JP3740739B2 - Dither matrix creation method - Google Patents

Description

【００４７】
尚、このように補正された今回の注目要素の値Ｄx,y は、その後、上記Ｓ３３０で他の要素が注目要素として選択された場合に、前述のＳ３３５にて、周辺要素の補正後の値として読み込まれることとなる。
このようにしてＳ３４５の処理が終わると、続くＳ３５０にて、処理対象マトリックスＳＭi の全要素について処理が終了したか否かを判定し、未処理の要素が存在すれば、Ｓ３３０に戻り、処理対象マトリックスＳＭi における次の座標の要素を注目要素として、前述したＳ３３０〜Ｓ３４５の処理を繰り返す。そして、Ｓ３５０にて、全要素についての処理が終了したと判定すれば、当該粗密計算処理を終了する。
【００４８】
つまり、粗密計算処理では、注目要素の値Ｄx,y に対して、周辺要素の値Ｄx-1,y-1 、Ｄx,y-1 、Ｄx+1,y-1 、Ｄx-1,y に所定の重み付け係数α１，α２，α３，α４を乗じた値を加算すると共に、処理対象マトリックスＳＭi の元の全要素の平均値Ｈi に重み付け係数の総和（α１＋α２＋α３＋α４）を乗じた値を減じ、その加算及び減算を行った後の値Ｄ′x,y を、注目要素の補正後の値Ｄx,y として保存する、という式１，２の演算を、２値マトリックスＦi をコピーした処理対象マトリックスＳＭi の各要素について順次実行するようにしている。
【００４９】
そして、この粗密計算処理が行われた後の処理対象マトリックスＳＭi は、全要素の平均値が２値マトリックスＦi の全要素の平均値Ｈi とほぼ一致するように、２値マトリックスＦi の各要素の値を他の要素の値に拡散させたマトリックスとなる。
【００５０】
上述したように少ドットマトリックス生成処理のＳ３２０で、図４の粗密計算処理の実行が終了すると、図３に示すようにＳ３６０へ進む。
そして、このＳ３６０にて、粗密計算処理が行われた後の処理対象マトリックスＳＭi の全要素の内で最大値を有する要素の位置を、２値マトリックスＦi にて「１」の要素が最も密である位置（ドットが最も密な位置）と判断し、更に、２値マトリックスＦi において、「１」の要素が最も密である位置と判断した位置の要素の値を「１」から「０」に変更することで、２値マトリックスＦi よりも「１」の要素が１つ少ない（ｉ−１）ドットの２値マトリックスＦi-1 を作成し、その２値マトリックスＦi-1 をワーキングメモリ１４に保存する。
【００５１】
その後、続くＳ３７０にて、ドット数番号ｉの値を１つ減少させ（デクリメントし）、続くＳ３８０にて、ドット数番号ｉの値が０よりも大きいか否かを判定する。ここで、ドット数番号ｉの値が未だ０よりも大きければ、Ｓ３２０に戻り、ドット数が今回のドット数番号ｉに一致する２値マトリックスＦi （つまり、前回のＳ３６０で新たに作成した２値マトリックスＦi-1 ）を今回の処理対象として、前述したＳ３２０〜Ｓ３７０の処理を繰り返す。そして、Ｓ３８０にて、ドット数番号ｉが０よりも大きくないと判定すれば、当該少ドットマトリックス作成処理を終了する。
【００５２】
よって、この少ドットマトリックス作成処理が終了すると、ワーキングメモリ１４には、上記基本マトリックスＦn と、その基本マトリックスＦn よりも「１」の要素が１つずつ少ないｎ個の２値マトリックスＦn-1 〜Ｆ0 とが保存されることになる。
【００５３】
ここで、説明を簡単にするため、Ｓ２００で保存された基本マトリックスＦnが、例えば図８（ａ）に示すように、全要素数ｋが２５（＝５×５）で、ドット数ｎが８であった場合について説明する。
この場合、少ドットマトリックス作成処理（図３）のＳ３２０では、上記基本マトリックスＦn が、最初に処理対象としての２値マトリックスＦ8 として選択され、その２値マトリックスＦ8 に対して図４の粗密計算処理が実行される。すると、粗密計算処理のＳ３２７で上記２値マトリックスＦ8 をコピーして作られる処理対象マトリックスＳＭ8 の各要素の値は、最終的に図８（ｂ）の様な値となる。
【００５４】
そして、少ドットマトリックス作成処理の次のＳ３６０では、処理対象マトリックスＳＭ8 の全要素の内で最大値（ｍａｘ）である「０．７３」の要素の位置を、２値マトリックスＦ8 にて「１」の要素が最も密である位置と判断する。そして更に、Ｓ３６０では、図８（ｃ）の○印で示すように、２値マトリックスＦ8 において、上記の如く「１」の要素が最も密である位置と判断した位置の要素の値を「１」から「０」に変更することで、「１」の要素が７個の（７ドットの）２値マトリックスＦ7 を作成する。
【００５５】
その後、新たに作成した２値マトリックスＦ7 に対しても、Ｓ３２０及びＳ３６０の処理を実行することで、「１」の要素が６個の（６ドットの）２値マトリックスＦ6 を作成し、以後同様に処理を繰り返すことで、図８（ｄ）に示すように、全ての要素が「０」である２値マトリックスＦ0 まで作成するのである。
【００５６】
このように、少ドットマトリックス作成処理を実行して、基本マトリックスＦn よりも「１」の要素が１つずつ少ないｎ個の２値マトリックスＦn-1 〜Ｆ0 を作成すると、図２に示す如く次のＳ４００に進む。
そして、このＳ４００にて、今度は、上記基本マトリックスＦn を元にして、（ｎ＋１）ドットの２値マトリックスＦn+1 からｋドットの２値マトリックスＦk までの、（ｋ−ｎ）個の２値マトリックス（つまり、基本マトリックスＦn よりも「１」の要素が１つずつ多い（ｋ−ｎ）個の２値マトリックス）Ｆn+1 〜Ｆk を作成する、多ドットマトリックス作成処理を実行する。
【００５７】
ここで、Ｓ４００の多ドットマトリックス作成処理の詳細を、図５のフローチャートに示す。
図５に示すように、多ドットマトリックス作成処理の実行が開始されると、Ｓ４１０及びＳ４２０にて、前述した少ドットマトリックス作成処理のＳ３１０及びＳ３２０と全く同様の処理を行う。
【００５８】
即ち、まずＳ４１０にて、今回の処理対象となる２値マトリックスを特定するためのドット数番号ｉに、初期値として、上記基本マトリックスＦn のドット数である「ｎ」を設定する。次にＳ４２０にて、ワーキングメモリ１４の中から、ドット数がドット数番号ｉと一致する２値マトリックス（ｉドットの２値マトリックス）Ｆi を選択し、その２値マトリックスＦi に対して、前述した図４の粗密計算処理を実行することにより、当該２値マトリックスＦi について「１」である要素の粗密（ドットの粗密）を計算する。
【００５９】
そして、Ｓ４２０にて図４に示した粗密計算処理の実行が終了すると、Ｓ４６０に進んで、粗密計算処理が行われた後の処理対象マトリックスＳＭi の全要素の内で最小値を有する要素の位置を、２値マトリックスＦi にて「１」の要素が最も粗である位置（ドットが最も粗な位置）と判断し、更に、２値マトリックスＦi において、「１」の要素が最も粗である位置と判断した位置の要素の値を「０」から「１」に変更することで、２値マトリックスＦi よりも「１」の要素が１つ多い（ｉ＋１）ドットの２値マトリックスＦi+1 を作成し、その２値マトリックスＦi+1 をワーキングメモリ１４に保存する。
【００６０】
その後、続くＳ４７０にて、ドット数番号ｉの値を１つ増加させ（インクリメントし）、続くＳ４８０にて、ドット数番号ｉの値が全要素数ｋ以下であるか否かを判定する。ここで、ドット数番号ｉの値が未だｋ以下であれば、Ｓ４２０に戻り、ドット数が今回のドット数番号ｉに一致する２値マトリックスＦi （つまり、前回のＳ４６０で新たに作成した２値マトリックスＦi+1 ）を今回の処理対象として、前述したＳ４２０〜Ｓ４７０の処理を繰り返す。そして、Ｓ４８０にて、ドット数番号ｉがｋ以下でないと判定すれば、当該多ドットマトリックス作成処理を終了する。
【００６１】
つまり、多ドットマトリックス作成処理では、少ドットマトリックス作成処理の場合とは逆に、今回選択した２値マトリックスＦi に対し図４の粗密計算処理を実行して得た処理対象マトリックスＳＭi の全要素の内で、最小値を有する要素の位置を、２値マトリックスＦi にて「１」の要素が最も粗である位置と判断し、２値マトリックスＦi において、その位置の要素の値を「０」から「１」に変更することで、２値マトリックスＦi よりも「１」の要素が１つ多い２値マトリックスＦi+1 を作成する、という処理を繰り返すようにしている。
【００６２】
例えば、基本マトリックスＦn が、図８（ａ）に例示したように、全要素数ｋが２５（＝５×５）で、ドット数ｎが８であった場合について説明する。
この場合、多ドットマトリックス作成処理（図５）のＳ４２０では、少ドットマトリックス作成処理の場合と同様に、まず基本マトリックスＦn が、最初に処理対象としての２値マトリックスＦ8 として選択され、その２値マトリックスＦ8 に対して図４の粗密計算処理が実行される。そして、前述した様に、粗密計算処理のＳ３２７で上記２値マトリックスＦ8 をコピーして作られる処理対象マトリックスＳＭ8 の各要素の値は、図８（ｂ）の様な値となる。
【００６３】
すると、多ドットマトリックス作成処理のＳ４６０では、処理対象マトリックスＳＭ8 の全要素の内で最小値（ｍｉｎ）である「−０．２８」の要素の位置を、２値マトリックスＦ8 にて「１」の要素が最も粗である位置と判断し、図８（ｅ）の○印で示すように、２値マトリックスＦ8 において、上記の如く「１」の要素が最も粗である位置と判断した位置の要素の値を「０」から「１」に変更することで、「１」の要素が９個の（９ドットの）２値マトリックスＦ9 を作成する。
【００６４】
そして、新たに作成した２値マトリックスＦ9 に対しても、Ｓ４２０及びＳ４６０の処理を実行することで、「１」の要素が１０個の（１０ドットの）２値マトリックスＦ10を作成し、以後同様に処理を繰り返すことで、図８（ｆ）に示すように、全ての要素が「１」である２値マトリックスＦ25（＝Ｆk ）まで作成するのである。
【００６５】
よって、図２のＳ４００にて、多ドットマトリックス作成処理の実行が終了すると、基本マトリックスＦn よりも「１」の要素が１つずつ多い（ｋ−ｎ）個の２値マトリックスＦn+1 〜Ｆk が新たに作成され、この結果、ワーキングメモリ１４内には、図９に示すように、基本マトリックスＦn を含めて、全要素が「０」である２値マトリックスＦ0 から全要素が「１」である２値マトリックスＦkまでの、（ｋ＋１）個の２値マトリックスＦ0 〜Ｆk が保存される。
【００６６】
こうして多ドットマトリックス作成処理の実行を終えると、図２に示す如くＳ５００に進む。そして、このＳ５００にて、ワーキングメモリ１４内の全ての２値マトリックスＦ0 〜Ｆk について、同一位置の要素の２値化値を合計し、この合計値を要素とする集積結果マトリックスＭを形成する。即ち、全ての２値マトリックスＦ0 〜Ｆk の各要素位置について、その値を合計し、その合計値を、図１０に示す如くワーキングメモリ１４内に用意された集積結果マトリックスＭの同一位置に格納するのである。
【００６７】
そして、続くＳ６００にて、集積結果マトリックスＭの合計値の大きい要素位置から順に、ディザマトリックス用の閾値を設定し、続くＳ７００にて、その閾値からなるマトリックスをディザマトリックスとして、ディザマトリックス格納メモリ１６に保存した後、当該ディザマトリックス作成処理を終了する。
【００６８】
尚、Ｓ６００での閾値の設定は、例えば以下の様に行われる。
まず、集積結果マトリックスＭの合計値の大きい要素位置から順に番号を付けると、その番号は、１〜１６３８４（＝１２８×１２８＝ｋ）となり、全ての２値マトリックスＦ0 〜Ｆk において「１」の要素が１つずつ増加していく要素位置に対応する。また、２値化処理する中間調画像の各画素の濃度値は、前述したように０〜２５５の２５６階調である。
【００６９】
そこで、Ｓ６００では、上記番号の順に、例えば、番号が１〜６４（＝１６３８４／２５６）の要素位置については、ディザマトリックス用の閾値として「０」を設定し、番号が６５〜１２８の要素位置については、閾値として「１」を設定し、番号が１２９〜１９２の要素位置については、閾値として「２」を設定し、・・・、番号が１６２５７〜１６３２０の要素位置については、閾値として「２５４」を設定し、番号が１６３２１〜１６３８４の要素位置については、閾値として「２５５」を設定するといった具合いに、番号が小さい要素位置から順に閾値を大きく設定していくのである。
【００７０】
また、Ｓ６００では、上述とは逆に、番号が１〜６４の要素位置では、閾値として「２５５」を設定し、番号が６５〜１２８の要素位置では、閾値として「２５４」を設定し、・・・、番号が１６２５７〜１６３２０の要素位置については、閾値として「１」を設定し、番号が１６３２１〜１６３８４の要素位置については、閾値として「０」を設定するといった具合いに、番号が小さい要素位置から順に閾値を小さく設定していくようにしても良い。
【００７１】
尚、本実施の形態では、図３に示した少ドットマトリックス作成処理のＳ３２０及びＳ３６０が、第１のマトリックス生成処理に相当し、図５に示した多ドットマトリックス作成処理のＳ４２０及びＳ４６０が、第２のマトリックス生成処理に相当している。そして、少ドットマトリックス作成処理のＳ３２０及び多ドットマトリックス作成処理のＳ４２０で夫々実行される図４の粗密計算処理が、拡散処理に相当している。
【００７２】
以上詳述したように、本実施の形態のディザマトリックス作成装置２では、まず、均一濃度画素マトリックスを、誤差拡散法により２値化処理することで、ｎドット（「１」の要素がｎ個）の基本マトリックスＦn を生成するようにしている（Ｓ１００，Ｓ２００）。
【００７３】
そして、ｉドットの２値マトリックスＦi について、「１」の要素が最も密である位置に存在する要素の値を「１」から「０」に置換することで、「１」の要素が１つ少ない新たな２値マトリックスＦi-1 を生成するＳ３２０及びＳ３６０の処理を、上記基本マトリックスＦn を最初の２値マトリックスＦi として、繰り返し行うことにより、基本マトリックスＦn よりも「１」の要素が１つずつ少ないｎ個の２値マトリックスＦn-1 〜Ｆ0 を生成し（Ｓ３００）、また、ｉドットの２値マトリックスＦi について、「１」の要素が最も粗である位置に存在する要素の値を「０」から「１」に置換することで、「１」の要素が１つ多い新たな２値マトリックスＦi+1 を生成するＳ４２０及びＳ４６０の処理を、上記基本マトリックスＦn を最初の２値マトリックスＦi として、繰り返し行うことにより、基本マトリックスＦn よりも「１」の要素が１つずつ多い（ｋ−ｎ）個の２値マトリックスＦn+1 〜Ｆk を生成している（Ｓ４００）。
【００７４】
よって、上記Ｓ３２０及びＳ３６０の繰り返しにより生成される２値マトリックスＦn-1 〜Ｆ0 において「１」から「０」に順次置換されていく要素の位置、及び、上記Ｓ４２０及びＳ４６０の繰り返しにより生成される２値マトリックスＦn+1 〜Ｆk において「０」から「１」に順次置換されていく要素の位置は、特定の領域に偏ることなく適度に分散することとなり、この結果、上記処理の繰り返しにより生成された複数のマトリックスＦ0 〜Ｆn-1， Ｆn+1 〜Ｆk と、これらマトリックスの元となる基本マトリックスＦn とを、図９に示す如く「１」の要素が少ないものから順に配列させれば、各マトリックスＦ0 〜Ｆk は、「１」の要素が、全くのランダムではないが不規則に分散して順次１つずつ増えていくものとなる。
【００７５】
そこで、本実施の形態のディザマトリックス作成装置２では、基本マトリックスＦn と、上記の如く生成した２値マトリックスＦ0 〜Ｆn-1，Ｆn+1 〜Ｆk と、からなるマトリックス群に基づいて、ディザマトリックスにおける各要素の閾値を設定している（Ｓ５００〜Ｓ７００）。
【００７６】
このため、ディザマトリックスの各要素における閾値は、特定の値に偏ることが無く、ランダムともならず、更に各種の値に適度に分散して分布するものとなる。
そして、このように作成したディザマトリックスを用いて、中間調のカラー画像を２値化処理し、出力部１９（カラープリンタ）にて記録したところ、人間の目に対してノイジーとならず、かつ解像度が悪化せず、紋様の発生が抑制された疑似中間調の２値化画像を生成することができた。勿論、画像の２値化処理時はディザ法であり、誤差拡散法のように多数の計算は行わないので、迅速に処理することができた。
【００７７】
そして特に、本実施の形態では、前述したＳ３２０，Ｓ４２０にて、図４の粗密計算処理を実行することにより、２値マトリックスＦi をコピーした処理対象マトリックスＳＭi の各要素について、図７の拡散配分マトリックスに基づく式１，２の演算を順次行い、全要素の平均値が２値マトリックスＦi の全要素の平均値Ｈi とほぼ一致するように、２値マトリックスＦi の各要素の値を他の要素の値に拡散させた処理対象マトリックスＳＭi を得るようにしている。
【００７８】
そして、前述したＳ３６０では、粗密計算処理が行われた後の処理対象マトリックスＳＭi の全要素の内で最大値を有する要素の位置を、２値マトリックスＦi にて「１」の要素が最も密である位置と判断し、前述したＳ４６０では、粗密計算処理が行われた後の処理対象マトリックスＳＭi の全要素の内で最小値を有する要素の位置を、２値マトリックスＦi にて「１」の要素が最も粗である位置と判断するようにしている。
【００７９】
従って、本実施の形態によれば、２値マトリックスＦi にて「１」の要素が最も密である位置、あるいは最も粗である位置を、人間の主観に頼ることなく、定量的且つ確実に検出することができ、この結果、上述したように解像度の低下，目障りな紋様の発生，及びノイジー性を抑制可能なディザマトリックスを、経験や勘を必要とせずに極めて簡単に作成することができる。
【００８０】
しかも、本実施の形態によれば、基本マトリックスＦn （２値マトリックスＦi ）のマトリックスサイズが大きくても、前述したＳ３６０，Ｓ４６０の処理にて、「１」の要素の粗密を確実に判断できるため、大きなサイズのディザマトリックスを容易に作成でき、一層大きな効果を得ることができる。
【００８１】
即ち、ディザマトリックスの大きさよりも広い中間調画像を２値化する場合には、画像の部分部分を順次、ディザマトリックスの大きさの領域毎に２値化処理することになるが、この場合、ディザマトリックスのサイズが小さいと、２値化後の画像上に、ディザマトリックスを繰り返して用いることに起因する一定パターンの紋様が現れ易くなってしまう。これに対して、本実施の形態によれば、１２８×１２８といった大きなサイズのディザマトリックスを簡単に作成することができるため、このような問題を解決することができるのである。
【００８２】
［実施の形態２］
次に、実施の形態２として、前述した少ドットマトリックス作成処理（図３）のＳ３２０、及び多ドットマトリックス作成処理（図５）のＳ４２０にて、走査方向が異なる複数の粗密計算処理を実行する、ディザマトリックス作成装置について説明する。尚、以下では、前述した実施の形態１に対して異なる点についてのみ説明する。
【００８３】
まず、本実施の形態２において、図３のＳ３２０及び図５のＳ４２０では、ワーキングメモリ１４の中からドット数がドット数番号ｉと一致する２値マトリックスＦi を選択すると、その２値マトリックスＦi に対し、図４に示した粗密計算処理を、図１１にてＮｏ．１〜Ｎｏ．８で示される８種類の拡散配分マトリックス及び走査方向（つまり、注目要素を順次選択する主走査方向ｘ，副走査方向ｙ）に基づき、合計８回実行する。そして、この８回の実行により、２値マトリックスＦi の各要素の値を、Ｎｏ．１〜Ｎｏ．８の走査方向で夫々拡散させた、８個の処理対象マトリックスＳＭ１i 〜ＳＭ８i を作成する。
【００８４】
尚、図１１に示すＮｏ．１の拡散配分マトリックス及び走査方向は、実施の形態１のものと同じである。また、他のＮｏ．２〜Ｎｏ．８は、Ｎｏ．１に対して、走査方向（主走査方向ｘ，副走査方向ｙ）が夫々異なっており、それに応じて拡散配分マトリックスにおける各重み付け係数α１〜α４の注目要素位置「＊」に対する配置順が異なっている。そして、Ｎｏ．１〜Ｎｏ．８の拡散配分マトリックス及び走査方向に夫々基づいて実行される各粗密計算処理のＳ３３５では、対応する拡散分配マトリックスにて、注目要素位置「＊」から見て重み付け係数α１〜α４が設定されている位置の要素が、周辺要素として選択される。
【００８５】
即ち、Ｓ３２０及びＳ４２０で１回目に実行される粗密計算処理（図４）では、そのＳ３２７にて、２値マトリックスＦi をコピーして第１の処理対象マトリックスＳＭ１i を作る。そして、Ｓ３３０にて、図１１のＮｏ．１に示す如く、実施の形態１の場合と同様に、処理対象マトリックスＳＭ１i の左上の位置を原点とし、その原点からはじめて右方向を主走査方向ｘ，下方向を副走査方向ｙとして、各要素を注目要素として順次選択することにより、２値マトリックスＦiの各要素の値を、右方向を主走査方向ｘ，下方向を副走査方向ｙとして拡散させた処理対処マトリックスＳＭ１i を得る。
【００８６】
一方、２回目に実行される粗密計算処理では、Ｓ３２７にて、２値マトリックスＦi をコピーして第２の処理対象マトリックスＳＭ２i を作り、Ｓ３３０にて、図１１のＮｏ．２に示す如く、処理対象マトリックスＳＭ２i の右上の位置を原点とし、その原点からはじめて左方向を主走査方向ｘ，下方向を副走査方向ｙとして、各要素を注目要素として順次選択する。そして、これにより、２値マトリックスＦi の各要素の値を、左方向を主走査方向ｘ，下方向を副走査方向ｙとして拡散させた処理対処マトリックスＳＭ２i を得る。
【００８７】
また、３回目に実行される粗密計算処理では、Ｓ３２７にて、２値マトリックスＦi をコピーして第３の処理対象マトリックスＳＭ３i を作り、Ｓ３３０にて、図１１のＮｏ．３に示す如く、処理対象マトリックスＳＭ３i の左下の位置を原点とし、その原点からはじめて右方向を主走査方向ｘ，上方向を副走査方向ｙとして、各要素を注目要素として順次選択する。そして、これにより、２値マトリックスＦi の各要素の値を、右方向を主走査方向ｘ，上方向を副走査方向ｙとして拡散させた処理対処マトリックスＳＭ３i を得る。
【００８８】
また更に、４回目〜８回目に実行される粗密計算処理でも、上記と同様に、Ｓ３２７の夫々にて、２値マトリックスＦi をコピーして処理対象マトリックスＳＭ４i ないしＳＭ８i を作り、Ｓ３３０にて、図１１のＮｏ．４〜Ｎｏ．８に夫々示す走査方向の順で、処理対象マトリックスＳＭ４i ないしＳＭ８i の各要素を注目要素として順次選択する。これにより、２値マトリックスＦi の各要素の値をＮｏ．４〜Ｎｏ．８の走査方向で夫々拡散させた処理対処マトリックスＳＭ４i 〜ＳＭ８i を得る。
【００８９】
そして、本実施の形態２において、図３のＳ３６０及び図５のＳ４６０では、前述の如く粗密計算処理を８回実行して得た８個の処理対象マトリックスＳＭ１i 〜ＳＭ８i について、各要素の値を同一位置の要素毎に平均した平均値を算出し、その平均値に基づき、２値マトリックスＦi にて「１」の要素が最も密である位置、あるいは「１」の要素が最も粗である位置を判断する。
【００９０】
即ち、図３のＳ３６０では、算出した平均値が最も大きい要素の位置を、２値マトリックスＦi にて「１」の要素が最も密である位置と判断し、図４のＳ４６０では、算出した平均値が最も小さい要素の位置を、２値マトリックスＦi にて「１」の要素が最も粗である位置と判断するのである。
【００９１】
以上のように、本実施の形態２においては、２値マトリックスＦi に対して、走査方向が異なる複数の粗密計算処理を実行し、その計算結果の平均値に基づいて、２値マトリックスＦi にて「１」の要素が最も密である位置あるいは最も粗である位置を判断するようにしている。
【００９２】
これは、前述した式１，２から明らかなように、粗密計算処理では、注目要素の値を既に補正した周辺要素の値に応じて補正していくようにしているため、同一の２値マトリックスＦi であっても、粗密計算処理の走査方向（つまり、注目要素を選択していく方向）が異なれば、各要素の補正後の値が変わり、延いては、「１」の要素が最も密であると判断される位置、あるいは最も粗であると判断される位置が変わってくるからである。
【００９３】
そして、本実施の形態２のように、走査方向が異なる複数の粗密計算処理を実行するようにすることで、２値マトリックスＦi にて「１」の要素が最も密である位置、あるいは最も粗である位置を、より確実に検出できるようになる。
［実施の形態３］
次に、実施の形態３について説明する。本実施の形態３のディザマトリックス作成装置では、前述した実施の形態２に対して、以下に述べる処理を更に追加して実行している。
【００９４】
まず、本実施の形態３において、図３のＳ３２０及び図５のＳ４２０では、ワーキングメモリ１４の中からドット数がドット数番号ｉと一致する２値マトリックスＦi を選択すると、図１２に示すように、その２値マトリックスＦi を複数個（本実施の形態では、６×６の合計３６個）配置してなる拡大処理対象マトリックスＦ′i を作成し、その作成した拡大処理対象マトリックスＦ′i に対して、前述した如く走査方向が夫々異なる８種類の粗密計算処理を実行する。そして更に、Ｓ３２０及びＳ４２０では、粗密計算処理を実行して得た計算結果のうち、図１２にて斜線で如く、拡大処理対象マトリックスＦ′i の中でほぼ中央に配置された１つの２値マトリックスＦi に対応する領域Ｒの各要素の値だけを、次の処理で用いる処理対象マトリックスＳＭ１i 〜ＳＭ８i として、ワーキングメモリ１４内に保存する。
【００９５】
すると、図３のＳ３６０では、Ｓ３２０で保存された上記領域Ｒに対応する処理対象マトリックスＳＭ１i 〜ＳＭ８i に基づき、２値マトリックスＦi にて「１」の要素が最も密である位置を判断し、図５のＳ４６０では、Ｓ４２０で保存された上記領域Ｒに対応する処理対象マトリックスＳＭ１i 〜ＳＭ８i に基づき、２値マトリックスＦi にて「１」の要素が最も粗である位置を判断することとなる。
【００９６】
そして、上述した処理を追加して行う本実施の形態３によれば、２値マトリックスＦi にて「１」の要素が最も密である位置、あるいは「１」の要素が最も粗である位置を、より一層確実に検出できるようになる。
つまり、既述したように、粗密計算処理のＳ３３０で注目要素として選択された要素が、図６にて斜線で示したように当該粗密計算処理が主走査方向ｘと副走査方向ｙとに夫々最初に実行される領域（先頭要素ライン部）に存在する要素であった場合には、その注目要素に対する全ての周辺要素が存在しないため、その存在しない周辺要素の値としては、予め定められた所定値（例えば「０」）が用いられる。
【００９７】
よって、このように粗密計算処理が開始される先頭要素ライン部分やそれに近い領域では、各要素の値が十分且つ正確に他の要素の値へ拡散されなくなり、この結果、上記先頭要素ライン部分やそれに近い領域に関しては、「１」の要素の粗密を適切に判断することができない場合が生じてしまう。
【００９８】
そこで、本実施の形態３では、「１」の要素の粗密を計算すべき２値マトリックスＦi を複数個配置してなる拡大処理対象マトリックスＦ′i に対して、粗密計算処理を実行し、その計算結果のうち、上記先頭要素ライン部分やそれに近い領域を全く含まない領域（即ち、本実施の形態３では、拡大処理対象マトリックスＦ′i の中でほぼ中央に配置された２値マトリックスＦi に対応する領域Ｒ）についての計算結果を用いて、「１」の要素の粗密を判断するようにしており、この結果、２値マトリックスＦi にて「１」の要素が最も密である位置、あるいは最も粗である位置を、より一層確実に検出できるのである。そして、これにより、解像度の低下，目障りな紋様の発生，及びノイジー性を抑制可能なディザマトリックスを、常に安定して作成することが可能となる。
【図面の簡単な説明】
【図１】 実施の形態１のディザマトリックス作成装置の主要ブロック図である。
【図２】 実施の形態１のディザマトリックス作成処理を表すフローチャートである。
【図３】 図２のディザマトリックス作成処理で実行される少ドットマトリックス作成処理を表すフローチャートである。
【図４】 実施の形態１の粗密計算処理を表わすフローチャートである。
【図５】 図２のディザマトリックス作成処理で実行される多ドットマトリックス作成処理を表すフローチャートである。
【図６】 実施の形態１の注目要素「＊」に対する周辺要素の配置説明図である。
【図７】 実施の形態１の拡散分配マトリックスの構成説明図である。
【図８】 図３の少ドットマトリックス作成処理及び図５の多ドットマトリックス作成処理の作用を説明する説明図である。
【図９】 実施の形態１でワーキングメモリに保存される２値マトリックスの説明図である。
【図１０】 実施の形態１の集積結果マトリックスの説明図である。
【図１１】 実施の形態２の粗密計算処理を説明する説明図である。
【図１２】 実施の形態３の粗密計算処理を説明する説明図である。
【符号の説明】
２…ディザマトリックス作成装置 １０…入力部
１１…マイクロコンピュータ部 １２…ＣＰＵ １３…プログラムメモリ
１４…ワーキングメモリ １６…ディザマトリックス格納メモリ
１７…出力イメージメモリ １８…システムバス １９…出力部[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a method of creating a dither matrix for converting a multi-value image into a binary image.
[0002]
[Prior art]
The data constituting the image is usually expressed in shades of about 8 bits. However, in a device that outputs this image data as an image that can be seen by humans, for example, an output device such as a printer, a dye such as ink is used as dots on recording paper because of its simple mechanism and ease of control. So-called binary recording, in which only the attachment is performed, is common.
[0003]
When using such a binary recording output device to record an image expressed in 8-bit grayscale, whether or not to apply ink by simply judging the value of each pixel based on a threshold value. Will be determined. However, by simply binarizing with the threshold value in this way, the rich shade state possessed by the 8-bit shade gradation (256 gradations for one color and 256 gradations for each of the three primary colors, approximately 16.7 million colors) can be obtained. It is impossible to express. For this reason, a method of expressing a shaded state in a pseudo manner in such a binary recording output device has been considered. In other words, this is the concept of area gradation in which shading is expressed by the number of dots arranged in a predetermined area.
[0004]
Various proposals have been made as methods for realizing this concept. For example, an error diffusion method, a random number generation type dither method, a systematic dither method, or the like.
[0005]
[Problems to be solved by the invention]
However, these methods have the following problems.
The error diffusion method has a problem that the binarization process is slowed down because an operation for error diffusion or error distribution must be executed for each pixel. Since the random number generation type dither method uses a dither matrix in which threshold values for each element position are arranged, the binarization process itself is fast, but since the threshold values are determined using random numbers, the threshold values in each element are completely different. There is a problem that the image quality is very noisy, that is, the image quality is such that a lot of noise is filled with the image.
[0006]
As another method using the dither matrix, there is a spiral type belonging to the systematic dither method. However, since this spiral type moves the threshold order from the closest pixel position, the dots are likely to be dense and dense. Since it was recognized as a large dot, the resolution was easily lowered. Further, among the systematic dither methods, there is a Bayer method. In this Bayer method, the order of threshold values is shifted from a pixel position as far as possible, so that dots are dispersed and resolution is good. However, the dispersion pattern of the dots became regular, and an unsightly pattern was likely to occur.
[0007]
The present invention creates a dither matrix capable of suppressing generation of a pattern without causing an image to become noisy or a decrease in resolution even when image processing is performed using a dither method. The purpose is to provide a method.
[0008]
[Means for solving the problems and effects of the invention]
In the dither matrix creating method of the present invention according to claim 1,
In a binary matrix in which each element is binarized in advance to a first predetermined value or a second predetermined value smaller than the first predetermined value, the position where the set state of elements having the first predetermined value is the most dense (in other words, Then, the position of the element having the second predetermined value is detected at the most rough position), and the value of the element existing at the position is replaced from the first predetermined value to the second predetermined value. A first matrix generation process for generating a new matrix having one less element having a first predetermined value than the value matrix;
By using a predetermined basic matrix prepared in advance as the first binary matrix and repeatedly using the generated new matrix as the next binary matrix, an element having a first predetermined value over the basic matrix Generate multiple matrices with one less
Further, in a binary matrix in which each element is binarized in advance to a first predetermined value or a second predetermined value smaller than the first predetermined value, the set state of elements having the first predetermined value is the coarsest (In other words, the position where the set state of the elements having the second predetermined value is the densest) is detected, and the value of the element existing at that position is replaced from the second predetermined value to the first predetermined value, A second matrix generation process for generating a new matrix having one more element having a first predetermined value than the binary matrix;
By using the basic matrix as the first binary matrix and repeatedly using the generated new matrix as the next binary matrix, one element having a first predetermined value than the basic matrix is obtained one by one. Generate multiple matrices,
Based on a matrix group consisting of a plurality of matrices generated by repeating the first and second matrix generation processes and the basic matrix, Sum the binarized values of the elements at the same position, starting from the element with the largest total value. Set a threshold for each element in the dither matrix.
[0009]
Here, each of the plurality of matrices generated by repeating the first matrix generation process as described above is not formed independently, but in a matrix having one element having the first predetermined value more than itself. It is formed by replacing the value of the element existing at the position where the set state of the elements having the first predetermined value is the most dense from the first predetermined value to the second predetermined value, and from the first predetermined value to the second The positions of the elements that are sequentially replaced with the predetermined value are appropriately dispersed without being biased toward a specific region.
[0010]
Similarly, each of the plurality of matrices generated by repeating the second matrix generation process as described above is not independently formed, but is a matrix having one less element having the first predetermined value than itself. Is formed by replacing the value of the element existing at the position where the aggregate state of the elements having the first predetermined value is the coarsest from the second predetermined value with the first predetermined value, and from the second predetermined value to the first predetermined value. 1 The positions of elements that are sequentially replaced with a predetermined value are moderately dispersed without being biased toward a specific region.
[0011]
As a result, a plurality of matrices generated by repetition of the first and second matrix generation processes and the basic matrix that is the basis of these matrices are, for example, in order from the smallest number of elements having the first predetermined value. If arranged, the elements having the first predetermined value in each matrix are not random at all, but are irregularly distributed and sequentially increased one by one.
[0012]
For this reason, when a threshold value of each element in the dither matrix is set based on a matrix group composed of a plurality of matrices generated by repeating the first and second matrix generation processes and the basic matrix, each element of the dither matrix The thresholds in are not biased to specific values, are not random, and are distributed in various values in a moderately distributed manner, and the resolution decreases even when image processing is performed using the dither matrix that is formed. In addition, annoying patterns are suppressed, and it is not random, so it is not noisy.
[0013]
By the way, in the first and second matrix generation processes, when the position where the set state of the elements having the first predetermined value is the densest or the coarsest is detected, the denseness is determined by human subjectivity. It is conceivable to determine a certain position or a rough position. However, if this is done, the criteria for determining the density will be ambiguous. In particular, if the size of the matrix (the total number of elements) is large, the density cannot be determined.
[0014]
Therefore, in particular, in the first and second matrix generation processes in the dither matrix creation method of the present invention,
Each element of the matrix to be processed is sequentially selected as a target element in the order of a predetermined scanning direction, and the value of the selected target element is determined according to the value of a peripheral element existing in a predetermined peripheral position when viewed from the target element By correcting, the value of each element of the processing target matrix is changed to the other element so that the average value of all the original elements of the processing target matrix and the average value of all the elements after the correction substantially match. A diffusion process for diffusing to the value of is performed on the binary matrix,
Furthermore, in the first matrix generation process, the position of the element having the maximum value among all the elements corrected by the diffusion process is expressed as the set state of the elements having the first predetermined value in the binary matrix. In the second matrix generation process, the position of the element having the minimum value among all the elements corrected by the diffusion process is detected as the first predetermined value in the binary matrix. Is detected as a position where the set state of the elements having the roughest is the most rough.
[0015]
In other words, in the present invention, the value of each element of the binary matrix is changed to the value of the other element so that the average value of all the original elements of the binary matrix and the average value of all the elements after correction are substantially the same. Performing a diffusion process to diffuse, and determining the position of the element having the largest value after correction (after diffusion) as the position where the set state of the elements having the first predetermined value is the densest in the binary matrix; Conversely, the position of the element having the smallest value after correction (after diffusion) is determined to be the position where the set state of the elements having the first predetermined value is the coarsest in the binary matrix.
[0016]
Therefore, according to the dither matrix creation method of the present invention, the position where the set state of the elements having the first predetermined value is the densest or the coarsest position in the binary matrix can be determined without depending on human subjectivity. Quantitative and reliable detection. As a result, as described above, a dither matrix capable of suppressing the reduction in resolution, the generation of annoying patterns, and noisiness can be created very easily without requiring experience or intuition.
[0017]
Moreover, according to the present invention, even if the size of the basic matrix (binary matrix) is large, it is possible to reliably determine the density of elements having the first predetermined value in the first and second matrix generation processes. As a result, a dither matrix having a large size can be easily created, and a greater effect can be obtained.
[0018]
That is, when binarizing an image wider than the size of the dither matrix, the partial portion of the image is sequentially binarized for each area of the dither matrix size. If the size of the pattern is small, a pattern having a certain pattern due to repeated use of the dither matrix tends to appear on the binarized image. On the other hand, according to the present invention, a dither matrix having a large size can be easily created, so that such a problem can be solved.
[0019]
As the diffusion processing, as described in claim 2, each element of the processing target matrix is sequentially selected as a target element in the order of a predetermined scanning direction, and the target element is selected with respect to the value of the selected target element. A value obtained by multiplying a value of a peripheral element existing at one or a plurality of peripheral positions determined in advance by a predetermined weighting coefficient is added, and the average value of all the original elements of the processing target matrix is added. The value obtained by multiplying the sum of the coefficients can be reduced, and the value after the addition and subtraction can be stored as the corrected value of the element of interest.
[0020]
In other words, in order to correct the value of the element of interest according to the value of the peripheral element, basically, the value obtained by multiplying the value of the peripheral element by a predetermined weighting factor is added to the value of the target element. It is good, but if you just do this, the value of each element will only be corrected to be larger, and the average value of all elements after correction will be very large compared to the original average value of all elements. End up. Therefore, not only the above addition, but also the subtraction of subtracting the value obtained by multiplying the average value of all the original elements by the sum of the weighting coefficients of the respective peripheral elements, so that all the original elements of the processing target matrix (binary matrix) are obtained. The value of each element of the binary matrix can be diffused to the value of the other element while the average value of the elements and the average value of all the elements after correction are substantially matched.
[0021]
On the other hand, in the first and second matrix generation processes, as described in claim 3, a plurality of diffusion processes with different scanning directions are executed on the binary matrix, and the respective diffusion processes are executed. Based on the average value obtained by averaging the values of each element obtained for each element at the same position, the position where the set state of the elements having the first predetermined value is the densest or the coarsest is detected in the binary matrix. You may make it do.
[0022]
This is because even if the same binary matrix is used, if the scanning direction of the diffusion process (that is, the direction in which the element of interest is selected) is different, the corrected value of each element changes, and as a result, the first This is because the position where the element having the predetermined value is detected as being the densest or the position where the element is detected as being the coarsest changes. Then, as described in claim 3, by performing a plurality of diffusion processes with different scanning directions, and averaging the values of each element obtained by executing each of the diffusion processes for each element at the same position, In the binary matrix, it is possible to more reliably detect the position where the aggregate state of the elements having the first predetermined value is the densest or the coarsest.
[0023]
On the other hand, in the first and second matrix generation processes, as described in claim 4, the diffusion process is performed on an expanded matrix in which a plurality of binary matrices are arranged, and the diffusion process is performed. Among the values of the elements obtained by executing the first predetermined value in the binary matrix based on the values of the elements in the region corresponding to the binary matrix that does not include the head element line portion for which the diffusion processing has been started. You may make it detect the position where the assembly state of the element which has a value is the densest or the coarsest.
[0024]
This is because the value of each element is not sufficiently diffused in the head element line portion where the spreading process has been started or in the region close thereto, in other words, regarding the head element line portion and the region close thereto, This is because there is a possibility that the density of the element having the first predetermined value cannot be properly determined.
[0025]
Then, if processing is performed as set forth in claim 4, the value of each element of the binary matrix is made substantially equal to the average value of all the original elements of the binary matrix and the average value of all the elements after correction. Based on the corrected value sufficiently diffused to the values of the other elements, the density of the elements having the first predetermined value can be determined. As a result, the set of elements having the first predetermined value in the binary matrix The position where the state is the densest or the coarsest can be detected more reliably. In particular, the combination of the process according to claim 3 and the process according to claim 4 is more reliable.
[0026]
By the way, in the dither matrix creating method according to claim 1 to claim 4, the basic matrix may be a random arrangement of elements having a first predetermined value and elements having a second predetermined value. As described in claim 5, if all elements are formed by performing error diffusion processing on a matrix having the same multivalue and binarizing each element into a first predetermined value or a second predetermined value A greater effect can be obtained.
[0027]
That is, the arrangement of the binary values (first predetermined value and second predetermined value) generated by the error diffusion method looks irregular at first glance, but is not random (random) at all. That is, there is a property that it is difficult to make a strong pattern but a noisy image. Then, by using the binary sequence generated by such an error diffusion method, the dither matrix finally incorporates the characteristics of the binary sequence in the error diffusion method to some extent. Therefore, it is possible to further enhance the effect that the resolution is not lowered, an unobtrusive pattern does not occur, and the human eye is not noisy.
[0028]
Of course, when a basic matrix having elements having a first predetermined value and elements having a second predetermined value arranged at random is used, there is some concern about noisy, A plurality of new binary matrices that are not generated are generated, and a dither matrix is created based on these matrix groups, so that noisiness can be greatly reduced.
[0029]
DETAILED DESCRIPTION OF THE INVENTION
[Embodiment 1]
FIG. 1 is a main block diagram of the dither matrix creation device 2.
The microcomputer unit 11 constituting the main body of the dither matrix creating apparatus 2 includes a CPU 12, a program memory 13 composed of ROM, a working memory 14 composed of RAM, a dither matrix storage memory 16 composed of RAM, and an output image memory 17 composed of RAM. It is configured. An input unit 10 and an output unit 19 are connected to the microcomputer unit 11 via a system bus 18.
[0030]
The input unit 10 includes an interface for inputting from a keyboard or an external storage device, and inputs data and instructions necessary for creating a dither matrix. In addition, the input unit 10 inputs image data having a gradation in which each pixel is represented by 8 bits in order to confirm the effect of the created dither matrix.
[0031]
The CPU 12 is for executing creation of a dither matrix according to a program as will be described later, and the program memory 13 stores programs for performing various controls performed by the CPU 12, including a dither matrix creation program. . The working memory 14 temporarily stores data necessary for the CPU 12 to execute a program stored in the program memory 13.
[0032]
The dither matrix storage memory 16 stores dither matrix data formed by the processing of the CPU 12.
The output image memory 17 uses the dither matrix stored in the dither matrix storage memory 16 by the CPU 12 to binarize image data having a gradation represented by 8 bits. Store image data.
[0033]
The output unit 19 is a device (color printer) that prints binary image data stored in the output image memory 17 with or without dots by an electrophotographic method.
Next, a dither matrix creation process executed by the dither matrix creation device 2 will be described. A flowchart of the dither matrix creation process is shown in FIG. In this embodiment, the density value of one pixel is used for binarization processing of a halftone image represented by 256 gradations of 0 to 255, and the size (that is, the number of threshold values) is k ( For example, a dither matrix with k = 128 × 128) is created.
[0034]
As shown in FIG. 2, when the execution of the dither matrix generation process is started, first, in step (hereinafter simply referred to as “S”) 100, the number of pixels is k (= 128 × 128), and A uniform density pixel matrix in which all pixels are set to a predetermined uniform density value (for example, 70 when the maximum density value is 255) is read into the working memory 14, and the uniform density pixel matrix is binarized by an error diffusion method. To process.
[0035]
The error diffusion method referred to here is used in a broad sense. When a certain pixel is binarized, a binarization error is distributed to the density of surrounding pixels that have not yet been binarized (narrow). Meaning error diffusion method / literature: Robert W. Floyd and Louis Steinberg, "An Adaptive Algorithm for Spatial Greyscale", Proceeding of the SID Vol.17 / 2, 1976, etc.) A method of receiving a predetermined ratio of errors generated during binarization from already binarized pixels (also called the mean error minimum method. Reference: JFJarvis, CNJudice, and WHNinke, "A Survey of Techniques for the Display of Continuous Tone" Since Pictures on Bilevel Displays ", Computer Graphics and Image Processing.5, 13-40 (1976), etc.) are well known, detailed description of the error diffusion method itself is omitted.
[0036]
In the present embodiment, each pixel of the uniform density pixel matrix is binarized into either “1” (with dots = on) or “0” (without dots = off) by an error diffusion method. In the binary matrix after binarization, the number of elements “1” (hereinafter also referred to as the number of dots) is assumed to be n (0 <n <k). In the following description, for example, “n dots” indicates that the number of dots is n.
[0037]
Next, in the subsequent S200, the binary matrix obtained by the binarization process of S100 is stored in the working memory 14 as an n-dot binary matrix (hereinafter referred to as a basic matrix) Fn that is the basis of the following process. save.
In the subsequent S300, n binary matrices (that is, the basic matrix) from the binary matrix Fn-1 of (n-1) dots to the binary matrix F0 of 0 dots are based on the basic matrix Fn. A small dot matrix creating process for creating n binary matrices (Fn-1 to F0) each having one less "1" element than the matrix Fn is executed.
[0038]
Details of the small dot matrix creation processing in S300 are shown in the flowchart of FIG.
As shown in FIG. 3, when the execution of the small dot matrix creation process is started, first, in S310, the dot number number i for specifying the binary matrix to be processed this time is set as an initial value. “N” which is the number of dots of the basic matrix Fn is set.
[0039]
In the subsequent S320, a binary matrix (i-dot binary matrix) Fi having the number of dots matching the dot number number i is selected from the working memory 14, and the binary matrix Fi is shown in FIG. By executing the density calculation processing shown in FIG. 4, the density (dot density) of the element that is “1” is calculated for the binary matrix Fi. When the process of S320 is first executed, the dot number number i is set to “n” in S310, so that the binary matrix Fi of i dots is stored in the working memory 14 in S200. The saved basic matrix Fn is selected.
[0040]
Here, in the coarse / fine calculation processing of S320, as shown in FIG. 4, first, in S325, the average value Hi of all elements of the binary matrix Fi of i dots selected as the current processing target is calculated, and then to S327. Then, the selected binary matrix Fi is copied on the working memory 14, and a processing target matrix SMi identical to the binary matrix Fi is created. In this embodiment, since each element of the binary matrix is binarized to “1” or “0”, the average value Hi calculated in S325 is the number of dots i in the binary matrix Fi. Divided by the total number of elements k (i / k).
[0041]
In subsequent S330, the target element (x, y) is selected from the processing target matrix SMi created in S327, and the value of the target element (x, y) (that is, the original binarized value) Dx, Read y. In the present embodiment, as shown in FIG. 6, the upper left position of the processing target matrix SMi is the origin (0, 0), and starting from this origin (0, 0), the right direction is the main scanning direction x. Each element is sequentially selected as a target element, with the downward direction as the sub-scanning direction y.
[0042]
Next, in the subsequent S335, as shown in FIG. 6, four elements (x-1, y-) existing at four peripheral positions adjacent to the target pixel "*" (x, y) in the processing target matrix SMi. 1) Each of the above peripherals after (x, y-1), (x + 1, y-1), (x-1, y) are selected as peripheral elements and corrected by the process of S345 described later. The element values Dx-1, y-1, Dx, y-1, Dx + 1, y-1 and Dx-1, y are read from the working memory 14.
[0043]
Note that, as indicated by hatching in FIG. 6, the elements present in the region (first element line portion) where the coarse / fine calculation process is first executed in the main scanning direction x and the sub-scanning direction y are determined in S330. When the element of interest “*” is selected, all four peripheral elements do not exist. Therefore, in this case, as a value of a peripheral element that does not exist, a predetermined value (“0” in the present embodiment, but preferably an average value Hi of all elements) is used.
[0044]
Then, in subsequent S340, it is stored in advance in the program memory 13 or the working memory 14, and from the diffusion distribution matrix shown in FIG. 1), weighting coefficients α1 (= 2/16), α2 (= 4/16), α3 corresponding to (x, y−1), (x + 1, y−1), and (x−1, y), respectively. (= 3/16) and α4 (= 4/16) are read.
[0045]
In the subsequent S345, the average value Hi obtained in S325, the value of the element of interest (x, y) read in S330 (original binarized value) Dx, y, and the peripheral elements read in S335 are corrected. From the values Dx-1, y-1, Dx, y-1, Dx + 1, y-1, Dx-1, y, and the weighting factors α1, α2, α3, α4 of the peripheral elements read in S340, Based on Expression 1, a correction value D′ x, y of the element of interest (x, y) is calculated, and the correction value D′ x, y is calculated for the element of attention (x, y) as shown in Expression 2 below. The value is saved in the working memory 14 as the value Dx, y.
[0046]
[Expression 1]

[0047]
It should be noted that the value Dx, y of the current element of interest corrected in this way is the value after correction of the peripheral elements in S335 described above when another element is selected as the element of interest in S330. Will be read as
When the process of S345 is completed in this way, in subsequent S350, it is determined whether or not the process has been completed for all the elements of the process target matrix SMi. If there are any unprocessed elements, the process returns to S330 and the process target is processed. The process of S330 to S345 described above is repeated with the element of the next coordinate in the matrix SMi as the target element. If it is determined in S350 that the processes for all elements have been completed, the coarse / fine calculation process is terminated.
[0048]
In other words, in the coarse / fine calculation processing, the values Dx-1, y-1, Dx, y-1, Dx + 1, y-1, and Dx-1, y of the peripheral elements are set to the value Dx, y of the target element. A value obtained by multiplying a predetermined weighting coefficient α1, α2, α3, α4 is added, and a value obtained by multiplying the average value Hi of all the original elements of the processing target matrix SMi by the sum of weighting coefficients (α1 + α2 + α3 + α4) is added. And the operation of Equations 1 and 2 in which the value D′ x, y after the subtraction is stored as the corrected value Dx, y of the element of interest is the same as the processing target matrix SMi copied from the binary matrix Fi. Each element is executed sequentially.
[0049]
Then, the processing target matrix SMi after this coarse / fine calculation processing is performed is such that the average value of all elements substantially coincides with the average value Hi of all elements of the binary matrix Fi. This is a matrix in which values are diffused to the values of other elements.
[0050]
As described above, when the execution of the coarse / dense calculation process of FIG. 4 ends in S320 of the small dot matrix generation process, the process proceeds to S360 as shown in FIG.
In S360, the position of the element having the maximum value among all the elements of the processing target matrix SMi after the density calculation processing is performed, and the element "1" is the most dense in the binary matrix Fi. It is determined that there is a certain position (the dot is the densest position), and further, in the binary matrix Fi, the value of the element at the position where the element “1” is determined to be the densest is changed from “1” to “0”. By making the change, a binary matrix Fi-1 having (i-1) dots, which is one less than the binary matrix Fi, is created, and the binary matrix Fi-1 is stored in the working memory 14. To do.
[0051]
Thereafter, in the subsequent S370, the value of the dot number number i is decreased by 1 (decremented), and in the subsequent S380, it is determined whether or not the value of the dot number number i is greater than zero. If the value of the dot number number i is still larger than 0, the process returns to S320, and the binary matrix Fi whose dot number matches the current dot number number i (that is, the binary newly created in the previous S360). The above-described processing of S320 to S370 is repeated with the matrix Fi-1) as the current processing target. If it is determined in S380 that the dot number number i is not greater than 0, the small dot matrix creation process is terminated.
[0052]
Therefore, when this small dot matrix creation process is completed, the working memory 14 stores the above-mentioned basic matrix Fn and n binary matrices Fn-1 to n elements, each of which is one less than the basic matrix Fn. F0 is saved.
[0053]
Here, in order to simplify the description, the basic matrix Fn stored in S200 has a total number of elements k of 25 (= 5 × 5) and a number of dots n of 8 as shown in FIG. 8A, for example. The case will be described.
In this case, in S320 of the small dot matrix creation process (FIG. 3), the basic matrix Fn is first selected as the binary matrix F8 as the processing target, and the coarse / fine calculation process of FIG. 4 is performed on the binary matrix F8. Is executed. Then, the value of each element of the processing object matrix SM8 produced by copying the binary matrix F8 in S327 of the coarse / fine calculation process finally becomes a value as shown in FIG.
[0054]
In S360 following the small dot matrix creation process, the position of the element of “0.73” which is the maximum value (max) among all the elements of the processing target matrix SM8 is set to “1” in the binary matrix F8. It is judged that the element of is the densest position. In S360, as indicated by a circle in FIG. 8C, the value of the element at the position where the element "1" is determined to be the most dense position as described above in the binary matrix F8 is "1". By changing from “0” to “0”, a binary matrix F7 having 7 elements (1 dot) is created.
[0055]
Thereafter, the processing of S320 and S360 is also executed for the newly created binary matrix F7 to create a binary matrix F6 having 6 elements (1 dot), and so on. By repeating this process, as shown in FIG. 8D, a binary matrix F 0 in which all elements are “0” is created.
[0056]
As described above, when the small dot matrix creating process is executed to create n binary matrices Fn-1 to F0 each having one less "1" element than the basic matrix Fn, as shown in FIG. The process proceeds to S400.
At S400, this time, (k−n) binary values from the (n + 1) dot binary matrix Fn + 1 to the k dot binary matrix Fk based on the basic matrix Fn. A multi-dot matrix creating process for creating a matrix (that is, (k−n) binary matrices having one more “1” element than the basic matrix Fn) one by one is executed.
[0057]
Here, the details of the multi-dot matrix creation process of S400 are shown in the flowchart of FIG.
As shown in FIG. 5, when the execution of the multi-dot matrix creation process is started, the same processing as S310 and S320 of the small dot matrix creation process described above is performed in S410 and S420.
[0058]
That is, first in S410, “n”, which is the number of dots of the basic matrix Fn, is set as an initial value to the dot number number i for specifying the binary matrix to be processed this time. Next, in S420, a binary matrix (i-dot binary matrix) Fi having the number of dots matching the dot number number i is selected from the working memory 14, and the binary matrix Fi has been described above. By executing the coarse / fine calculation process of FIG. 4, the coarse / fine (dot coarse / dense) of the element which is “1” is calculated for the binary matrix Fi.
[0059]
When the execution of the coarse / fine calculation process shown in FIG. 4 is completed in S420, the process proceeds to S460, and the position of the element having the minimum value among all the elements of the processing target matrix SMi after the coarse / fine calculation process is performed. Is determined as the position where the element “1” is the coarsest in the binary matrix Fi (the position where the dot is the coarsest), and the position where the element “1” is the coarsest in the binary matrix Fi. By changing the value of the element at the determined position from “0” to “1”, a binary matrix Fi + 1 having (i + 1) dots having one more “1” element than the binary matrix Fi is created. Then, the binary matrix Fi + 1 is stored in the working memory 14.
[0060]
Thereafter, in the subsequent S470, the value of the dot number number i is incremented by 1 (incremented), and in the subsequent S480, it is determined whether or not the value of the dot number number i is equal to or less than the total number of elements k. If the value of the dot number number i is still less than or equal to k, the process returns to S420 and the binary matrix Fi whose dot number matches the current dot number number i (that is, the binary newly created in the previous S460). The processing of S420 to S470 described above is repeated with the matrix Fi + 1) as the current processing target. If it is determined in S480 that the dot number number i is not less than or equal to k, the multi-dot matrix creation process is terminated.
[0061]
That is, in the multi-dot matrix creation process, contrary to the small-dot matrix creation process, all the elements of the processing target matrix SMi obtained by executing the coarse / fine calculation process of FIG. 4 on the binary matrix Fi selected this time are used. In the binary matrix Fi, the position of the element having the minimum value is determined to be the position where the element of “1” is the coarsest, and the value of the element at that position is changed from “0” in the binary matrix Fi. By changing to “1”, the process of creating a binary matrix Fi + 1 having one more “1” element than the binary matrix Fi is repeated.
[0062]
For example, the case where the basic matrix Fn has a total number of elements k of 25 (= 5 × 5) and the number of dots n is 8 as illustrated in FIG. 8A will be described.
In this case, in S420 of the multi-dot matrix creation process (FIG. 5), as in the case of the small-dot matrix creation process, first, the basic matrix Fn is first selected as the binary matrix F8 to be processed, and its binary value is selected. The coarse / fine calculation process of FIG. 4 is performed on the matrix F8. As described above, the values of the respective elements of the processing target matrix SM8 produced by copying the binary matrix F8 in the coarse / dense calculation process S327 are as shown in FIG. 8B.
[0063]
Then, in S460 of the multi-dot matrix creation process, the position of the element “−0.28” that is the minimum value (min) among all the elements of the processing target matrix SM8 is set to “1” in the binary matrix F8. The element is determined to be the most rough position, and as indicated by the circle in FIG. 8 (e), in the binary matrix F8, the element at the position where the element "1" is determined to be the roughest position as described above. By changing the value of “0” from “0” to “1”, a binary matrix F9 having nine (9 dots) elements is created.
[0064]
Then, by executing the processing of S420 and S460 for the newly created binary matrix F9, a binary matrix F10 with 10 elements (1 dot) is created, and so on. By repeating the process, the binary matrix F25 (= Fk) in which all elements are "1" is created as shown in FIG. 8 (f).
[0065]
Therefore, when the execution of the multi-dot matrix creation process is completed in S400 of FIG. 2, (k−n) binary matrices Fn + 1 to Fk, each having one more “1” element than the basic matrix Fn. As a result, as shown in FIG. 9, in the working memory 14, all elements including the basic matrix Fn are “1” from the binary matrix F0 having all elements “0”. Up to a certain binary matrix Fk, (k + 1) binary matrices F0 to Fk are stored.
[0066]
When the execution of the multi-dot matrix creation process is completed in this way, the process proceeds to S500 as shown in FIG. In S500, the binarized values of the elements at the same position are summed for all the binary matrices F0 to Fk in the working memory 14, and an integration result matrix M having the sum as an element is formed. That is, the values for all element positions of all binary matrices F0 to Fk are summed, and the total value is stored in the same position of the integration result matrix M prepared in the working memory 14 as shown in FIG. It is.
[0067]
Subsequently, in S600, threshold values for the dither matrix are set in order from the element position with the largest total value of the accumulation result matrix M, and in S700, the dither matrix storage memory 16 uses the matrix composed of the threshold values as a dither matrix. Then, the dither matrix creation process is terminated.
[0068]
The setting of the threshold value in S600 is performed as follows, for example.
First, when numbers are assigned in order from the element positions having the largest total value in the accumulation result matrix M, the numbers become 1 to 16384 (= 128 × 128 = k), and “1” in all the binary matrices F0 to Fk. It corresponds to the element position where the element increases by one. Further, the density value of each pixel of the halftone image to be binarized is 256 gradations from 0 to 255 as described above.
[0069]
Therefore, in S600, in the order of the above numbers, for example, for the element positions with numbers 1 to 64 (= 16384/256), “0” is set as the threshold for the dither matrix, and the element positions with numbers 65 to 128 are set. Is set to “1” as the threshold value, “2” is set as the threshold value for the element positions with numbers 129 to 192,..., And the threshold value is set to “2” for the element positions with numbers 16257 to 16320. “254” is set, and the element positions with numbers 16321 to 16384 are set in such a manner that “255” is set as the threshold value, and the threshold value is set in order from the element position with the smallest number.
[0070]
Also, in S600, contrary to the above, “255” is set as the threshold for the element positions with numbers 1 to 64, and “254” is set as the threshold for the element positions with numbers 65 to 128. .. For elements positions with numbers 16257 to 16320, “1” is set as the threshold value, and for element positions with numbers 16321 to 16384, “0” is set as the threshold value. You may make it set a threshold value small sequentially from a position.
[0071]
In the present embodiment, S320 and S360 of the small dot matrix creation process shown in FIG. 3 correspond to the first matrix generation process, and S420 and S460 of the multi-dot matrix creation process shown in FIG. This corresponds to the second matrix generation process. The coarse / fine calculation processing of FIG. 4 executed in S320 of the small dot matrix creation processing and S420 of the multi-dot matrix creation processing corresponds to the diffusion processing.
[0072]
As described above in detail, in the dither matrix creation device 2 of the present embodiment, first, the uniform density pixel matrix is binarized by the error diffusion method, so that n dots (n elements of “1” are included). ) Is generated (S100, S200).
[0073]
Then, in the i-dot binary matrix Fi, the value of the element existing in the position where the element of “1” is the densest is replaced from “1” to “0”, so that one element of “1” is obtained. By repeating the processes of S320 and S360 for generating a small new binary matrix Fi-1 with the basic matrix Fn as the first binary matrix Fi, there is one "1" element than the basic matrix Fn. N binary matrices Fn-1 to F0 which are smaller by one are generated (S300), and the value of the element existing at the position where the element of "1" is the coarsest is obtained for the binary matrix Fi of i dots. By replacing “0” with “1”, the processing of S420 and S460 for generating a new binary matrix Fi + 1 having one more “1” element is performed, and the basic matrix Fn is replaced with the first binary. As trix Fi, by repeating, it has generated one by one element of "1" than the basic matrix Fn often (k-n) pieces of binary matrix Fn + 1 ~Fk (S400).
[0074]
Therefore, in the binary matrixes Fn-1 to F0 generated by repeating S320 and S360, the positions of elements that are sequentially replaced from "1" to "0", and generated by repeating S420 and S460. In the binary matrixes Fn + 1 to Fk, the positions of the elements that are sequentially replaced from “0” to “1” are moderately dispersed without being biased toward a specific region, and as a result, are generated by repeating the above processing. If the plurality of matrixes F0 to Fn-1, Fn + 1 to Fk and the basic matrix Fn which is the basis of these matrices are arranged in order from the one with the smallest number of elements "1" as shown in FIG. In each matrix F0 to Fk, the elements of "1" are not random at all, but are irregularly distributed and sequentially increased one by one.
[0075]
Therefore, in the dither matrix creating apparatus 2 of the present embodiment, the dither matrix is based on the matrix group consisting of the basic matrix Fn and the binary matrices F0 to Fn-1 and Fn + 1 to Fk generated as described above. The threshold value of each element is set (S500 to S700).
[0076]
For this reason, the threshold value in each element of the dither matrix is not biased to a specific value, is not random, and is distributed appropriately distributed in various values.
Then, using the dither matrix created in this way, a halftone color image is binarized and recorded by the output unit 19 (color printer). It was possible to generate a pseudo-halftone binary image in which the resolution was not deteriorated and the generation of patterns was suppressed. Of course, the binarization processing of the image is a dither method, and since many calculations are not performed unlike the error diffusion method, the image can be processed quickly.
[0077]
In this embodiment, in particular, in the above-described S320 and S420, the coarse / dense calculation process of FIG. 4 is executed, so that each element of the processing target matrix SMi copied from the binary matrix Fi is diffused and distributed as shown in FIG. The operations of Equations 1 and 2 based on the matrix are sequentially performed, and the value of each element of the binary matrix Fi is changed to the other elements so that the average value of all the elements substantially matches the average value Hi of all the elements of the binary matrix Fi The processing object matrix SMi diffused to the value of is obtained.
[0078]
In S360 described above, the position of the element having the maximum value among all the elements of the processing target matrix SMi after the density calculation processing is performed, and the element of “1” is the most dense in the binary matrix Fi. In S460 described above, the position of the element having the minimum value among all the elements of the processing target matrix SMi after the coarse / dense calculation process is performed is set to the element “1” in the binary matrix Fi. Is determined to be the roughest position.
[0079]
Therefore, according to the present embodiment, the position where the element “1” is the densest or the coarsest in the binary matrix Fi is quantitatively and reliably detected without depending on human subjectivity. As a result, as described above, a dither matrix capable of suppressing a decrease in resolution, generation of an unsightly pattern, and noisiness can be created very easily without requiring experience or intuition.
[0080]
In addition, according to the present embodiment, even if the matrix size of the basic matrix Fn (binary matrix Fi) is large, the density of the element “1” can be reliably determined by the processing of S360 and S460 described above. A dither matrix having a large size can be easily created, and a greater effect can be obtained.
[0081]
That is, when binarizing a halftone image wider than the size of the dither matrix, the partial portions of the image are sequentially binarized for each area of the dither matrix size. If the size of the dither matrix is small, a pattern with a certain pattern due to repeated use of the dither matrix tends to appear on the binarized image. On the other hand, according to the present embodiment, a dither matrix having a large size of 128 × 128 can be easily created, so that such a problem can be solved.
[0082]
[Embodiment 2]
Next, as the second embodiment, a plurality of density calculation processes with different scanning directions are executed in S320 of the small dot matrix creation process (FIG. 3) and S420 of the multidot matrix creation process (FIG. 5). A dither matrix creation device will be described. In the following, only differences from the first embodiment will be described.
[0083]
First, in the second embodiment, in S320 of FIG. 3 and S420 of FIG. 5, when a binary matrix Fi whose dot number matches the dot number number i is selected from the working memory 14, the binary matrix Fi is selected. On the other hand, the coarse / fine calculation processing shown in FIG. 1-No. This is executed a total of eight times based on the eight types of diffusion distribution matrixes indicated by 8 and the scanning direction (that is, the main scanning direction x and the sub-scanning direction y for sequentially selecting the target element). Then, by executing this eight times, the value of each element of the binary matrix Fi is changed to No. 1-No. Eight processing target matrices SM1i to SM8i are created by diffusing in the eight scanning directions.
[0084]
In addition, No. shown in FIG. 1 diffusion distribution matrix and the scanning direction are the same as those in the first embodiment. In addition, other No. 2-No. 8 is No.8. 1, the scanning direction (main scanning direction x, sub-scanning direction y) is different, and the arrangement order of the weighting coefficients α1 to α4 in the diffusion distribution matrix with respect to the target element position “*” differs accordingly. Yes. And No. 1-No. In S335 of each of the coarse / dense calculation processes executed based on each of the eight diffusion distribution matrices and the scanning direction, weighting coefficients α1 to α4 are set in the corresponding diffusion distribution matrix as viewed from the target element position “*”. A position element is selected as a peripheral element.
[0085]
That is, in the coarse / fine calculation processing executed in S320 and S420 for the first time (FIG. 4), in S327, the binary matrix Fi is copied to create the first processing target matrix SM1i. In S330, No. 1 in FIG. As shown in FIG. 1, as in the case of the first embodiment, the upper left position of the processing target matrix SM1i is the origin, and starting from the origin, the right direction is the main scanning direction x and the lower direction is the sub scanning direction y. Are sequentially selected as elements of interest to obtain a processing countermeasure matrix SM1i in which the values of the elements of the binary matrix Fi are diffused with the rightward direction as the main scanning direction x and the downward direction as the subscanning direction y.
[0086]
On the other hand, in the coarse / fine calculation processing executed for the second time, in S327, the binary matrix Fi is copied to create the second processing target matrix SM2i. As shown in FIG. 2, each element is sequentially selected as a target element, with the upper right position of the processing target matrix SM2i as the origin, the left direction as the main scanning direction x and the lower direction as the sub scanning direction y starting from the origin. Thus, a processing countermeasure matrix SM2i is obtained in which the values of the elements of the binary matrix Fi are diffused with the left direction as the main scanning direction x and the downward direction as the sub-scanning direction y.
[0087]
In the coarse / fine calculation processing executed for the third time, the binary matrix Fi is copied to create a third processing target matrix SM3i in S327, and in S330, No. 1 in FIG. 3, the lower left position of the processing target matrix SM3i is set as the origin, and from the origin, the right direction is the main scanning direction x, the upper direction is the sub scanning direction y, and each element is sequentially selected as a target element. Thus, a processing countermeasure matrix SM3i is obtained in which the values of the elements of the binary matrix Fi are diffused with the right direction as the main scanning direction x and the upward direction as the sub-scanning direction y.
[0088]
Further, in the coarse / fine calculation processing executed for the fourth time to the eighth time, similarly to the above, in S327, the binary matrix Fi is copied to create the processing target matrices SM4i to SM8i, and in S330, No. 11 no. 4-No. Each element of the processing object matrices SM4i to SM8i is sequentially selected as a target element in the order of the scanning direction shown in FIG. As a result, the value of each element of the binary matrix Fi is set to No. 4-No. The processing countermeasure matrices SM4i to SM8i diffused in the eight scanning directions are obtained.
[0089]
In the second embodiment, in S360 of FIG. 3 and S460 of FIG. 5, the values of the respective elements are set for the eight processing target matrices SM1i to SM8i obtained by executing the coarse / dense calculation process eight times as described above. An average value is calculated for each element at the same position, and based on the average value, the position where the element “1” is the densest or the position where the element “1” is the coarsest in the binary matrix Fi Judging.
[0090]
That is, in S360 of FIG. 3, the position of the element having the largest calculated average value is determined as the position where the element “1” is the densest in the binary matrix Fi, and in S460 of FIG. The position of the element having the smallest value is determined as the position where the element of “1” is the coarsest in the binary matrix Fi.
[0091]
As described above, in the second embodiment, a plurality of coarse / fine calculation processes with different scanning directions are performed on the binary matrix Fi, and the binary matrix Fi is used based on the average value of the calculation results. The position where the element “1” is the densest or the coarsest is determined.
[0092]
As is clear from the above-described equations 1 and 2, in the coarse / fine calculation process, the value of the element of interest is corrected according to the value of the peripheral element that has already been corrected. Even in the case of Fi, if the scanning direction of the density calculation process (that is, the direction in which the element of interest is selected) is different, the corrected value of each element changes, and the element “1” is the most dense. This is because the position determined to be or the position determined to be the coarsest changes.
[0093]
Then, by executing a plurality of coarse / fine calculation processes with different scanning directions as in the second embodiment, the position where the element “1” is the densest or the coarsest in the binary matrix Fi. It is possible to more reliably detect the position.
[Embodiment 3]
Next, Embodiment 3 will be described. In the dither matrix creating apparatus according to the third embodiment, the processing described below is further added to the above-described second embodiment and executed.
[0094]
First, in the third embodiment, in S320 of FIG. 3 and S420 of FIG. 5, when a binary matrix Fi whose dot number matches the dot number number i is selected from the working memory 14, as shown in FIG. Then, an enlargement processing target matrix F′i is formed by arranging a plurality of the binary matrices Fi (in this embodiment, a total of 36 × 6 × 6), and the created enlargement processing target matrix F′i On the other hand, as described above, eight types of coarse / fine calculation processes with different scanning directions are executed. Further, in S320 and S420, among the calculation results obtained by executing the coarse / fine calculation process, one binary value arranged almost at the center in the enlargement process target matrix F′i, as shown by the oblique line in FIG. Only the values of the respective elements in the region R corresponding to the matrix Fi are stored in the working memory 14 as processing target matrices SM1i to SM8i used in the next processing.
[0095]
Then, in S360 of FIG. 3, based on the processing target matrices SM1i to SM8i corresponding to the region R stored in S320, the position where the element of “1” is the densest in the binary matrix Fi is determined. In S460 of No. 5, based on the processing target matrices SM1i to SM8i corresponding to the region R stored in S420, the position where the element “1” is the coarsest in the binary matrix Fi is determined.
[0096]
Then, according to the third embodiment which is performed by adding the above-described processing, the position where the element “1” is the densest or the position where the element “1” is the coarsest in the binary matrix Fi. , It becomes possible to detect more reliably.
That is, as described above, the element selected as the element of interest in S330 of the coarse / fine calculation process is processed by the coarse / fine calculation process in the main scanning direction x and the sub-scanning direction y, respectively, as indicated by hatching in FIG. If it is an element that exists in the area to be executed first (first element line part), since there are not all peripheral elements for the element of interest, the value of the peripheral element that does not exist is determined in advance. A predetermined value (for example, “0”) is used.
[0097]
Therefore, in the head element line portion where the coarse / fine calculation processing is started in this way or in an area close thereto, the value of each element is not sufficiently and accurately diffused to the value of the other element. For a region close to that, the density of the element “1” cannot be appropriately determined.
[0098]
In the third embodiment, therefore, a coarse / fine calculation process is performed on an enlargement processing target matrix F′i in which a plurality of binary matrices Fi for calculating the coarse / fine of the element “1” are arranged. Of the calculation results, the area that does not include the head element line portion or the area close thereto (that is, in the third embodiment, the binary matrix Fi arranged almost at the center in the enlargement processing target matrix F′i). The calculation result for the corresponding region R) is used to determine the density of the element “1”. As a result, the position where the element “1” is the densest in the binary matrix Fi, or The most rough position can be detected more reliably. As a result, it is possible to always stably create a dither matrix capable of suppressing a reduction in resolution, occurrence of an unsightly pattern, and noisiness.
[Brief description of the drawings]
FIG. 1 is a main block diagram of a dither matrix creating apparatus according to a first embodiment.
FIG. 2 is a flowchart showing a dither matrix creation process according to the first embodiment.
FIG. 3 is a flowchart showing a small dot matrix creation process executed in the dither matrix creation process of FIG. 2;
FIG. 4 is a flowchart showing a coarse / fine calculation process according to the first embodiment.
FIG. 5 is a flowchart showing a multi-dot matrix creation process executed in the dither matrix creation process of FIG.
FIG. 6 is an explanatory diagram of arrangement of peripheral elements with respect to a target element “*” according to the first embodiment.
7 is a configuration explanatory diagram of a diffusion distribution matrix according to Embodiment 1. FIG.
FIG. 8 is an explanatory diagram for explaining the operation of the small dot matrix creation process of FIG. 3 and the multi-dot matrix creation process of FIG. 5;
FIG. 9 is an explanatory diagram of a binary matrix stored in the working memory in the first embodiment.
10 is an explanatory diagram of an integration result matrix according to Embodiment 1. FIG.
FIG. 11 is an explanatory diagram for explaining coarse / dense calculation processing according to the second embodiment;
FIG. 12 is an explanatory diagram for explaining coarse / dense calculation processing according to the third embodiment;
[Explanation of symbols]
2 ... Dither matrix creation device 10 ... Input section
11 ... Microcomputer part 12 ... CPU 13 ... Program memory
14 ... Working memory 16 ... Dither matrix storage memory
17 ... Output image memory 18 ... System bus 19 ... Output unit

Claims (5)

For a binary matrix in which each element is binarized in advance to a first predetermined value or a second predetermined value smaller than the first predetermined value, a position where the set state of elements having the first predetermined value is the densest is detected. Then, by replacing the value of the element existing at that position from the first predetermined value to the second predetermined value, a new matrix that has one element having the first predetermined value less than the binary matrix is generated. 1 matrix generation processing is performed by repeatedly using a predetermined basic matrix prepared in advance as the first binary matrix and using the generated new matrix as the next binary matrix. Generating a plurality of matrices having one element each having a first predetermined value,
Further, in a binary matrix in which each element is binarized in advance to a first predetermined value or a second predetermined value smaller than the first predetermined value, the set state of elements having the first predetermined value is the coarsest And a new matrix having one more element having the first predetermined value than the binary matrix is generated by replacing the value of the element existing at that position with the first predetermined value from the second predetermined value. The second matrix generation process is performed repeatedly by using the basic matrix as the first binary matrix and using the generated new matrix as the next binary matrix. Generate multiple matrices with one element each having a predetermined value,
Based on a matrix group consisting of a plurality of matrices generated by repeating the first and second matrix generation processes and the basic matrix, the binarized values of elements at the same position are summed, and the total value A dither matrix creation method for setting a threshold value of each element in a dither matrix in order from an element having a larger size ,
In the first and second matrix generation processes,
Each element of the matrix to be processed is sequentially selected as a target element in the order of a predetermined scanning direction, and the value of the selected target element is determined according to the value of a peripheral element existing in a predetermined peripheral position when viewed from the target element By correcting, the value of each element of the processing target matrix is changed to the other element so that the average value of all the original elements of the processing target matrix and the average value of all the elements after the correction substantially match. A diffusion process for diffusing to the value of is performed on the binary matrix,
Furthermore, in the first matrix generation process,
Detecting the position of the element having the maximum value among all the elements corrected by the diffusion process as the position where the set state of the elements having the first predetermined value is the densest in the binary matrix;
In the second matrix generation process,
Detecting the position of the element having the minimum value among all the elements corrected by the diffusion processing as the position where the set state of the elements having the first predetermined value is the coarsest in the binary matrix;
A dither matrix creation method characterized by The diffusion process is
A value obtained by multiplying a value of a peripheral element existing at one or a plurality of predetermined peripheral positions as viewed from the target element by a predetermined weighting coefficient is added to the value of the selected target element. A process of subtracting a value obtained by multiplying the average value of all the original elements of the processing target matrix by the sum of the weighting coefficients and storing the value after the addition and subtraction as the corrected value of the element of interest. ,
The method of creating a dither matrix according to claim 1. In the first and second matrix generation processes,
Based on an average value obtained by averaging the values of each element obtained by executing each of the diffusion processes for each element at the same position, while executing a plurality of the diffusion processes with different scanning directions for the binary matrix Detecting a position in which a set state of elements having the first predetermined value is the densest or the coarsest in the binary matrix;
The dither matrix creating method according to claim 1, wherein: In the first and second matrix generation processes,
The first element line portion where the diffusion processing is started among the values of each element obtained by executing the diffusion processing on the enlarged matrix formed by arranging a plurality of binary matrices. Detecting a position in which a set state of elements having the first predetermined value is the densest or coarsest in the binary matrix based on the value of each element in the region corresponding to the binary matrix not including
The dither matrix creating method according to claim 1, wherein: The basic matrix is formed by performing error diffusion processing on a matrix having all the same multivalues and binarizing each element into a first predetermined value or a second predetermined value,
The dither matrix creating method according to claim 1, wherein:

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