候補画素の位置を次に黒化すべき画素（黒化画素）に決定する。
【０１１５】
この場合、この次の黒化画素位置を次の閾値Ｔ＝１２９の配列位置として、作成途中スーパーセル閾値テンプレート３６Ｍ中の閾値位置のメモリアドレスに閾値Ｔ＝１２９を格納する。なお、処理を早くするため、ステップＳ９における黒化画素の決定は１個ではなく小さい方から複数個を決めるようにしてもよい。
【０１１６】
次に、ステップＳ１０において、黒化画素決定部４６は、１階調あたりの画素数Ｎｄｏｔ＝５５個分の閾値Ｔ＝１２９の、作成途中スーパーセル閾値テンプレート３６Ｍ中での配置位置が決定したかどうかを確認し、決定していない場合には、ステップＳ６からステップＳ９（第１の過程、第２の過程、第３の過程）までの処理を決定するまで繰り返す。なお、繰り返す際のステップＳ６の処理において、画像データ発生部３０から出力される画像データＧは、黒化画素決定部４６からの黒化画素決定通知に基づき、次の階調の画像データＧ＝１２９とされる。
【０１１７】
さらに、ステップＳ１０における判断が成立したとき、すなわち、１階調あたりの画素数Ｎｄｏｔの全ての黒化画素に対応する閾値位置が決定したとき、ステップＳ１１において、黒化画素決定部４６は、閾値Ｔが最大値である閾値Ｔ＝２５５までの全ての閾値配列が決定したかどうかを確認し、閾値配列が決定していない場合には、ステップＳ５からステップＳ１０の処理を繰り返して閾値Ｔ＝２５５までの全ての閾値配列を決定して処理を終了する。
【０１１８】
なお、全ての閾値配列が決定した作成途中スーパーセル閾値テンプレート３６Ｍは、スーパーセル閾値テンプレート３６とされ、その閾値テンプレート３６のデータが記憶媒体４９に記憶され、この記憶媒体４９から図１に示した製版システム１０中のスーパーセル閾値テンプレート３６にコピーされる。
【０１１９】
以下、同様にして、ステップＳ１において新たなパラメータ（線数、角度、出力解像度、網形状等）を設定することにより、このパラメータに対応したスーパーセル閾値テンプレート３６の閾値配列を略自動的に決定することができる。
【０１２０】
なお、上述した実施の形態においては、２値網点画像データＨを対象としているが、この発明は２値網点画像データＨに限らず、出力値が「０，１，２，３」の値をとる４値、８値等の多値網点画像データにも適用することができる。
【０１２１】
また、上述した実施の形態においては、図６に示した網点５０による階調画像作成用の閾値配列の決定について説明しているが、この発明は、網点画像作成用の閾値テンプレートの作成に限らず、Ｎ×Ｎ画素を階調再現の１つの単位として考え、それに対応する階調画像作成用のＮ×Ｎ個の閾値テンプレート（ディザマトリクス）の閾値配列にも適用することができる。
【０１２２】
このディザマトリクスでは、画素の集合密度（周波数）を階調に応じて変化させるＦＭ（周波数変調）スクリーンにも適用することができる。
【０１２３】
図１２は、ディザマトリクスの閾値配列を決定するための手順を示すフロー図である。
【０１２４】
まず、ステップＳ２１では、入力パラメータを設定する。ここで、入力パラメータは、出力解像度（画素／ｍｍ）、ＦＭスクリーンにおける１画素の大きさ、ディザマトリクスの大きさ、例えばＮ画素×Ｎ画素（上述したように、設定すべき閾値Ｔは１からＮ²個となる。）である。
【０１２５】
次いで、ステップＳ２２では、閾値Ｔ＝１の初期位置をディザマトリクス中の適当な画素位置に決める。
【０１２６】
次いで、ステップＳ２３では、閾値Ｔ＝１のみが決定されたディザマトリクスと画素値が全て１であるＮ×Ｎ画素の画像データと比較して、２値画像データを比較部３２により作成する。
【０１２７】
次いで、ステップＳ２４では、ステップＳ７で説明したのと同様に、ステップＳ２３で作成した２値画像データに対して低周波成分データの抽出処理を行う（第１の過程）。
【０１２８】
次いで、ステップＳ２５では、次に黒化すべき画素の位置、換言すれば、次の閾値Ｔ＝２を入れるべきディザマトリクス中の位置を決定する。このステップＳ５の処理では、低周波成分データの最も小さい（弱い）位置が次に黒化すべき画素位置であると決定すればよい（第２の過程）。
【０１２９】
次に、ステップＳ２６では、Ｎ²個の全ての閾値配置位置が決定しているかどうかを判定し、全ての閾値の配置位置が決定するまで、この場合、次の閾値Ｔ＝２の配列位置から最終閾値Ｔ＝Ｎ²までステップＳ２３〜ステップＳ２５の処理を繰り返す。
【０１３０】
閾値を実際に使用する場合は、出力機に合わせた階調数に規格化して使用する。たとえば、出力機の階調数が２５６階調であれば、元の閾値をＴとすると、新しい閾値は、閾値＝Ｔ×（２５５／Ｎ²）として使用する。
【０１３１】
このように、１〜Ｎ²の閾値配列を決めた後に、必要階調数の閾値配列を求める方法は、前述の網点画像作成用閾値データを作成する際にも適用することができることはいうまでもない。
【０１３２】
このようにして、ディザマトリクスの閾値配列を決定することができる。閾値配列の決定したディザマトリクスは、記憶媒体４９に格納することができる。
【０１３３】
なお、上述した図３のフロー図に基づく閾値配列の決定および図１２のフロー図に基づく閾値配列の決定の際には、閾値Ｔ＝１から網％では０％（小さい方）から昇順で順次黒化画素（閾値配列）を決定するようにしているが、この閾値配列の決定は、閾値Ｔの最大値から網％では１００％（大きい方）から降順で順次決定するようにしてもよい。
【０１３４】
図２例の閾値配列作成装置１８において、黒化画素決定部４６および黒化候補画素選択部４１を、それぞれ白化画素決定部および白化候補画素選択部に代替することで、降順に閾値の配置位置を決める方式に対応することが可能である。
【０１３５】
この場合、図３のフローチャート中、ステップＳ９（第３の過程）では、白化画素決定部（図４中の黒化画素決定部４６に相当する。）が、ステップＳ８で算出した各非白化画素位置における低周波成分データＬの中、最も、値の大きい（低周波成分データのパワー値が強い、換言すれば、低周波成分強度の最も強い）白化候補画素の位置を次に白化すべき画素（白化画素）に決定するようにすればよい。また、図１２のフローチャート中、ステップＳ２５の処理では、低周波成分データの最も大きい（強い）位置が次に白化すべき画素位置であると決定すればよい（第２の過程）。
【０１３６】
また、閾値の配置位置を決める場合に、ある特定の網％におけるドットの配置位置（２値パターン、ドットパターン、網点形状、白黒のパターン）のみが、特別の方法によって最適なドット配置位置として選ばれているような場合にも以下のように対応することができる。
【０１３７】
すなわち、配置位置が決定している閾値Ｔｆｉｘに対して階調の高い方の次階調の閾値Ｔｈの配置位置と階調の低い方の次階調の閾値Ｔｌの配置位置を決定する際、階調の高い方の次階調の閾値Ｔｈの配置位置を決定する場合には、前記ドットパターン（閾値配列）の閾値Ｔを便宜的に全て０値として、昇順に閾値Ｔｈ＋１以降の閾値の配置位置を決定し、階調の低い方の次階調の閾値Ｔｌの配置位置を決定する場合には、前記ドットパターン（閾値配列）の閾値Ｔを便宜的に全て最大値、たとえば、Ｔ＝Ｎ²として、降順に閾値Ｔｌ−１以降の閾値の配置位置を決定すればよい。
【０１３８】
図１３は、ある階調での閾値Ｔｆｉｘにおける配置位置（白黒のパターン、ドットパターン）が決定しているとき、階調の高い方の閾値Ｔｈと階調の低い方の閾値Ｔｌの配置位置をそれぞれ決定する手順を示している。
【０１３９】
この図１３に示すフローチャートにおけるステップＳ３１〜Ｓ４１の処理は、図３に示したフローチャートにおけるステップＳ１〜Ｓ１１の処理内容と同様であり、また、図１３に示すフローチャートにおけるステップＳ４５〜Ｓ５１の処理も同様にステップＳ５〜Ｓ１１の処理内容と同様であるので、その詳細な説明を省略する。
【０１４０】
この図１３に示すフローチャートにおいて、階調の高い方の次階調の閾値Ｔｈを決定する場合には、上述したように、ある閾値Ｔｆｉｘのドットパターンで黒化されている画素は、閾値Ｔに便宜的に０（常に黒化される画素）としてしまい、ステップＳ３５における黒化候補画素として選択されないようにして、初期値としての次階調の閾値Ｔｈ＝Ｔｆｉｘ＋１以上の閾値Ｔの配置位置を順次決定する。なお、ステップＳ３４Ａは、初期値の閾値Ｔｈ＝Ｔｆｉｘ＋１の設定を示し、ステップＳ４２は、閾値Ｔの高い方の次階調の閾値Ｔｈ（Ｔｈ＝Ｔｈ＋１）への閾値の更新処理を示している。
【０１４１】
同様に、階調の低い方の次階調の閾値Ｔｌの配置位置を決定する場合にも、上述したように、ある閾値Ｔｆｉｘのドットパターンで白化されている画素は、閾値Ｔを便宜的に、たとえば２５５（常に白化される画素）としてしまい、白化候補画素として選択されないようにしてＴｆｉｘ−１以下の閾値Ｔの配置位置を順次決定する。なお、ステップＳ３４Ｂは、初期値の閾値Ｔｌ＝Ｔｆｉｘ−１の設定そ示し、ステップＳ５２は、閾値Ｔの低い方の次階調の閾値Ｔｌ（Ｔｌ＝Ｔｌ−１）への閾値の更新処理を示している。
【０１４２】
ここで、ステップＳ４５においては、ステップＳ５と同様に、網の形状を損なわないように、低い方の次階調の同値複数の閾値Ｔｌの配置位置の候補位置を複数箇所選択する。ここで、候補位置は、次に白化する候補の画素位置に対応するので、白化候補画素という。
【０１４３】
また、次階調の閾値ＴｈとＴｌの配置位置を決定する際、１階調ずつ同時に決定してもよく、高い方の閾値Ｔｈの配置位置を全て決めた後、低い方の閾値Ｔｌの配置位置を決めるように、独立に決定してもよい。
【０１４４】
この場合、複数の異なる網％に対応する複数の異なる階調での閾値のそれぞれから昇順および降順に閾値の配置位置を決定するように構成を変更することも可能である。
【０１４５】
図１４は、２箇所の異なるある階調までの閾値Ｔｆｉｘ１、Ｔｆｉｘ２（Ｔｆｉｘ１＜Ｔｆｉｘ２）の配置位置（白黒のパターン、ドットパターン）が決定しているとき、初期値の閾値をそれぞれステップＳ６４Ａ、Ｓ６４Ｂに示すように、閾値Ｔｈ＝Ｔｆｉｘ１＋１、Ｔｌ＝Ｔｆｉｘ２−１とし、閾値Ｔｆｉｘ１と閾値Ｔｆｉｘ２の間の閾値の配置位置を決定する手順を示している。
【０１４６】
この図１４に示すフローチャートにおけるステップＳ６１〜Ｓ６９、Ｓ８０、Ｓ８１の処理は、図３に示したフローチャートにおけるステップＳ１〜Ｓ１１の処理内容と同様であり、また、図１４に示すフローチャートにおけるステップＳ７５〜Ｓ８１の処理も同様にステップＳ５〜Ｓ１１の処理と同様であるので、その詳細な説明を省略する。
【０１４７】
この図１４に示すフローチャートにおいては、図１３例のように高い方と低い方の次階調の閾値ＴｈとＴｌの配置位置を独立に計算するのではなく、平均の値（Ｔｆｉｘ１＋Ｔｆｉｘ２）／２で閾値の配置位置が一致するように、高い方の次階調の閾値Ｔｈと低い方の次階調の閾値Ｔｌの増加（Ｔｈ＝Ｔｈ＋１）と減少（Ｔｌ＝Ｔｌ−１）を同じタイミングで行い、高い方と低い方の次階調の閾値Ｔｈ、Ｔｌ側で１画素ずつ閾値の配置位置を決定する。
【０１４８】
なお、ステップＳ６５、Ｓ７５の候補画素の選択の際には、高い方と低い方の次階調の閾値Ｔｈ、Ｔｌ側のどちらにも閾値の配置位置が決まっていない画素の中から候補画素を選択する。この図１４例では、高い方の次階調の閾値Ｔｈを低い方の次階調の閾値Ｔｌより先に処理しているが、低い方の次階調の閾値Ｔｌの配置位置を先に処理してもよい。
【０１４９】
このようにすれば、閾値Ｔｆｉｘ１、Ｔｆｉｘ２に対応する特定の網％での好ましいドットパターンを保持したまま、閾値Ｔｆｉｘ１、Ｔｆｉｘ２の間もモアレの発生を抑制した閾値配置を決定することができる。
【０１５０】
また、この方式で決定した閾値配列として、閾値Ｔｆｉｘ１＝０％（全て白）、閾値Ｔｆｉｘ２＝１００％（全て黒）と設定し、網％で０％（＝Ｔｆｉｘ１）〜５０％は昇順に、網％で１００％（＝Ｔｆｉｘ２）〜５０％は降順に閾値配置を決定する方式も当然に含まれる。
【０１５１】
ある網％、たとえば、３０％、５０％、７０％で２値パターンを決定し、その前後に閾値配列を決定する場合について、具体的に説明する。
【０１５２】
この場合、０〜３０％の閾値は、３０％のドットパターンを基に、図３の手順に対応して降順に０％までの閾値の配置位置を決定する。３０〜５０％の閾値は、図１４の手順に従い、３０〜４０％までの閾値は、３０％のドットパターンを基に３０％から昇順に配置位置を決定し、４０〜５０％までの閾値は、５０％のドットパターンを基に５０％から降順に配置位置を決定する。
【０１５３】
さらに、５０〜７０％までの閾値範囲では、５０〜６０％の閾値の配置位置を５０％のドットパターンを基に５０％から昇順に決定し、６０〜７０％の閾値の配置位置は７０％のドットパターンを基に７０％から降順に閾値の配置位置を決定する。
【０１５４】
さらに、７０〜１００％の閾値は、７０％の閾値を基に、図３の手順により昇順で１００％までの配置位置を決定する。
【０１５５】
図１５は、網点ではなく、ディザマトリクスの閾値配列において、ある閾値Ｔｆｉｘにおける配置位置（白黒のパターン、ドットパターン）が決定しているとき、階調の高い方の閾値Ｔｈと階調の低い方の閾値Ｔｌの配置位置を決定する手順を示している。
【０１５６】
この図１５に示すフローチャートにおけるステップＳ１２１、Ｓ１２３〜Ｓ１２６の処理は、図１２に示したフローチャートにおけるステップＳ２１、Ｓ２３〜Ｓ２６の処理内容と同様であり、また、図１５に示すフローチャートにおけるステップＳ２２３〜Ｓ２２６の処理も同様にステップＳ２３〜Ｓ２６の処理内容と同様であるので、その詳細な説明を省略する。
【０１５７】
ここで、ステップＳ１２２Ａの処理では、初期値として閾値Ｔｈ＝Ｔｆｉｘ＋１が設定され、ステップＳ１２７で、高い方の次階調の閾値Ｔｈ＝Ｔｈ＋１に更新される。
【０１５８】
また、ステップＳ１２２Ｂの処理では初期値として閾値Ｔｆｉｘ−１が設定され、ステップＳ２２７で、低い方の次階調の閾値Ｔｌ＝Ｔｌ−１に更新される。
【０１５９】
このようにして、ある階調の閾値Ｔ＝Ｔｆｉｘでのドットパターンの決定しているディザマトリクスの全体の閾値配列を決定することができる。この閾値配列は、予め決められたＴｆｉｘでのドットパターンを保持しつつ、その近傍でモアレの発生を抑えることの可能な閾値配列となる。閾値配列の決定したディザマトリクスは、記憶媒体４９に格納することができる。
【０１６０】
図１６は、網点ではなく、ディザマトリクスの閾値配列において、複数の異なるある階調までの閾値Ｔｆｉｘ１、Ｔｆｉｘ２（Ｔｆｉｘ１＜Ｔｆｉｘ２）における配置位置（白黒のパターン、ドットパターン）が決定しているとき、閾値Ｔｆｉｘ１と閾値Ｔｆｉｘ２との間の閾値Ｔの配置位置を決定する手順を示している。
【０１６１】
この図１６に示すフローチャートにおけるステップＳ３２１、Ｓ３２３〜Ｓ３２５の処理は、図１２に示したフローチャートにおけるステップＳ２１、Ｓ２３〜Ｓ２５の処理内容と同様であり、また、図１６に示すフローチャートにおけるステップＳ４２３〜Ｓ４２６の処理も同様にステップＳ２３〜Ｓ２６の処理内容と同様であるので、その詳細な説明を省略する。
【０１６２】
ここで、ステップＳ３２２Ａ、Ｓ３２２Ｂの処理では、初期値としてそれぞれ閾値Ｔｈ＝Ｔｆｉｘ１＋１、Ｔｈ＝Ｔｆｉｘ２−１が設定され、ステップＳ４２７で、高い方の次階調の閾値Ｔｈ＝Ｔｈ＋１と低い方の次階調Ｔｌ＝Ｔｌ−１に更新される。
【０１６３】
ここで、初期値としての閾値Ｔｈ＝Ｔｆｉｘ１＋１と更新された閾値Ｔｈ＝Ｔｈ＋１は、ステップＳ３２３〜Ｓ３２５の高い方の閾値Ｔｈの配置位置の決定処理に使用され、初期値としての閾値Ｔｌ＝Ｔｆｉｘ２−１と更新された閾値Ｔｌ＝Ｔｌ−１は、ステップＳ４２３〜Ｓ４２５の低い方の閾値Ｔｌの配置位置の決定処理に使用される。
【０１６４】
なお、低い方の閾値Ｔｆｉｘ１以下の閾値の配置位置については、図１５に示したステップＳ１２２Ｂ、Ｓ２２３〜Ｓ２２７の手順を使用して決定することができ、高い方の閾値Ｔｆｉｘ２以上の閾値の配置位置については、図１５に示したステップＳ１２２Ａ、Ｓ１２３〜Ｓ１２７の手順を使用して決定することができる。
【０１６５】
このようにして、複数の異なるある階調の閾値Ｔ＝Ｔｆｉｘ１、Ｔｆｉｘ２でのドットパターンの決定しているディザマトリクスの全体の閾値配列を決定することができる。このようにすれば、閾値Ｔｆｉｘ１、Ｔｆｉｘ２に対応する特定の網％での好ましいドットパターンを保持したまま、閾値Ｔｆｉｘ１、Ｔｆｉｘ２の間もモアレの発生を抑制した閾値配置を決定することができる。閾値配列の決定したディザマトリクスは、記憶媒体４９に格納することができる。
【０１６６】
この場合においても、この方式で決定した閾値配列として、閾値Ｔｆｉｘ１＝０％（全て白）、閾値Ｔｆｉｘ２＝１００％（全て黒）と設定し、網％で０％（＝Ｔｆｉｘ１）〜５０％は昇順に、網％で１００％（＝Ｔｆｉｘ２）〜５０％は降順に閾値配置を決定する方式も当然に含まれる。
【０１６７】
なお、この発明は、上述した実施の形態に限らず、この発明の要旨を逸脱することなく、種々の構成を採りうることはもちろんである。
【０１６８】
【発明の効果】
以上説明したように、この発明によれば、周期的な模様やモアレの発生のきわめて少ない閾値配列を決定することができる。
【０１６９】
また、この発明によれば、出力される階調画像データにより形成される階調画像上でモアレ等の低周波成分の発生を抑制することができる。
【図面の簡単な説明】
【図１】この発明の一実施の形態に係るスーパーセル閾値テンプレートが適用された製版システムの構成を示すブロック図である。
【図２】閾値作成装置の構成を示すブロック図である。
【図３】閾値配列の決定手順を示すフロー図である。
【図４】図３例の閾値配列決定手順中、黒化候補画素の選択処理の詳細な処理手順を示すフロー図である。
【図５】距離関数の説明に供される線図である。
【図６】閾値配列決定前の２値網点画像データにより表される位置空間上の画像を示す線図である。
【図７】閾値配列決定前の２値網点画像データを高速フーリエ変換したときのＦＦＴパワーを示す線図である。
【図８】抽出しようとする低周波成分の領域の説明に供される線図である。
【図９】抽出しようとする低周波成分の領域を拡大したＦＦＴパワーを示す線図である。
【図１０】人間の視覚特性の説明に供される特性図である。
【図１１】抽出した低周波成分を逆フーリエ変換したときの位置空間上での低周波成分の形状を示す線図である。
【図１２】ディザマトリクスの閾値配列の決定手順説明を示すフロー図である。
【図１３】ある階調での閾値のドットパターンが決定している場合の閾値配列の決定手順を示すフロー図である。
【図１４】２箇所の異なる階調での閾値のドットパターンが決定している場合の閾値配列の決定手順を示すフロー図である。
【図１５】ある階調での閾値でのドットパターンが決定している場合のディザマトリクスの閾値配列の決定手順を示すフロー図である。
【図１６】２箇所の異なる階調での閾値のドットパターンが決定している場合のディザマトリクスの閾値配列の決定手順を示すフロー図である。
【符号の説明】
１０…製版システム １２…原稿画像
１４…画像入力部 １６…画像処理部
１８…階調画像作成用閾値配列作成装置
２０…２値網点画像データ作成部（階調画像データ作成装置）
３２…比較部 ３４…アドレス計算部
３６…スーパセル閾値テンプレート（網点閾値データ）
３６Ｍ…作成途中スーパーセル閾値テンプレート
３７…パラメータ入力部 ３８…網属性入力部
４０…ＦＦＴ ４１…黒化候補画素選択部
４２…ＬＰＦ ４４…ＩＦＦＴ
４６…黒化画素決定部 ４９…記憶媒体
５０…網点 ＡＤ…アドレス
ＤＡ、Ｇ…画像データ Ｆ…フイルム
Ｈ…修正後の網点画像データ Ｌ…低周波成分データ
Ｍ…感光材料 ＰＰ…刷版
ＰＭ…印刷物 Ｓ１…周波数空間上のデータ
Ｓ２…低周波成分データ Ｔ…閾値データ（閾値）[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a gradation image creation threshold array determination method and a gradation image data creation apparatus that are suitable for printing field devices such as a color scanner, an image setter, a CTP device, a CTC device, and a DDCP.
[0002]
[Prior art]
In a halftone image output device such as an image setter that forms a halftone image consisting of binary values (for example, a blackened portion and a non-blackened portion by turning on / off a laser beam) on photographic paper or film, the output resolution and screen It has been pointed out that moire fringes caused by interference with the number of lines may occur on the output image (see Japanese Patent Application Laid-Open No. 8-317212).
[0003]
Here, the output resolution is the resolution of the image output apparatus, and is defined by dpi (dot per inch), pixels / inch (agreeing with dpi), pixels / mm, or the like. The number of screen lines is defined by lines / inch (convertible to lines / mm), which is the number of lines of halftone dots (also referred to as halftone cells) included per unit length (1 inch), and lpi (Line per inch), number of lines, screen frequency or halftone frequency.
[0004]
Moire fringes generated by interference between the output resolution and the number of screen lines are periodic patterns of halftone dots, that is, periodic interference fringes generated between the halftone dot pitch and the scanning line pitch. This moire fringe becomes a low-frequency noise component and degrades the image quality.
[0005]
The inventor of this application has proposed a technique for reducing this low-frequency noise component, as disclosed in Japanese Patent Application Laid-Open No. 8-317212 (referred to as the first technique), Japanese Patent Application Laid-Open No. 9-200518 (referred to as the second technique), and the like. This is proposed in Japanese Patent Application Laid-Open No. 11-112814 (referred to as the third technique).
[0006]
In the first technique, a threshold arrangement position in a threshold array (also referred to as a threshold template or a threshold matrix) used when generating binary halftone dot image data is devised, and blackening is performed in the threshold array. This is intended to reduce the occurrence of low-frequency noise components by aligning the number of pixels (non-blackened) as much as possible.
[0007]
In the second technique, random numbers are added when the thresholds are arranged in the threshold array in the first technique to further reduce the generation of low-frequency noise components.
[0008]
Furthermore, the third technique compares the median value within a predetermined threshold correction range with the threshold value before correction among the existing threshold values before correction in the threshold value array, and after converting it to halftone image data, The data is converted into data on the frequency space, and data including a low frequency noise component lower than the fundamental frequency component of the halftone dot is extracted from the data, and converted into image data on the real space. The data in the real space after the conversion and the threshold value before the correction are observed within the predetermined threshold correction range, and the pair of threshold values to be replaced are set under a certain condition (basically in the real space). This is a technique for obtaining a corrected threshold value array by selecting and replacing the threshold value pair at a position where a pixel having the maximum value and the minimum value of image data is generated.
[0009]
According to the third technique, the corrected threshold array itself is an array in which low-frequency noise components are unlikely to occur.
[0010]
In the first and second techniques, a certain low frequency component generation reduction degree is achieved. However, for example, when a higher quality image is handled, further improvement of the low frequency component generation reduction degree is required. Yes.
[0011]
In the third technique, the generation of low-frequency noise components can be considerably reduced. However, since this technique is a technique for correcting a threshold value that has already been created, the degree of freedom of correction is limited, and the effect of noise reduction. There may be cases where this is not fully achieved.
[0012]
[Problems to be solved by the invention]
The present invention has been made in connection with such problems and techniques, and does not modify the existing threshold arrangement, but is unlikely to generate low-frequency noise components. In other words, a gradation image is output. It is an object of the present invention to provide a threshold value array determining method for creating a gradation image that makes it possible to create a threshold value array from which moire is unlikely to occur from the beginning.
[0013]
It is another object of the present invention to provide a gradation image data creation device that can suppress the generation of low frequency components such as moire on a gradation image formed by output gradation image data. And
[0014]
[Means for Solving the Problems]
The gradation image creating threshold value array determining method according to the present invention has one or more threshold values having the same value of the next gradation when the threshold arrangement positions from the smaller threshold value to a certain gradation value are determined in the threshold value array. When determining the arrangement position of the next gradation, the process A for determining one or more candidate positions of one or more threshold values having the same value of the next gradation, and determining the arrangement position of the threshold value of the next gradation among the candidate positions A first step of extracting a low frequency component of image data obtained based on a threshold arrangement in which the arrangement positions of the thresholds up to a certain gradation are determined; A second step of determining the low-frequency component intensity at each candidate position of the one or more locations, and a third process of determining a candidate position having the weakest low-frequency component intensity as an arrangement position of the threshold value of the next tone And the third process from the first process to the third process. All positions equivalence one or more threshold gradation is characterized repeated to perform up to determine (the invention according to claim 1).
[0015]
The alphabets “A” and “B” in the “A process” and “B process” are merely used for the convenience of understanding the present invention. The same applies to the “C process” used in the following description.
[0016]
  Claims5, 6, 7, 8The described invention will be better understood, for example, by reference to FIGS. 13-16, respectively.
[0017]
According to the present invention, the third process of determining the candidate position having the weakest low frequency component intensity as the arrangement position of the threshold value of the next tone is a processing process in the real space, and is accurately and accurately viewed. The location of the next threshold can be determined.
[0018]
In this way, the threshold value array used for creating the gradation image becomes a threshold value array that suppresses unnecessary low-frequency components when the gradation image is created.
[0019]
In the first aspect of the present invention, the threshold values are determined in ascending order from the smaller side (the smallest value in the case of the smallest), but the third process is a candidate position where the obtained low frequency component intensity is strongest. Can be determined in descending order from the side with the larger threshold value (the maximum value when the threshold value is the largest) by setting the threshold value for the next gradation as the arrangement position (the invention according to claim 2).
[0020]
Further, the threshold image determination method for gradation image creation according to the present invention is arranged such that when the threshold arrangement position from the smaller threshold value to a certain gradation is determined during the threshold value arrangement, the threshold value arrangement of the next gradation is determined. When determining the position, after extracting the low frequency component of the image data obtained based on the threshold arrangement in which the threshold arrangement position up to a certain gradation is determined, the position where the extracted low frequency component intensity is the weakest The arrangement position of the threshold value of the next gradation is determined (the invention according to claim 3).
[0021]
According to the present invention, the second process of determining the position where the low frequency component intensity is the weakest as the arrangement position of the threshold value of the next gradation is a processing process in the real space, and the next threshold value is accurately and accurately viewed. Can be determined.
[0022]
In this way, the threshold value array used for creating the gradation image becomes a threshold value array that suppresses unnecessary low-frequency components when the gradation image is created.
[0023]
In the third aspect of the present invention, the threshold values are determined in ascending order from the smaller side (in the case of the smallest, the minimum value), but the third process is the candidate position where the obtained low frequency component intensity is strongest. Can be determined in descending order from the larger threshold value side (the maximum value in the case of the largest threshold value).
[0027]
  Further, according to the threshold value arrangement determination method for gradation image creation of the present invention, when the arrangement of the threshold values in a certain gradation is determined, the higher gradation is in ascending order and the lower gradation is in descending order. Threshold arrangements for all gradations can be determined (claims)5, 7Described invention).
[0028]
  Then, when threshold arrangement positions at a plurality of different gradations are determined in the threshold array, the threshold arrangement positions between the plurality of different gradations are ascending in ascending order from the lower threshold value. All can be determined in descending order from the threshold with the higher gradation.6, 8Described invention).
[0029]
  In the first to eighth aspects of the invention, by extracting the low frequency component by weighting according to human visual characteristics, it becomes possible to extract the low frequency component in a form closer to human perception (claim 9). ).
  Claim 1~ 9In the described invention, generation of unnecessary low-frequency components on the generated halftone image is suppressed by setting the threshold value array as a threshold gradation image generation threshold value array.10Described invention).The threshold gradation array for creating a halftone image is a supercell threshold array (the invention according to claim 11).
[0030]
  Claim1-9By using the threshold array in the described invention as a dither matrix, generation of unnecessary low-frequency components on the gradation image created using the dither matrix is suppressed (the invention according to claim 12).
[0032]
  For the convenience of understanding, the claims5, 6, 7, 8The correspondence between each process in the description and the steps (processes) in FIGS. 13 to 16 in the embodiment will be described.
[0033]
  Claim5→ FIG. 13: Aa process → Step S35, Ba1 process → Step S37, Ba2 process → Step S38, Ba3 process → Step S39, Ca process → Step S42, Ab process → Step 45, Bb1 process → Step 47, Bb2 process → Step S48, Bb3 process → step S49.
[0034]
  Claim6→ FIG. 14: Ac process → Step S65, Bc1 process → Step S67, Bc2 process → Step 68, Bc3 process → Step S69, Ad process → Step S75, Bd1 process → Step S77, Bd2 process → Step S78, Bd3 process → Step 79, Cc process-> step S82.
[0035]
  Claim7→ FIG. 15: first process → step S124, second process → step S125, third process → step S127, fourth process → step S224, fifth process → step S225, sixth process → step S227.
[0036]
  Claim8→ FIG. 16: first process → step S324, second process → step S325, third process → step S424, fourth process → step S425, fifth process → step S427.
[0037]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment of the present invention will be described with reference to the drawings. First, in order to facilitate understanding of the present invention, the basics of a plate making system to which a threshold array according to an embodiment of the present invention is applied. A typical configuration will be briefly described.
[0038]
FIG. 1 shows a basic configuration of a plate making system 10 to which a supercell threshold template (supercell threshold array) 36 according to an embodiment of the present invention is applied.
[0039]
The plate making system 10 shown in FIG. 1 basically includes an image input unit 14, an image processing unit 16, a binary halftone dot image data creation unit 20, and an image output device 24. The plate making system 10 is a system for forming an image read from an original image 12 by an image input unit 14 on a film F as a halftone image.
[0040]
In this case, in the image input unit 14, reflected light or transmitted light from the document image 12 that is irradiated with light from the light source and transferred in the sub-scanning direction is guided to a photoelectric conversion element such as a linear image sensor and electrically. Main scanning is performed, and an image signal (pixel signal) that is an electric signal is converted through the photoelectric conversion element. The converted image signal is converted into, for example, 8-bit digital image data (also simply referred to as image data) DA having values 0, 1,..., 255 by an A / D converter.
[0041]
The image input unit 14 is not limited to such a scanner, and may be any medium that outputs digital image data as a result, such as an image recording disk (image recording medium) such as a DVD, a communication network, or a digital still camera. .
[0042]
For the image data DA output from the image input unit 14, the image processing unit 16 performs a color conversion process and a sharpness process as necessary, and a resolution conversion process for corresponding to the resolution of the image output device 24. This is done to create image data G.
[0043]
In this embodiment, the resolution of the image output device 24, that is, the output resolution is, for example, 72 scan lines / mm. Since the expression of the scanning line / mm is confusing with the number of screen lines, the output resolution is hereinafter expressed by 72 dpm (dot / mm). Here, dot means one pixel as described above.
[0044]
The image data G that has been subjected to predetermined processing by the image processing unit 16 is supplied to a binary halftone dot image data creation unit 20 as a gradation image data creation device. In recent years, the image data G supplied to the binary halftone dot image data creation unit 20 may be directly supplied as a result of image processing using a medium that outputs digital image data, such as the digital camera. is there.
[0045]
The binary halftone dot image data creation unit 20 can be realized by a computer using software, but can also be realized by hardware. It can also be realized by mixing software and hardware.
[0046]
The binary halftone dot image data creation unit 20 includes a comparison unit 32 that functions as a gradation image data creation unit, an address calculation unit 34, and a supercell threshold template as a storage medium that stores a plurality of gradation image data creation threshold arrays. (Threshold array) 36 and a network attribute input unit 38 as selection means for selecting a desired threshold array.
[0047]
The image data G supplied to the binary halftone dot image data creation unit 20 is supplied to the comparison input of the comparison unit 32. Further, an address AD = AD (x, y) representing the x-axis and y-axis addresses on the supercell threshold template 36 is calculated by the address calculation unit 34 from the image data G.
[0048]
The supercell threshold value template 36 is a threshold value stored in the designated address AD (in this case, 8 bits taking the value 1,... 255 (precisely, it is a value obtained by subtracting 1 from 8 bits. , 8 bits) is read and supplied to the reference input of the comparator 32.
[0049]
As the supercell threshold template 36, a template corresponding to the network attributes (the number of screen lines, the screen angle, and the network shape) designated by the network attribute input unit 38 among the plurality of supercell threshold templates is used. In this embodiment, as an example, it is assumed that the number of screen lines is 175, the mesh angle is 45 °, and the mesh shape is designated as square.
[0050]
The supercell is composed of a plurality of halftone cells (halftone dots). In general, in the halftone generation technology field, a supercell is set on a pixel grid determined by the output resolution, the set supercell is divided into halftone cells, and a threshold value corresponding to each pixel in the divided halftone cell is set. Is assigned to generate a halftone threshold, and the supercell to which the threshold is assigned is referred to as a supercell threshold template (threshold array).
[0051]
References for techniques for generating halftone dots in relation to supercells include, for example, “Book Title: Postscript Screening, Author: Peter Fink, Publisher: MD Corporation, Publication Date: August 1994” 11th, first edition first print ".
[0052]
By considering a supercell composed of a plurality of halftone cells, it is possible to change the screen line number and the halftone angle more finely, and select a value closer to the specified screen line number and halftone angle. There is an advantage that it can be.
[0053]
A pixel grid refers to a collection of pixels that are blackening units. Therefore, the pixel grid may image a state in which the pixels are arranged in the vertical and horizontal order at the output resolution.
[0054]
In this embodiment, as the supercell threshold template 36, the one published by the above-mentioned Japanese Patent Laid-Open No. 8-317212 (first technology) or Japanese Patent Laid-Open No. 9-200208 (second technology) is used. I use it.
[0055]
In the comparison unit 32, the magnitudes of G ≧ T → 1 (on, blackening) and G <T → 0 (off, whiteout, non-blackening) for the image data G and threshold data (also simply referred to as threshold) T are large. Binary halftone dot image data (binary data, binary image data, halftone dot image data, or digital halftone dot data) as gradation image data that performs comparison calculation and takes the value 1 or value 0 of the comparison calculation result Say) Create H.
[0056]
The generated binary halftone image data H, that is, gradation image data, is supplied to an exposure recording unit 26 constituting the image output device 24.
[0057]
The exposure recording unit 26 performs exposure scanning and recording on the photosensitive material M disposed in the exposure recording unit 26 by a laser beam (recording beam) that is turned on / off in accordance with the binary halftone dot image data H. A halftone dot image as a latent image is formed on the top. The photosensitive material M on which the halftone dot image is formed is developed by the automatic developing machine 28, and a film F on which a visualized halftone dot image is formed is created. The film F is used as an original plate to form a printing plate. The created printing plate is mounted on a printing machine (not shown), and ink is applied to the mounted printing plate.
[0058]
By transferring the ink applied to the printing plate onto a sheet such as photographic paper, a desired printed matter having an image formed on the sheet can be obtained.
[0059]
The present invention is not an image output device 24 that outputs a film F as an original plate but a CTP (computer to plate) that is an image output device that can directly output a printing plate PP by binary halftone dot image data H. It can also be applied to the output machine 24a. In the CTP output machine 24a, the photosensitive material M is scanned and recorded by a laser beam (recording beam), so that the printing plate PP is obtained directly.
[0060]
Further, the image output apparatus is not limited to a scanning exposure apparatus using a so-called laser beam, and can be applied to an apparatus that draws a film, a printing plate, or a printed matter by a surface exposure method or an inkjet method.
[0061]
Further, if the binary dot image data H is supplied to a CTC (computer to cylinder) printer 24b, the CTC printer 24b is wound around a cylinder based on the binary dot image data H. Ink is applied to the printing plate obtained by scanning and recording the photosensitive material M, and the ink applied to the printing plate is transferred to the sheet, thereby directly obtaining a desired printed matter PM formed on the sheet. Can do.
[0062]
The threshold array of the supercell threshold template 36 constituting the binary halftone dot image data creation unit 20 in FIG. 1 is the one stored in the storage medium 49 such as a floppy disk.
[0063]
This binary halftone dot image creation unit 20 may be executed by software on hardware or a computer. In this case, the threshold value array used is stored in a storage medium such as a hard disk.
[0064]
The above is the description of the basic configuration of the plate making system 10 to which the threshold array according to one embodiment of the present invention is applied.
[0065]
Next, a gradation image creating threshold value array creating apparatus for carrying out a gradation image creating threshold value array determining method according to an embodiment of the present invention will be described.
[0066]
FIG. 2 shows a supercell threshold value template (threshold value) which is configured by a storage medium such as a RAM (Random Access Memory) or a hard disk as a storage means, and is created by assigning a plurality of threshold values 1, 2,... An example of the configuration of a creation device 18 (gradation image creation threshold array creation device) 18 is shown. Here, the gradation image means a binary image {an image made up of blackened pixels and non-blackened (whitened) pixels} or a quaternary image (for example, four levels of density 0, 1, 2, 3). It means a multi-valued image such as an image composed of the gradations shown.
[0067]
In the gradation image creating threshold value array creating apparatus 18 in the example of FIG. 2, the same reference numerals are given to the components corresponding to the components of the plate making system 10 shown in FIG. 1, and the detailed description thereof is omitted.
[0068]
The gradation image creating threshold array creating device 18 selects a parameter input unit 37 for setting input parameters such as the number of lines, an angle, an output resolution, a mesh shape, and the like, and a substantial number of lines according to the set input parameters. A substantial line number angle selection unit 39 and a blackening candidate pixel selection unit 41 that selects a blackening candidate pixel according to the selected substantial line number angle are provided.
[0069]
Further, the threshold image creating apparatus 18 for creating a gradation image generates a threshold size that has already been determined in accordance with the selection of the blackening candidate pixel selected by the blackening candidate pixel selection unit 41. An image data generation unit 30 that generates image data G having a constant size in minutes, and an address AD that is calculated based on the generated image data G and supplied to the supercell threshold template 36M in the process of creation (in the process of creation) A calculation unit 34, and a supercell threshold template 36M in the middle of creation in which thresholds that are sequentially determined from a state in which the thresholds T are all set to zero at the beginning and virtually no threshold T is arranged are stored (saved); A comparison unit 32 is provided that creates binary halftone dot image data H that takes a value 0 or a value 1 from a threshold value (determined threshold value) T and image data G until the middle of creation.
[0070]
Further, the gradation image creating threshold array creating device 18 extracts a low frequency component data (low frequency noise component, low frequency noise data, low frequency component) L from the binary halftone dot image data H. 45, based on the low frequency component data L, the low frequency component at the position of the blackening candidate pixel selected by the blackening candidate pixel selection unit 41 is calculated, and the next blackening is performed based on the calculated low frequency component. A blackened pixel determining unit 46 that determines the pixel position as the threshold arrangement position is provided.
[0071]
Here, the low frequency component extraction unit 45 includes a fast Fourier transformer (FFT) 40 as a frequency converting means, a low-pass filter (LPF) 42, and a fast inverse Fourier transformer (IFFT) 44 as an inverse frequency converting means. Consists of As the frequency conversion means, not only the fast Fourier transformer 40 but also a weblet conversion means can be used. When the weblet conversion means is used, the weblet inverse conversion means is used as the frequency inverse conversion means. .
[0072]
Moreover, the low frequency component extraction part 45 can also extract a low frequency component by filtering (convolution calculation) in real space, without having a frequency conversion means. Although it depends on the mask size and image data size of the convolution calculation, the calculation time is often shorter when the calculation is performed than the convolution calculation. Hereinafter, an example using frequency conversion means will be described.
[0073]
The binary halftone image data H created by the comparison unit 32 is supplied to a fast Fourier transformer 40 which is a Fourier transform unit.
[0074]
This binary halftone dot image data H is image data in a position space (real space). Here, the data on the position space means data on coordinates defined on the xy plane. The binary halftone dot image data H on the position space is converted into data D1 which is an information signal on the frequency space by the fast Fourier transformer 40, and the cutoff frequency is the fundamental frequency component (screen line number component) of the halftone dot. Is supplied to the low-pass filter 42 set to. Here, the data on the frequency space means data on coordinates defined on the frequency plane with the xy axis as the frequency axis.
[0075]
The low-pass filter 42 extracts data D2 including a low frequency component having a frequency lower than the fundamental frequency component (screen line number component) of the halftone dot from the data D1 on the frequency space, and supplies the data D2 to the fast inverse Fourier transformer 44. To do.
[0076]
The fast inverse Fourier transformer 44 converts the data D2 including the low-frequency component extracted in the frequency space into low-frequency component data L that is image data in the position space, and supplies it to the blackened pixel determination unit 46. .
[0077]
The threshold value array determined by the blackened pixel determination unit 46 based on the low-frequency component data L is stored in the generation supercell threshold template 36M, and when all the threshold value arrays 1 to 255 are determined, The supercell threshold template 36M is a supercell threshold template in which all threshold arrays are determined, and is stored in a storage medium 49 such as a floppy disk. From this storage medium 49, the supercell threshold template 36 in the plate making system 10 of FIG. And used for the plate making system 10.
[0078]
Next, a more detailed operation of the gradation image creating threshold value array creating apparatus 18 will be described with reference to the flowchart of FIG.
[0079]
First, in step S <b> 1, input parameters are set by the parameter input unit 37. Here, the input parameters are, for example, 175 screen lines (LPI) = 6.89 lines / mm, a screen angle of 45 degrees, an output resolution of 72 dots / mm (pixels / mm) {the size of one pixel is 13. 9 μm square} and a net-shaped square (square). The net shape may be a circle or other geometric shape other than a quadrangle.
[0080]
Next, in steps S2, S3, and S4, the number of pixels of the supercell (supercell threshold template 36) that is the threshold array is selected to be 119 pixels × 119 pixels in the substantial line number angle selection unit 39, and the halftone image Is selected, and the number of pixels Ndot per gradation is selected. Here, the number of pixels Ndot per gradation is determined by the following equation (1).
[0081]

This is because the threshold T to be placed in the supercell threshold template 36M in the middle of creation, in other words, the threshold T = 1, threshold T = 2,... Threshold T = 255 placed in the supercell threshold template 36, It means that there are 55 each.
[0082]
In this embodiment, for easy understanding, the threshold T array of the supercell threshold template 36M in the process of creation is determined from T = 1 to T = 128, and then 55 (one The operation at the time of determining the arrangement position of the next gradation threshold T = 129 (the arrangement position of one or more thresholds with the same value) will be described.
[0083]
In this case, in step S5 (referred to as “A process” for convenience), a plurality of candidate positions of the same threshold values for the next gradation are selected so as not to impair the shape of the mesh. Here, since the candidate position corresponds to the pixel position of the candidate to be blackened next, it is referred to as a blackened candidate pixel.
[0084]
When the number of blackening candidate pixels is m, m = Ndot + α, for example, Ndot × 2 = 110 is selected. Increasing the margin α increases the degree of freedom of the threshold arrangement, but the blackened shape of the mesh deviates from the square in this example.
[0085]
FIG. 4 shows an example of the procedure for selecting the blackening candidate pixels.
[0086]
That is, in step S5-1, as schematically shown in FIG. 5, for example, the distance value from the center O of each halftone dot 50 normalized by ± 1 to the unprocessed pixel, in other words, still The distance value to the pixel position where the threshold value is not arranged is obtained by the distance function D (x, y) of the following equation (2) that matches the square that is the desired shape.
[0087]
    D (x, y) = 1−(| x | + | y |)                        ... (2)
  In this schematically drawn FIG. 5, when the threshold arrangement to the inside of the square 51 including the center O is determined, the distance value to the unprocessed pixel near the side of the square 52 is then expressed as a distance function D. (X, y).
[0088]
Note that the distance function D (x, y) may be expressed by the following equation (3) when the blackened portion has a circular and thick halftone dot shape.
[0089]
D (x, y) = 1- (x²+ Y²(3)
The distance function D (x, y) corresponds to a so-called spot function.
[0090]
Next, in step S5-2, the minimum value minD (x, y), which is the minimum value, is obtained from the distance values obtained in step S5-1.
[0091]
In step S5-3, it is confirmed whether or not the arrangement position of the minimum value minD (x, y) is an unprocessed pixel, in other words, whether or not a threshold value has been determined. Returns to step S5-2, and if it is an unprocessed pixel, it is set as a blackening candidate pixel in step S5-4.
[0092]
Next, in step S5-5, it is determined whether or not the number of blackening candidate pixels determined up to step S5-4 is equal to the number of blackening candidate pixels m = Ndot + α (here m = 110). When the number of candidate pixels is less than m, the processes of Steps S5-2 to S5-5 are repeated until the number of blackening candidate pixels becomes m.
[0093]
When the blackening candidate pixel number m matches the blackening candidate pixel number m = Ndot + α, the blackening candidate pixel selection unit 41 notifies the blackening pixel determination unit 46 of each pixel position of the blackening candidate pixel number m. To do.
[0094]
Next, the arrangement positions of a plurality of blackening candidate pixels (threshold thresholds at a plurality of locations) are determined by repeatedly performing the processing of step S6 to step S9 described below (referred to as B process for convenience).
[0095]
That is, in the process of step S6, the comparison unit 32 creates binary halftone dot image data H, which is a gradation image, using the supercell threshold template 36M in the process of creation in which a predetermined threshold array is stored. The value of the image data G for creating the binary halftone image data H is G = 128. That is, when determining the arrangement position of the threshold T = 129, when creating the binary halftone image data H representing the predetermined threshold array of the threshold T = 1 to 128, the image data generating unit 30 outputs the image data. A constant value G = 128 is supplied to the super cell threshold size comparison unit 32 as the value of G.
[0096]
FIG. 6 schematically shows a halftone dot image represented by the binary halftone dot image data H created by the comparison unit 32 using the supercell threshold template 36M during creation when the image data G is G = 128. Show.
[0097]
Here, a halftone dot is a flat halftone dot with a dot percentage of 50%, and a halftone dot image (bits) based on binary halftone dot image data H of 119 pixels × 119 pixels related to one supercell obtained by the comparison unit 32. Can be thought of as a pattern.) Here, the fundamental frequency of the halftone dot is approximately equal to the number of screen lines, and can be considered to be 6.89 (c / mm: cycle / mm).
[0098]
From FIG. 6, binary halftone dot image data H is data on coordinates defined on the xy plane, that is, data on the position space (which can be considered as z-axis data) has a value of 0 (non-black). It is understood that the data takes the value 1 (blackening).
[0099]
In FIG. 6, one halftone dot 50 drawn as an example includes about 109 (145² /13.9² ) Pixels are included. In the process of step S5, the pixel positions corresponding to the number m of blackening candidate pixels (m = 110) that are selected and determined by the blackening candidate pixel selection unit 41 and stored in the blackening pixel determination unit 46 are shown in FIG. It is one of the positions that are non-blackened pixels.
[0100]
Next, in step S7 (first process), the low frequency component of the binary halftone image data H is extracted by the low frequency component extraction unit 45 by a special process. Therefore, in this step S7, first, the binary halftone dot image data H is fast Fourier transformed by a two-dimensional FFT 40 to be transformed into data D1 which is an information signal in the frequency space.
[0101]
FIG. 7 shows an FFT power diagram of data D1 on the frequency space after the fast Fourier transform, corresponding to the binary halftone image data H on the position space shown in FIG. The x-axis and y-axis indicate frequency (c / mm), and the z-axis indicates power.
[0102]
In the data D1 on the frequency space in FIG. 7, the power P1 having a value of about 0.5 at the center coordinate (x, y) = (0, 0) is 50% of the net percentage when the flat net is assumed. It is a corresponding basic component, not noise. On the xy plane, coordinates (x, y) = (5, 5), (−5, 5), (−5, 5) on the 45 ° direction from the center coordinate (x, y) = (0, 0). −5), powers P2 to P5 having a value of about 0.2 existing at coordinate positions near (5, −5) are also powers corresponding to the fundamental frequency 6.89 (c / mm) of the network, Absent. For example, the exact x and y coordinates where the power P2 exists can be calculated as 6.89 ÷ √2 = 4.87 instead of the value 5.
[0103]
Considering that the moire fringes are interference fringes generated at a frequency lower than that of the network, the coordinates (x, y) = (5, 5), (−5, 5), (−5, 5) of these four points are used. -5), it is understood that the frequency component existing in the region Q (see also the hatched region in FIG. 5) surrounded by (5, -5) is a noise component (low frequency component) related to moire fringes. The
[0104]
FIG. 9 is an enlarged view of the FFT power diagram of FIG. It can be seen that unevenness, that is, a power component exists in the region Q although it is small.
[0105]
Next, in order to remove high-frequency components other than the region Q, the low-pass filter 42 having a cutoff frequency corresponding to the region Q is operated to extract data D2 including the low-frequency component in the region Q. In other words, low frequency component data D2 having a lower frequency than the basic frequency component of the halftone dot is extracted from the data D1 on the frequency space. At this time, the power P1, which is a DC component, is also removed. In consideration of the blocking of the DC component, the low-pass filter 42 is precisely a band-pass filter.
[0106]
In practice, since moire fringes are perceived by humans, high-frequency components other than the region Q are removed by the low-pass filter 42 in the data D1 obtained by performing fast Fourier transform on the binary halftone image data H by the FFT 40. In this case, after weighting with the human visual characteristic 65 shown in FIG. 10, the low-frequency component is extracted by applying the low-pass filter 42. As shown in FIG. 10, the human visual characteristic 65 is a characteristic having a maximum sensitivity in the vicinity of a frequency of 0.8 (c / mm).
[0107]
Next, the IFFT 44 performs inverse Fourier transform on the low-frequency component data S2 extracted by the low-pass filter 42 to obtain low-frequency component data L on the position space (real space).
[0108]
FIG. 11 three-dimensionally shows the low-frequency component data L represented in a bird's eye view on a 119 pixel × 119 pixel region in the position space. That is, it is understood that low-frequency density undulations are extracted from the original image at peaks and valleys on the three-dimensional figure.
[0109]
In FIG. 11, since weighting is applied based on the human visual characteristic (human visual frequency characteristic) 65 shown in FIG. 10, the low-frequency component data L after inverse Fourier transform by IFFT 44 is the human eye. In other words, the graphic is weighted so that the size (strength) can be easily determined by a computer.
[0110]
  For a model of human visual frequency characteristics, see the article "Design of minimum visual modulation halftone patterns" by the author J. Sullivan, L. Ray, and R. Miller, IEEE Trans. Syst. Man Cybern., Vo.l21, No. 1, 33-38 (1991).
[0111]
Further, even in a method of extracting low-frequency components by applying human visual characteristics, extraction can be performed not only by the above-described filtering calculation in the frequency space but also by a convolution calculation in the real space.
[0112]
The low frequency component data L is supplied from the low frequency component extraction unit 45 to the blackened pixel determination unit 46.
[0113]
Therefore, in step S8 (second process), the blackened pixel determining unit 46, first, the low frequency component data L of 119 pixels × 119 pixels and the binary network of 119 pixels × 119 pixels shown in FIG. The low-frequency component data L at each non-blackened pixel position corresponding to the blackened candidate pixel position where the number of blackened candidate pixels is m = 110 is calculated from FIG.
[0114]
Next, in step S9 (third process), the blackened pixel determination unit 46 has the smallest value (low frequency component data) among the low frequency component data L at each non-blackened pixel position calculated in step S8. The position of the blackening candidate pixel is determined to be the next pixel to be blackened (blackened pixel).
[0115]
In this case, the next blackened pixel position is set as the array position of the next threshold T = 129, and the threshold T = 129 is stored in the memory address at the threshold position in the supercell threshold template 36M in the process of creation. In order to speed up the processing, the determination of the blackened pixels in step S9 may be determined from a smaller one instead of one.
[0116]
Next, in step S10, has the blackened pixel determining unit 46 determined the arrangement position in the supercell threshold template 36M in the process of creation of the threshold T = 129 for the number of pixels Ndot = 55 per gradation? If it has not been determined, the process from step S6 to step S9 (first process, second process, third process) is repeated until it is determined. In the process of step S6 when iterating, the image data G output from the image data generation unit 30 is the image data G of the next gradation based on the black pixel determination notification from the black pixel determination unit 46 = 129.
[0117]
Further, when the determination in step S10 is established, that is, when the threshold positions corresponding to all the blackened pixels of the number of pixels Ndot per gradation are determined, in step S11, the blackened pixel determining unit 46 It is confirmed whether or not all threshold arrays up to the threshold T = 255 where T is the maximum value have been determined. If the threshold array has not been determined, the processing from step S5 to step S10 is repeated to determine the threshold T = 255. All the threshold arrays up to are determined, and the process is terminated.
[0118]
Note that the supercell threshold template 36M in the process of creation in which all threshold arrays are determined is the supercell threshold template 36, and the data of the threshold template 36 is stored in the storage medium 49, and the storage medium 49 shown in FIG. It is copied to the supercell threshold template 36 in the plate making system 10.
[0119]
Thereafter, in the same manner, by setting new parameters (number of lines, angle, output resolution, mesh shape, etc.) in step S1, the threshold array of the supercell threshold template 36 corresponding to these parameters is substantially automatically determined. can do.
[0120]
In the above-described embodiment, the binary halftone image data H is targeted. However, the present invention is not limited to the binary halftone image data H, and the output value is “0, 1, 2, 3”. The present invention can also be applied to multi-value halftone image data such as 4-value or 8-value.
[0121]
Further, in the above-described embodiment, the determination of the threshold arrangement for creating a gradation image by the halftone dot 50 shown in FIG. 6 has been described. However, the present invention creates a threshold template for creating a halftone image. The present invention is not limited to this, and N × N pixels can be considered as one unit of gradation reproduction, and can be applied to a threshold array of N × N threshold templates (dither matrix) for creating gradation images corresponding thereto.
[0122]
This dither matrix can also be applied to an FM (frequency modulation) screen that changes the collective density (frequency) of pixels in accordance with gradation.
[0123]
FIG. 12 is a flowchart showing a procedure for determining the threshold arrangement of the dither matrix.
[0124]
First, in step S21, input parameters are set. Here, the input parameters are the output resolution (pixels / mm), the size of one pixel on the FM screen, the size of the dither matrix, for example, N pixels × N pixels (as described above, the threshold T to be set is 1). N²It becomes a piece. ).
[0125]
Next, in step S22, the initial position of the threshold T = 1 is determined as an appropriate pixel position in the dither matrix.
[0126]
Next, in step S23, the comparison unit 32 creates binary image data by comparing the dither matrix for which only the threshold value T = 1 is determined with the image data of N × N pixels whose pixel values are all 1.
[0127]
Next, in step S24, as described in step S7, low-frequency component data extraction processing is performed on the binary image data created in step S23 (first process).
[0128]
Next, in step S25, the position of the pixel to be blacked out next, in other words, the position in the dither matrix where the next threshold value T = 2 is to be entered is determined. In the process of step S5, it is only necessary to determine that the lowest (weak) position of the low frequency component data is the pixel position to be blackened next (second process).
[0129]
Next, in step S26, N²It is determined whether or not all threshold arrangement positions have been determined, and in this case, from the arrangement position of the next threshold T = 2 to the final threshold T = N until all threshold arrangement positions are determined.²Steps S23 to S25 are repeated.
[0130]
When the threshold is actually used, it is standardized to the number of gradations according to the output device. For example, if the number of gradations of the output device is 256 gradations, and the original threshold value is T, the new threshold value is threshold = T × (255 / N²).
[0131]
Thus, 1-N²It goes without saying that the method of obtaining the threshold array of the necessary number of gradations after determining the threshold array can also be applied when creating the above-described threshold image creation threshold data.
[0132]
In this way, the threshold array of the dither matrix can be determined. The dither matrix whose threshold value array is determined can be stored in the storage medium 49.
[0133]
In the determination of the threshold value array based on the flow chart of FIG. 3 and the determination of the threshold value array based on the flow chart of FIG. 12, the threshold value T = 1 to the network% is sequentially increased from 0% (the smaller one) in ascending order. The blackened pixels (threshold array) are determined, but this threshold array may be determined sequentially in descending order from 100% (larger) in the halftone from the maximum value of the threshold T.
[0134]
In the threshold value array creating apparatus 18 of FIG. 2, by replacing the blackened pixel determining unit 46 and the blackened candidate pixel selecting unit 41 with a whitened pixel determining unit and a whitened candidate pixel selecting unit, respectively, the threshold arrangement positions in descending order. It is possible to correspond to the method of determining
[0135]
In this case, in step S9 (third process) in the flowchart of FIG. 3, each whitened pixel calculated by the whitened pixel determining unit (corresponding to the blackened pixel determining unit 46 in FIG. 4) is calculated in step S8. Among the low-frequency component data L at the position, the pixel to be whitened next is the position of the whitening candidate pixel having the largest value (the power value of the low-frequency component data is strong, in other words, the strongest low-frequency component intensity). (Whitened pixels) may be determined. Further, in the process of step S25 in the flowchart of FIG. 12, it may be determined that the largest (strong) position of the low frequency component data is the pixel position to be whitened next (second process).
[0136]
Further, when determining the threshold arrangement position, only the dot arrangement position (binary pattern, dot pattern, halftone dot shape, black and white pattern) in a specific halftone dot is determined as an optimum dot arrangement position by a special method. Even if it is selected, it can be handled as follows.
[0137]
That is, when determining the arrangement position of the threshold value Th of the next gradation with the higher gradation and the arrangement position of the threshold value Tl of the next gradation with the lower gradation with respect to the threshold value Tfix for which the arrangement position is determined, When determining the arrangement position of the threshold value Th of the higher gradation of the next gradation, all the threshold values T of the dot pattern (threshold array) are set to 0 for convenience, and the threshold values after the threshold value Th + 1 are arranged in ascending order. When determining the position and determining the arrangement position of the threshold value Tl of the next gradation having the lower gradation, all the threshold values T of the dot pattern (threshold array) are set to the maximum value for convenience, for example, T = N²As described above, the threshold arrangement positions after the threshold Tl-1 may be determined in descending order.
[0138]
FIG. 13 shows the arrangement positions of the threshold value Th having the higher gradation and the threshold value Tl having the lower gradation when the arrangement position (monochrome pattern, dot pattern) at the threshold value Tfix at a certain gradation is determined. The procedure to determine each is shown.
[0139]
The processing in steps S31 to S41 in the flowchart shown in FIG. 13 is the same as the processing contents in steps S1 to S11 in the flowchart shown in FIG. 3, and the processing in steps S45 to S51 in the flowchart shown in FIG. Since the processing contents of steps S5 to S11 are the same, detailed description thereof is omitted.
[0140]
In the flowchart shown in FIG. 13, when determining the threshold value Th of the next gradation having the higher gradation, as described above, pixels that are blackened with a dot pattern of a certain threshold value Tfix are set to the threshold value T. For convenience, it is set to 0 (a pixel that is always blackened), and is not selected as a blackening candidate pixel in step S35, and the arrangement position of the threshold value T equal to or higher than the threshold value Th = Tfix + 1 of the next tone as an initial value is sequentially set. decide. Step S34A shows the setting of the threshold value Th = Tfix + 1 as the initial value, and step S42 shows the threshold value update process to the threshold value Th (Th = Th + 1) of the next gradation with the higher threshold value T.
[0141]
Similarly, when determining the arrangement position of the threshold value Tl of the next gradation with the lower gradation, as described above, a pixel that is whitened with a dot pattern of a certain threshold value Tfix is set to the threshold value T for convenience. For example, the position of the threshold value T equal to or less than Tfix-1 is sequentially determined so that the pixel is 255 (a pixel that is always whitened) and is not selected as a whitening candidate pixel. Step S34B shows the setting of the threshold value Tl = Tfix-1 as the initial value, and step S52 performs the threshold value update process to the threshold value Tl (Tl = Tl-1) of the next gradation with the lower threshold value T. Show.
[0142]
Here, in step S45, as in step S5, a plurality of candidate positions for the arrangement positions of the plurality of threshold values Tl having the same value of the lower next gradation are selected so as not to impair the shape of the mesh. Here, the candidate position corresponds to the pixel position of a candidate to be whitened next, and is therefore referred to as a whitening candidate pixel.
[0143]
Further, when determining the arrangement positions of the threshold values Th and Tl of the next gradation, they may be determined one gradation at a time, and after determining all the arrangement positions of the higher threshold value Th, the arrangement of the lower threshold value Tl. The position may be determined independently so as to determine the position.
[0144]
In this case, it is also possible to change the configuration so that the arrangement positions of the threshold values are determined in ascending order and descending order from the threshold values at a plurality of different gradation levels corresponding to a plurality of different halftone%.
[0145]
In FIG. 14, when the arrangement positions (monochrome pattern, dot pattern) of the threshold values Tfix1, Tfix2 (Tfix1 <Tfix2) up to two different gradations are determined, the initial value threshold values are set to steps S64A and S64B, respectively. As shown in FIG. 8, the threshold Th = Tfix1 + 1 and Tl = Tfix2-1 are set, and the procedure for determining the threshold arrangement position between the threshold Tfix1 and the threshold Tfix2 is shown.
[0146]
The processing in steps S61 to S69, S80, and S81 in the flowchart shown in FIG. 14 is the same as the processing contents in steps S1 to S11 in the flowchart shown in FIG. 3, and steps S75 to S81 in the flowchart shown in FIG. Since the process of step S5 is the same as the process of steps S5 to S11, detailed description thereof is omitted.
[0147]
In the flowchart shown in FIG. 14, the arrangement positions of the threshold values Th and Tl of the higher and lower next tones are not calculated independently as in the example of FIG. 13, but the average value (Tfix1 + Tfix2) / 2 is used. The threshold value Th of the higher next gradation and the threshold value Tl of the lower next gradation are increased (Th = Th + 1) and decreased (Tl = Tl-1) at the same timing so that the threshold arrangement positions coincide. The threshold arrangement positions are determined for each pixel on the threshold Th and Tl sides of the higher and lower next gradations.
[0148]
Note that when selecting candidate pixels in steps S65 and S75, candidate pixels are selected from pixels whose threshold positions are not determined on either the higher or lower next-threshold threshold Th or Tl side. select. In the example of FIG. 14, the threshold value Th of the higher next tone is processed before the threshold value Tl of the lower next tone, but the arrangement position of the threshold value Tl of the lower next tone is processed first. May be.
[0149]
In this way, it is possible to determine a threshold arrangement that suppresses the occurrence of moire between the thresholds Tfix1 and Tfix2, while maintaining a preferable dot pattern at a specific halftone% corresponding to the thresholds Tfix1 and Tfix2.
[0150]
Further, as the threshold value array determined by this method, threshold value Tfix1 = 0% (all white) and threshold value Tfix2 = 100% (all black) are set, and 0% (= Tfix1) to 50% in halftone% are ascending order. Naturally, a method of determining the threshold value arrangement in descending order from 100% (= Tfix2) to 50% in the net% is also included.
[0151]
A specific description will be given of a case where a binary pattern is determined at a certain mesh%, for example, 30%, 50%, and 70%, and a threshold value array is determined before and after that.
[0152]
In this case, the threshold value of 0 to 30% is determined based on the dot pattern of 30% and the threshold arrangement position up to 0% is determined in descending order corresponding to the procedure of FIG. The threshold of 30 to 50% follows the procedure of FIG. 14, and the threshold of 30 to 40% determines the arrangement position in ascending order from 30% based on the 30% dot pattern, and the threshold of 40 to 50% The arrangement positions are determined in descending order from 50% based on the 50% dot pattern.
[0153]
Further, in the threshold range from 50 to 70%, the arrangement position of the threshold value of 50 to 60% is determined in ascending order from 50% based on the dot pattern of 50%, and the arrangement position of the threshold value of 60 to 70% is 70%. Based on the dot pattern, the threshold arrangement positions are determined in descending order from 70%.
[0154]
Further, for the threshold value of 70 to 100%, arrangement positions up to 100% are determined in ascending order according to the procedure of FIG. 3 based on the threshold value of 70%.
[0155]
FIG. 15 shows that when the arrangement position (monochrome pattern, dot pattern) at a certain threshold value Tfix is determined in the threshold array of the dither matrix instead of the halftone dot, the threshold value Th having the higher gradation and the lower gradation are obtained. This shows a procedure for determining the arrangement position of the threshold value Tl.
[0156]
The processing in steps S121 and S123 to S126 in the flowchart shown in FIG. 15 is the same as the processing contents in steps S21 and S23 to S26 in the flowchart shown in FIG. 12, and steps S223 to S226 in the flowchart shown in FIG. Similarly, the process of step S23 to S26 is the same as that of step S23, and detailed description thereof is omitted.
[0157]
Here, in the process of step S122A, a threshold value Th = Tfix + 1 is set as an initial value, and in step S127, the threshold value Th = Th + 1 of the higher next gradation is updated.
[0158]
In the process of step S122B, a threshold value Tfix-1 is set as an initial value, and in step S227, the threshold value Tl = Tl-1 for the lower next gradation is updated.
[0159]
In this way, it is possible to determine the entire threshold arrangement of the dither matrix in which the dot pattern is determined with a certain threshold T = Tfix. This threshold value array is a threshold value array that can suppress the occurrence of moire in the vicinity thereof while retaining a dot pattern at a predetermined Tfix. The dither matrix whose threshold value array is determined can be stored in the storage medium 49.
[0160]
FIG. 16 shows not the halftone dots but the arrangement positions (monochrome pattern, dot pattern) in the threshold values Tfix1, Tfix2 (Tfix1 <Tfix2) up to a plurality of different gradations in the dither matrix threshold array. The procedure for determining the arrangement position of the threshold T between the threshold Tfix1 and the threshold Tfix2 is shown.
[0161]
The processing in steps S321 and S323 to S325 in the flowchart shown in FIG. 16 is the same as the processing contents in steps S21 and S23 to S25 in the flowchart shown in FIG. 12, and steps S423 to S426 in the flowchart shown in FIG. Similarly, the process of step S23 to S26 is the same as that of step S23, and detailed description thereof is omitted.
[0162]
Here, in the processing of steps S322A and S322B, thresholds Th = Tfix1 + 1 and Th = Tfix2-1 are set as initial values, respectively. In step S427, the threshold value Th = Th + 1 for the higher next gradation and the lower next floor are set. The key T1 is updated to Tl-1.
[0163]
Here, the threshold value Th = Tfix1 + 1 as the initial value and the updated threshold value Th = Th + 1 are used for the determination processing of the arrangement position of the higher threshold value Th in steps S323 to S325, and the threshold value Tl = Tfix2− as the initial value. The threshold value Tl = Tl−1 updated to 1 is used for the determination processing of the arrangement position of the lower threshold value Tl in steps S423 to S425.
[0164]
Note that the arrangement positions of the threshold values below the lower threshold value Tfix1 can be determined using the procedure of steps S122B and S223 to S227 shown in FIG. 15, and the arrangement positions of the threshold values above the higher threshold value Tfix2 are shown. Can be determined using the procedure of steps S122A and S123 to S127 shown in FIG.
[0165]
In this way, it is possible to determine the entire threshold arrangement of the dither matrix in which the dot pattern is determined with a plurality of different gradation thresholds T = Tfix1 and Tfix2. In this way, it is possible to determine a threshold arrangement that suppresses the occurrence of moire between the thresholds Tfix1 and Tfix2, while maintaining a preferable dot pattern at a specific halftone% corresponding to the thresholds Tfix1 and Tfix2. The dither matrix whose threshold value array is determined can be stored in the storage medium 49.
[0166]
Also in this case, as the threshold value array determined by this method, threshold value Tfix1 = 0% (all white) and threshold value Tfix2 = 100% (all black) are set, and 0% (= Tfix1) to 50% in halftone% Naturally, a method of determining the threshold value arrangement in descending order from 100% (= Tfix2) to 50% in the network% in ascending order is naturally included.
[0167]
In addition, this invention is not restricted to embodiment mentioned above, Of course, a various structure can be taken, without deviating from the summary of this invention.
[0168]
【The invention's effect】
As described above, according to the present invention, it is possible to determine a threshold arrangement with very little occurrence of a periodic pattern or moire.
[0169]
Further, according to the present invention, it is possible to suppress the occurrence of low frequency components such as moire on the gradation image formed by the output gradation image data.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of a plate making system to which a supercell threshold template according to an embodiment of the present invention is applied.
FIG. 2 is a block diagram showing a configuration of a threshold value creation device.
FIG. 3 is a flowchart showing a procedure for determining a threshold array.
4 is a flowchart showing a detailed processing procedure of a blackening candidate pixel selection process during the threshold sequence determination procedure in the example of FIG. 3; FIG.
FIG. 5 is a diagram for explaining a distance function;
FIG. 6 is a diagram showing an image on a position space represented by binary halftone dot image data before threshold value array determination.
FIG. 7 is a diagram showing FFT power when binary halftone image data before threshold array determination is subjected to fast Fourier transform.
FIG. 8 is a diagram for explaining a region of a low-frequency component to be extracted.
FIG. 9 is a diagram showing FFT power obtained by enlarging a region of a low frequency component to be extracted.
FIG. 10 is a characteristic diagram for explaining human visual characteristics.
FIG. 11 is a diagram showing the shape of a low frequency component on the position space when the extracted low frequency component is subjected to inverse Fourier transform.
FIG. 12 is a flowchart illustrating a procedure for determining a threshold array of a dither matrix.
FIG. 13 is a flowchart showing a threshold arrangement determination procedure when a threshold dot pattern at a certain gradation is determined.
FIG. 14 is a flowchart showing a threshold arrangement determining procedure when threshold dot patterns at two different gradations are determined.
FIG. 15 is a flowchart showing a procedure for determining a threshold arrangement of a dither matrix when a dot pattern with a threshold at a certain gradation is determined.
FIG. 16 is a flowchart showing a procedure for determining a threshold arrangement of a dither matrix when threshold dot patterns at two different gradations have been determined.
[Explanation of symbols]
10 ... Prepress system 12 ... Original image
14 ... Image input unit 16 ... Image processing unit
18... Threshold array creation device for creating gradation images
20... Binary dot image data creation unit (gradation image data creation device)
32 ... Comparison part 34 ... Address calculation part
36 ... Supercell threshold template (halftone threshold data)
36M ... Supercell threshold template during creation
37 ... Parameter input part 38 ... Network attribute input part
40 ... FFT 41 ... Blackening candidate pixel selector
42 ... LPF 44 ... IFFT
46 ... Blackened pixel determining unit 49 ... Storage medium
50 ... halftone dot AD ... address
DA, G ... image data F ... film
H: Halftone dot image data after correction L: Low frequency component data
M ... photosensitive material PP ... printing plate
PM ... Printed matter S1 ... Data on frequency space
S2 ... Low frequency component data T ... Threshold data (threshold)

Claims (14)

When determining the arrangement position of one or more threshold values of the same value of the next gradation when the arrangement position of the threshold value from the smaller threshold value to a certain gradation is determined in the threshold value array,
A process of determining one or more candidate positions of arrangement positions of one or more threshold values having the same value of the next gradation;
A B process for determining an arrangement position of a threshold value of the next gradation among the candidate positions;
The process B is
A first step of extracting a low-frequency component of image data obtained based on a threshold arrangement in which the arrangement positions of the thresholds up to a certain gradation are determined;
A second step of determining the low frequency component intensity at each candidate position of the one or more locations;
A third step of determining the candidate position having the weakest low frequency component intensity as the arrangement position of the threshold value of the next gradation,
A gradation image creating threshold array determining method, wherein the first to third processes are repeated until all arrangement positions of one or more thresholds having the same value of the next gradation are determined. When determining the arrangement position of one or more threshold values of the same value of the next gradation when the arrangement position of the threshold value from the larger threshold value to a certain gradation is determined in the threshold value array,
A process of determining one or more candidate positions of arrangement positions of one or more threshold values having the same value of the next gradation;
A B process for determining an arrangement position of a threshold value of the next gradation among the candidate positions;
The process B is
A first step of extracting a low-frequency component of image data obtained based on a threshold arrangement in which the arrangement positions of the thresholds up to a certain gradation are determined;
A second step of determining the low frequency component intensity at each candidate position of the one or more locations;
A third step of determining a candidate position having the strongest low frequency component intensity as an arrangement position of the threshold value of the next gradation,
A gradation image creating threshold array determining method, wherein the first to third processes are repeated until all arrangement positions of one or more thresholds having the same value of the next gradation are determined. When determining the arrangement position of the threshold value of the next gradation when the arrangement position of the threshold value from the smaller threshold value to a certain gradation is determined in the threshold array,
A first step of extracting a low-frequency component of image data obtained based on a threshold arrangement in which the arrangement positions of the thresholds up to a certain gradation are determined;
And a second step of determining a position where the extracted low frequency component intensity is the weakest as the arrangement position of the threshold value of the next gradation. When determining the arrangement position of the threshold of the next gradation when the arrangement position of the threshold from the larger threshold to a certain gradation is determined in the threshold array,
A first step of extracting a low-frequency component of image data obtained based on a threshold arrangement in which the arrangement positions of the thresholds up to a certain gradation are determined;
And a second step of determining a position where the extracted low-frequency component intensity is the strongest as the arrangement position of the threshold value of the next gradation. A gradation image that determines the arrangement positions of the thresholds for all gradations, that is, higher and lower than the certain gradation, when the arrangement positions of the thresholds for a certain gradation are determined in the threshold arrangement. In the threshold sequence determination method for creation,
When determining the arrangement positions of all the thresholds of the higher gradation,
An Aa process for determining one or more candidate positions for the arrangement of one or more thresholds (Th = Tfix + 1) of the same value of the next gradation having a higher threshold value (Tfix) of the certain gradation;
A Ba process for determining an arrangement position of a threshold value (Th) of the next gradation among the candidate positions;
The Ba process is
A Ba1 process for extracting a low-frequency component of image data obtained based on a threshold arrangement of thresholds (Th-1) at a certain gradation whose arrangement position is determined;
A Ba2 process for determining the low frequency component intensity at each candidate position of the one or more locations;
A Ba3 process for determining a candidate position having the weakest low frequency component intensity as an arrangement position of the threshold value (Th) of the next tone,
The Ba1 process to the Ba3 process are repeated until all arrangement positions of one or more threshold values (Th) having the same value of the next gradation are determined,
A Ca process for updating a threshold value (Th) in the Aa process and the Ba process to a threshold value (Th + 1);
The Aa process to the Ca process are repeated until all threshold positions having higher gradations than a certain gradation are determined,
When determining the arrangement positions of all the threshold values of the lower gradation,
Ab process for determining one or more candidate positions of arrangement positions of one or more thresholds (Tl = Tfix-1) of the same value of the next gradation of the lower one of the thresholds of the certain gradation (Tfix). When,
A Bb process for determining an arrangement position of a threshold value (Tl) of the next gradation among the candidate positions;
The Bb process is
A Bb1 process for extracting a low-frequency component of image data obtained based on a threshold arrangement of threshold values (Tl + 1) at a certain gradation whose arrangement position is determined;
A Bb2 process for determining the low frequency component intensity at each candidate position of the one or more locations;
A Bb3 process for determining a candidate position having the strongest low frequency component intensity as an arrangement position of the threshold value Tl of the next gradation,
The Bb1 process to the Bb3 process are repeated until all arrangement positions of one or more threshold values (Tl) having the same value of the next gradation are determined,
And a Cb process for updating a threshold value (Tl) in the Ab process and the Bb process to a threshold value (Tl-1),
The threshold image determination method for gradation image creation, wherein the Ab process to the Cb process are repeated until the arrangement positions of all threshold values having a lower gradation than the certain gradation are determined. For creating a gradation image that determines the arrangement position of each threshold between the different gradations when the arrangement positions of the thresholds (Tfix1, Tfix2 (Tfix1 <Tfix2)) at different gradations are determined in the threshold arrangement. In the threshold sequencing method,
One candidate position of the arrangement position of one or more thresholds (Th = Tfix1 + 1) having the same value of the next gradation higher than the threshold (Tfix1) of the lower gradation determined by the arrangement position. Ac process determined above,
A Bc process for determining an arrangement position of a threshold value (Th) of the next gradation among the candidate positions determined in the Ac process,
The Bc process is:
A Bc1 process for extracting a low-frequency component of image data obtained based on a threshold arrangement of threshold values (Th-1) at gradations at which arrangement positions are determined;
A Bc2 process for determining the low frequency component intensity at each candidate position of the one or more locations;
A Bc3 process for determining a candidate position having the weakest low frequency component intensity as an arrangement position of the threshold value (Th) of the next tone,
Candidate positions for the arrangement position of one or more threshold values (Tl = Tfix2-1) of the next gradation lower than the higher gradation threshold value (Tfix2) determined by the arrangement position are set. An Ad process that determines one or more locations;
A Bd process for determining an arrangement position of the threshold value (Tl) of the next gradation among the candidate positions determined in the Ad process,
The Bd process is:
A Bd1 process for extracting a low-frequency component of image data obtained based on the threshold arrangement of the threshold (Tl + 1) at the gradation at which the arrangement position is determined;
A Bd2 process for determining the low frequency component intensity at each candidate position of the one or more locations;
A Bd3 process for determining a candidate position having the strongest low frequency component intensity as an arrangement position of the threshold value (Tl) of the next tone,
And the Cc process for updating the threshold values (Th) and (Tl) in the Ac process, Bc process, Ad process, and Bd process to threshold values (Th + 1) and (Tl-1), respectively.
The Ac process, the Bc process, the Ad process, the Bd process, and the Cc process are repeated until the arrangement positions of all the threshold values between the thresholds (Tfix1) and (Tfix2) of the different gradations are determined. A method for determining a threshold arrangement for creating a toned image. When the threshold arrangement position for a certain gradation is determined in the threshold arrangement, the threshold arrangement positions for all gradations are determined which are higher and lower than the certain gradation. In the threshold value array determining method for gradation image creation,
When determining the arrangement positions of all the thresholds having a higher gradation than the certain gradation,
A first process of converting image data obtained on the basis of an arrangement position of a determined threshold value (defined as Th-1) at a certain gradation into data on a frequency space and extracting a low-frequency component;
A second step of determining the position where the extracted low-frequency component intensity is the weakest as the arrangement position of the threshold value (Th) of the next gradation having the higher gradation;
A third step of updating the threshold (Th) in the first and second steps to a threshold (Th + 1);
The first to third processes are repeatedly performed until the arrangement positions of all the thresholds having a higher gradation than the certain gradation are determined,
When determining the arrangement positions of all the thresholds whose gradation is lower than the certain gradation,
A fourth process of converting the image data obtained based on the arrangement position of the determined threshold value (Tl + 1) at a certain gradation into data on a frequency space and extracting a low frequency component;
A fifth step of determining the position where the extracted low frequency component intensity is the strongest as the arrangement position of the threshold value (Tl) of the next gradation of the lower gradation;
A sixth step of updating the threshold (Tl) in the first and second steps to a threshold (Tl-1);
The threshold image determination method for gradation image creation, characterized in that the fourth to sixth processes are repeated until the arrangement positions of all the thresholds having gradations lower than the certain gradation are determined. For creating a gradation image that determines the arrangement position of each threshold between the different gradations when the arrangement positions of the thresholds (Tfix1, Tfix2 (Tfix1 <Tfix2)) at different gradations are determined in the threshold arrangement. In the threshold sequencing method,
Image data obtained based on a threshold arrangement of threshold values with lower gradations (Tfix1 = Th−1) among the threshold values determined by the arrangement position is converted into data on a frequency space, A first process of extracting low frequency components;
A second step of determining the position where the extracted low frequency component intensity is the weakest as the arrangement position of the threshold value (Th) of the next gradation of the higher gradation;
Image data obtained based on a threshold arrangement of higher thresholds (Tfix2 = Tl−1) among thresholds determined by the arrangement position is converted into data on a frequency space, A third step of extracting low frequency components;
A fourth step of determining the position where the extracted low frequency component intensity is strongest as the arrangement position of the threshold value (Tl) of the next gradation of the lower gradation;
The fifth step of updating the threshold value (Th) in the first and second steps to the threshold value (Th + 1) and updating the threshold value (Tl) in the third and fourth steps to the threshold value (Tl-1). When,
The gradation image creating threshold array determination method, wherein the first to fifth processes are repeated until all arrangement positions of the threshold values between the different gradations are determined. In the threshold value array determining method for gradation image creation according to any one of claims 1 to 8 ,
In the process of extracting the low frequency component,
A threshold image determination method for gradation image creation, characterized by extracting low-frequency components by weighting according to human visual characteristics. In the threshold value array determining method for gradation image creation according to any one of claims 1 to 9 ,
The threshold value array determining method according to claim 1, wherein the threshold value array is a halftone image forming threshold value array. The threshold value array determining method for creating a gradation image according to claim 10,
The halftone image creating threshold array is a supercell threshold array.
A threshold value array determining method for creating a gradation image, characterized in that In the threshold value array determining method for gradation image creation according to any one of claims 1 to 9 ,
The threshold value array determining method for gradation image creation, wherein the threshold value array is a dither matrix. A threshold value array determined by the gradation image creating threshold value array determining method according to any one of claims 1 to 11. A gradation image data creation device for creating gradation image data by comparing the threshold value array according to claim 12 and image data by a comparison unit.

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