JP3998321B2 - Image processing method and apparatus - Google Patents

Description

【００３２】
そして、第１減算手段４４においては、原信号Ｓ_F から低周波数成分（低周波信号）Ｒ_L ，Ｇ_L ，Ｂ_L を減算して、中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHを抽出する。このように抽出された後の低周波数成分Ｒ_L ，Ｇ_L ，Ｂ_L はカラー画像中のエッジや細かいテクスチャやフィルムの粒状によるざらつきを含まないものである。一方、中間周波数成分Ｒ_M ，Ｇ_M ，Ｂ_M にはフィルムの粒状によるざらつきを含み、高周波数成分Ｒ_H ，Ｇ_H ，Ｂ_H はカラー画像中のエッジや細かいテクスチャを含むものである。
【００３３】
ここで、原信号の低周波数成分、中間周波数成分および高周波数成分とは、図３に示すように分布される後述する中間・高周波数成分に乗じるゲインＭ，Ｈを１．０とした場合の周波数成分のことをいうものであり、中間周波数成分Ｒ_M ，Ｇ_M ，Ｂ_M は、処理後のデータを可視像Ｐとして再生する際の出力のナイキスト周波数ｆ_S ／２の１／３付近にピークを持って分布Ｈ_M となる周波数成分をいうものであり、低周波数成分Ｒ_L ，Ｇ_L ，Ｂ_L とは、０周波数にピークを持って分布Ｈ_L となる成分をいい、高周波数成分Ｒ_H ，Ｇ_H ，Ｂ_H とは出力のナイキスト周波数ｆ_S ／２にピークを持って分布Ｈ_H となる成分をいうものである。なお、本実施形態においてナイキスト周波数は、記録媒体Ｚへの記録が３００ｄｐｉで行われる場合のナイキスト周波数をいうものである。ここで、図３においては、各周波数において周波数成分の和は１となっている。
【００３４】
次いで、輝度算出手段４６において、第１減算手段４４によって分解された中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHから輝度成分が抽出される。この輝度成分の抽出は原信号Ｓ_F の中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHをＹＩＱ規定に変換した際の成分Ｙ_MHがデータの輝度成分を表すものである。ここで、ＹＩＱ規定への変換は下記式（２）により行う。
【００３５】
【数２】

【００３６】
ここで、ＹＩＱ規定に変換後の色成分である成分Ｉ_MHおよび成分Ｑ_MHはフィルム粒状に起因する色のざらつきを含むものであるため、成分Ｉ_MHおよび成分Ｑ_MHはここでは０とおいてフィルム粒状に起因する色のざらつきを抑制する。ここで、色成分である成分Ｉ_MHおよび成分Ｑ_MHは一般の被写体を写した画像の場合は殆ど成分を持たないことが経験的に分かっている。したがって、成分Ｉ_MHおよび成分Ｑ_MHはフィルム粒状に起因する色のざらつきとみなして０とおくことにより、ざらつきを抑制した良好な再生画像を得ることができる。
【００３７】
次いで、成分Ｙ_MHに対して以下に示すような５×５の第２ＬＰＦ４８によってフィルタリング処理を施して、成分Ｙ_MHの中間周波数成分Ｙ_M を得る。
【００３８】
【数３】

【００３９】
さらに、第２減算手段５０において、成分Ｙ_MHから中間周波数成分Ｙ_M を減算することにより成分Ｙ_MHの高周波数成分Ｙ_H を得る。
【００４０】
一方、画像特性取得手段５２では、前述した演算部３０において求められたゲインＭ₀ およびゲインＨ₀ を調整する際に依存させる画像特性、例えば、コントラスト、コントラストのハイライト部およびシャドー部、特定画像濃度ならびにエッジなどが、原信号Ｓ_F （ＲＧＢ）に基づいて求められる。ここで、ゲインＭ₀ およびゲインＨ₀ を調整する際に依存させるのに用いる画像特性の種類は、１種であっても、２種以上であってもよい。また、ここで用いる画像特性の種類は、オペレータによってＣＲＴ３４などに入力され、ＣＲＴ３４からインターフェイス３６を経由して演算部３０に入力され、演算部３０から強調処理手段３８の画像特性取得手段に入力されたものであってもよいし、演算部３０において、ＣＲＴ３４からの入力信号に基づいて設定されるものであってもよいし、画像自体から自動的に設定されるものであってもよい。
取得手段５２において行われる、画像特性に応じた信号処理については、具体的な個々の画像特性に応じて後述する。
【００４１】
こうして、取得手段５２において、画像特性が取得されると、画像特性依存ゲイン算出手段５４では、前述した演算部３０において求められたゲインＭ₀ およびゲインＨ₀ を取得された画像特性に依存させて調整するための画像特性依存強度Ｗを設定する。ここで設定する画像特性依存強度Ｗは、画像や画像特性に応じてゲイン算出手段５４で設定するようにしてもよいが、ゲイン算出手段５４に設けられたメモリ（図示せず）などに予め強度関数や画像特性依存強度テーブル（ＬＵＴ）などに、好ましくは複数用意しておき、これらから画像や画像特性に応じて選択するようにしても良い。なお、予め強度関数や画像特性依存強度ＬＵＴなどは、演算部３０に用意しておき、必要な強度関数や画像特性依存強度ＬＵＴなどを受け取るようにしてもよい。
【００４２】
こうして、ゲイン算出手段５４において画像特性に応じて設定された画像特性依存強度Ｗが、それぞれ、演算部３０において求められたゲインＭ₀ およびゲインＨ₀ に下記式（３）に示すように乗じられて、中間周波数成分Ｙ_M を画像特性に依存させて抑制するための画像特性依存ゲインＭおよび高周波数成分Ｙ_H を画像特性に依存させて強調するための画像特性依存ゲインＨが算出される。
ゲインＭ＝ゲインＭ₀ ×Ｗ
ゲインＨ＝ゲインＨ₀ ×Ｗ ……（３）
ここで、演算部３０において、元々、フィルム粒状に基づく輝度成分のざらつきが比較的多く含まれている中間周波数成分Ｙ_M のゲインを比較的低く設定することにより、ざらつき感を抑え、画像の鮮鋭度が依存する輝度成分の高周波数成分Ｙ_H のゲインＨを比較的大きくすることにより、処理済画像の鮮鋭度を強調することができるように、ゲインＭ₀ とゲインＨ₀ とはゲインＭ₀ ＜ゲインＨ₀ となるように設定されている。従って、ゲイン算出手段５４で算出される画像特性依存ゲインＭとゲインＨとはゲインＭ＜ゲインＨとなるように設定される。
【００４３】
ところで、演算部３０においては、例えば、カラー画像ＣＩがアンダーネガの場合には、フィルム粒状に起因するざらつきが目立つうえに、階調特性を改善するために階調を立てた場合に粒状がかなり悪い画像となってしまうため、ゲインＭ₀ がかなり低く設定される。このため、ゲイン算出手段５４で画像特性に依存させてゲインＭもかなり低く設定される。そしてこれにより、画像特性に依存させて、粒状を強く抑制することができる。また、プリントサイズに依存しても演算部３０で最適なゲインＭ₀ およびゲインＨ₀ が設定される。さらに、前述したようにユーザがいくつかの鮮鋭度強調処理メニューから所望とするメニューを選択する場合には、このメニューに応じたゲインＭ₀ およびゲインＨ₀ をテーブルとして記憶しておき、メニュー選択に応じて最適なゲインＭ₀ およびゲインＨ₀ を選択できるようにしておくことが好ましい。これにより、画像ごとにあるいはユーザの好みに応じた処理を行うことができるようになる。
このように、演算部３０においてプリントサイズやユーザの好みに応じて最適なゲインＭ₀ およびゲインＨ₀ が設定されているので、ゲイン算出手段５４で画像特性に依存させて設定されるゲインＭおよびＨも最適なものとなるのはいうまでもない。
【００４４】
ところで、画像特性依存強度Ｗは、中間周波数成分抑制のためのゲインＭと高周波数成分強調のためのゲインＨとで、同一の画像特性依存強度を用いているけれども、本発明はこれに限定されず、ゲインＭとゲインＨとでそれぞれ異なる画像特性依存強度を用いてもよい。
なお、上述した実施形態おいては、基本となるゲインＭ₀およびゲインＨ₀は、演算部３０において算出または設定し、ゲイン算出手段５４において、まず画像特性依存強度Ｗを算出し、上記式（３）によって画像特性依存ゲインＭおよびゲインＨを算出しているが、本発明はこれに限定されず、基本となるゲインＭ₀およびゲインＨ₀を、演算部３０では求めず、ゲイン算出手段５４で直接求めるようにしてもよいし、さらに、基本となるゲインＭ₀およびゲインＨ₀および画像特性依存強度Ｗを求めることなく、直接、画像特性依存ゲインＭおよびゲインＨを算出するように構成してもよい。
【００４５】
次いで、下記式（４）に示すように、こうしてゲイン算出手段５４によって算出された画像特性依存ゲインＭおよびゲインＨが、それぞれ第１および第２アンプ５６および５８において、第２ＬＰＦ４８によって得られた成分Ｙ_MHの中間周波数成分Ｙ_M および第２減算手段５０によって得られた成分Ｙ_MHの高周波数成分Ｙ_H にそれぞれ乗じられて処理済成分Ｙ_M ´，Ｙ_H ´が得られる。
Ｙ_M ´＝ゲインＭ×Ｙ_M
Ｙ_H ´＝ゲインＨ×Ｙ_H ……（４）
続いて、第１加算手段６０において、下記式（５）に示すように、それぞれ第１および第２アンプ５６および５８で得られた処理済成分Ｙ_M ´およびＹ_H ´が合成されて、成分Ｙ_MH´が得られる。
Ｙ_MH´＝Ｙ_M ´＋Ｙ_H ´ ……（５）
（＝ゲインＭ×Ｙ_M ＋ゲインＨ×Ｙ_H ）
【００４６】
ここで、上述したように、ゲイン算出手段５４においてゲインＭとゲインＨとはゲインＭ＜ゲインＨとなるように設定されている。すなわち、フィルム粒状に基づく輝度成分のざらつきは、中間周波数成分に比較的多く含まれているため、成分Ｙ_M のゲインＭを画像特性に依存させて比較的低く設定することにより、画像特性に依存させて適切にざらつき感を抑えることができるものである。また、画像の鮮鋭度（シャープネス）は、輝度成分の高周波数成分に依存するため、輝度成分の高周波数成分Ｙ_H のゲインＨを画像特性に依存させて比較的大きくすることにより、処理済画像の鮮鋭度を画像特性に依存させて適切に強調することができるものである。
【００４７】
そして、第２加算手段６２において、このようにして得られた成分Ｙ_MH´を前述した原信号Ｓ_F の低周波数成分Ｒ_L ，Ｇ_L ，Ｂ_L と合成して処理済信号Ｒ´，Ｇ´，Ｂ´を得る。この際、前述した成分Ｉ_MHおよび成分Ｑ_MHの値は０とされているため、処理された輝度成分Ｙ_MH´を逆変換してＲＧＢのデータに対応させると、ＲＧＢ３つのデータは全て成分Ｙ_MH´と同一の値となる。したがって、処理された輝度成分Ｙ_MH´を逆変換しなくても合成した結果は、逆変換した場合と同一となる。よって、処理を簡便なものとするために処理された輝度成分Ｙ_MH´を逆変換しないで合成するようにしているのである。
その後、処理済信号Ｒ´，Ｇ´，Ｂ´は再生手段１６に入力され、プリンタ４０により記録材料Ｚに可視像Ｐとして再生される。
【００４８】
このようにして再生された再生可視像Ｐは、フィルム粒状に起因するざらつきを含むデータの中間・高周波数成分の色成分が０とされており、さらに、中間・高周波数成分の輝度成分のうち中間周波数成分Ｙ_M のゲインＭが画像特性に依存して抑制され、高周波数成分Ｙ_H のゲインＨが画像特性に依存して強調されているため、どのような画像であっても適切に鮮鋭度が強調されるとともにフィルム粒状に起因するざらつきが十分に抑制された画像となる。
【００４９】
次いで、本発明の画像処理方法を実施する本発明の画像処理装置の具体的な実施例について説明する。
図４〜７に示す粒状抑制シャープネス強調処理手段３８の実施例は、それぞれ画像特性が、コントラスト、コントラストのハイライト部およびシャドー部、特定画像濃度ならびにエッジである場合の画像特性取得手段５２および画像特性依存ゲイン算出手段５４の具体例を示すもので、これらを除いて、図２に示す粒状抑制シャープネス強調処理手段３８と同一であるので、同一の構成要素には同一の番号を付し、その説明は省略する。
【００５０】
まず、本発明の具体的第１実施例による画像処理装置の強調処理手段について説明する。図４（ａ）は、本発明の具体的第１実施例による画像処理装置の強調処理手段３８ａにおいて行われるコントラスト依存強調抑制処理の詳細を説明するためのブロック図である。
図４（ａ）に示すように、本発明の第１実施例による画像処理装置１４の強調処理手段３８ａは、画像特性としてコントラストを用いるもので、コントラストとして第１減算手段４４によって算出された原信号Ｓ_F と低周波数信号Ｒ_L ，Ｇ_L ，Ｂ_L との差信号である中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHを用い、この差信号Ｒ_MH，Ｇ_MH，Ｂ_MHから輝度算出手段４６によって算出された輝度成分（輝度信号）Ｙ_MHに依存して強調抑制処理をおこなうものである。従って、図４（ａ）に示す強調処理手段３８ａにおいては、分解手段を構成する第１減算手段４４および輝度算出手段４６は、図２に示す強調処理手段３８における画像特性取得手段５２に相当するコントラスト（信号）取得手段５２ａをも構成し、コントラスト依存ゲイン算出手段５４ａは、図２に示す画像特性依存ゲイン算出手段５４にとして機能するものである。
【００５１】
すなわち、コントラスト信号取得手段５２ａは、原信号Ｓ_Fと低周波信号Ｒ_L，Ｇ_L，Ｂ_L との差信号である中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHを算出する第１減算手段４４と、この差信号Ｒ_MH，Ｇ_MH，Ｂ_MHから上記式（２）に従って輝度信号Ｙ_MHを算出する輝度算出手段４６とから構成される。
また、ゲイン算出手段５４ａは、画像特性取得手段５２として機能する輝度算出手段４６によって取得された差信号（中間・高周波数成分）Ｒ_MH，Ｇ_MH，Ｂ_MHの輝度信号Ｙ_MHに依存する強度関数Ｗを、例えば図４（ｂ）に示すコントラスト依存テーブルのようにコントラストに依存させて、すなわち低コントラストで小さく、高コントラストで大きく設定することにより、この強度関数Ｗと基本となるゲインＭ₀およびゲインＨ₀とから上記式（３）によってゲインＭおよびＨを算出するものである。
なお、本実施例においては、コントラスト信号取得手段５２ａを第１減算手段４４および輝度算出手段４６によって構成し、ゲインＭおよびＨを、差信号（中間・高周波数成分）Ｒ_MH，Ｇ_MH，Ｂ_MHの輝度信号Ｙ_MHに依存して強度抑制処理を行っているが、本発明は、これに限定されず、コントラスト信号取得手段５２ａを第１減算手段４４のみによって構成し、ゲインＭおよびＨを、差信号（中間・高周波数成分）Ｒ_MH，Ｇ_MH，Ｂ_MH、例えばこれらの３色の平均値に依存して強度抑制処理を行ってもよい。
【００５２】
このように、本実施例においては、例えば、図４（ｂ）に示すようなコントラスト依存テーブルを用いるので、コントラストが高い場合、すなわち差信号の輝度信号Ｙ_MHの絶対値が大きい場合には、強度関数Ｗの値を１，０として、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ および高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ とする。これに対し、コントラストが低い場合、すなわち差信号の輝度信号Ｙ_MHの絶対値が小さい所定範囲の値の場合には、強度関数Ｗの値を１．０より小さくして、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ より、高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ より小さくする。
こうすることにより、本実施例においては、処理済成分Ｙ_M ´，Ｙ_H ´を低コントラスト部でさらに小さくして、最終的に得られる処理済信号Ｒ´，Ｇ´，Ｂ´から再生されるカラー画像の鮮鋭度を強調し、フィルムの粒状に基づくノイズ成分を除去するとともに、コントラストの低い平坦部分における粒状性をさらに抑制し、良好な画質の再生画像を得ることができる。
【００５３】
次いで、本発明の具体的第２実施例による画像処理装置の強調処理手段について説明する。図５（ａ）は、本発明の具体的第２実施例による画像処理装置の強調処理手段３８ｂにおいて行われるコントラスト依存方式によるハイライト部およびシャドー部依存強調抑制処理の詳細を説明するためのブロック図である。
図５（ａ）に示すように、本発明の第２実施例による画像処理装置１４の強調処理手段３８ｂは、画像特性としてコントラストを用い、コントラストのハイライト部およびシャドー部の各々を独立に操作するもので、コントラストとして第１減算手段４４によって算出された原信号Ｓ_F と低周波数信号Ｒ_L ，Ｇ_L ，Ｂ_L との差信号である中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHを用い、この差信号Ｒ_MH，Ｇ_MH，Ｂ_MHの正負によってコントラストのハイライト部およびシャドー部を判定または検出し、この差信号Ｒ_MH，Ｇ_MH，Ｂ_MHから輝度算出手段４６によって算出された輝度成分（輝度信号）Ｙ_MHの正負に依存して強調抑制処理をおこなうものである。
【００５４】
従って、図５（ａ）に示す強調処理手段３８ｂは、図４（ａ）に示す強調処理手段３８ａと、図２に示す強調処理手段３８における画像特性依存ゲイン算出手段５４に相当するハイライト／シャドー判定・ゲイン算出手段５４ｂが、コントラスト信号取得手段５２ａによって取得されたコントラストに相当する差信号またはその輝度信号のみならずコントラストのハイライト部およびシャドー部、すなわち差信号の正負またはその輝度信号の正負を判定し、判定されたハイライト部およびシャドー部（差信号やその輝度信号の正負）に依存して、コントラスト依存ゲイン算出手段５４ａにおけるゲインＭおよびゲインＨの値を調整する点を除いて全く同一に機能する。
すなわち、図５（ａ）に示す強調処理手段３８ｂにおいては、分解手段を構成する第１減算手段４４および輝度算出手段４６は、図４（ａ）に示す強調処理手段３８ａと同様に、図２に示す強調処理手段３８における画像特性取得手段５２に相当するコントラスト（信号）取得手段５２ａをも構成し、ハイライト／シャドー判定・ゲイン算出手段５４ｂは、図２に示す画像特性依存ゲイン算出手段５４として機能する。
【００５５】
ここで、ハイライト／シャドー判定・ゲイン算出手段５４ｂは、画像特性取得手段５２として機能する輝度算出手段４６によって取得された差信号（中間・高周波数成分）Ｒ_MH，Ｇ_MH，Ｂ_MHの輝度信号Ｙ_MHの正負を判定し、判定された輝度信号Ｙ_MHの正負に依存する強度関数Ｗを、例えば図５（ｂ）に示すコントラスト依存テーブルのようにコントラストならびにハイライト側およびシャドー側に依存させて、すなわち低コントラストで小さく、高コントラストのハイライト側で大きく、高コントラストのシャドー側でさらに大きく設定することにより、この強度関数Ｗと基本となるゲインＭ₀ およびゲインＨ₀ とから上記式（３）によってゲインＭおよびＨを算出するものである。
なお、本実施例においても、コントラスト信号取得手段５２ａを第１減算手段４４および輝度算出手段４６によって構成し、ゲインＭおよびＨを、差信号（中間・高周波数成分）Ｒ_MH，Ｇ_MH，Ｂ_MHの輝度信号Ｙ_MHの正負に依存して強度抑制処理を行っているが、本発明は、これに限定されず、コントラスト信号取得手段５２ａを第１減算手段４４のみによって構成し、ゲインＭおよびＨを、差信号（中間・高周波数成分）Ｒ_MH，Ｇ_MH，Ｂ_MHの正負、例えば、これらの３色の平均値の正負に依存して強度抑制処理を行ってもよい。
【００５６】
このように、本実施例においては、例えば、図５（ｂ）に示すようなコントラスト依存テーブルを用いるので、ハイライト側でコントラストが高い場合、すなわち差信号の輝度信号Ｙ_MHが正でその絶対値が大きい場合には、強度関数Ｗの値を１，０として、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ および高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ とし、シャドー側でコントラストが高い場合、すなわち差信号の輝度信号Ｙ_MHが負でその絶対値が大きい場合には、強度関数Ｗの値を１，０よりさらに大きくして、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ より、高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ よりさらに大きくする。これに対し、コントラストが低い場合、すなわち差信号の輝度信号Ｙ_MHの絶対値が小さい所定範囲の値の場合には、強度関数Ｗの値を１．０より小さくして、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ より、高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ より小さくする。
こうすることにより、本実施例においては、処理済成分Ｙ_M ´，Ｙ_H ´を低コントラスト部でさらに小さくするとともに、高コントラスト部のシャドー側では、高コントラスト部のハイライト側よりもさらに大きくして、最終的に得られる処理済信号Ｒ´，Ｇ´，Ｂ´から再生されるカラー画像の鮮鋭度を強調し、フィルムの粒状に基づくノイズ成分を除去するとともに、エッジ部の偽輪郭を防止し、良好な画質の再生画像を得ることができる。
【００５７】
続いて、本発明の具体的第３実施例による画像処理装置の強調処理手段について説明する。図６（ａ）は、本発明の具体的第３実施例による画像処理装置の強調処理手段３８ｃにおいて行われる特定濃度依存強調抑制処理の詳細を説明するためのブロック図である。
図６（ａ）に示すように、本発明の第３実施例による画像処理装置１４の強調処理手段３８ｃは、画像特性として特定濃度を用いるもので、特定濃度として原信号Ｓ_F の濃度信号（ＲＧＢ信号）を用い、この原信号Ｓ_F の濃度信号（ＲＧＢ）から算出された輝度成分（輝度信号）Ｙ_F に依存して強調抑制処理をおこなうものである。従って、図６（ａ）に示す強調処理手段３８ｃにおいては、原信号輝度算出手段５２ｃが図２に示す強調処理手段３８における画像特性取得手段５２として機能し、輝度信号依存ゲイン算出手段５４ｃは、図２に示す画像特性依存ゲイン算出手段５４にとして機能するものである。
【００５８】
すなわち、原信号輝度算出手段５２ｃは、原信号Ｓ_F の濃度信号（ＲＧＢ）から、前述したＹＩＱ規定への変換式（２）に従って輝度信号Ｙ_F を算出するものである。
また、ゲイン算出手段５４ｃは、画像特性取得手段５２として機能する原信号輝度算出手段５２ｃによって算出された輝度信号Ｙ_F に依存する強度関数Ｗを、例えば図６（ｂ）に示す輝度信号依存テーブルのように輝度信号に依存させて、すなわち輝度信号が所定値以下では大きく、輝度信号が所定値より大きくなるにつれて所定割合で単調に減少するように、すなわち特定濃度領域（特定輝度領域）では徐々に小さくなるように設定することにより、この強度関数Ｗと基本となるゲインＭ₀ およびゲインＨ₀ とから上記式（３）によってゲインＭおよびＨを算出するものである。
【００５９】
このように、本実施例においては、例えば、図６（ｂ）に示すような輝度信号依存テーブルを用いるので、輝度信号が所定値以下の場合には、強度関数Ｗの値を１．０として、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ および高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ とする。これに対し、輝度信号が所定値より大きい場合には、輝度信号が大きくなるにつれて、強度関数Ｗの値を１．０より０．０まで所定割合で単調に減少するように設定して、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ から、高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ から０．０まで所定割合で単調に小さくする。
こうすることにより、本実施例においては、処理済成分Ｙ_M ´，Ｙ_H ´を輝度信号が所定値より大きい特定濃度（輝度）領域ではさらに徐々に小さくして、最終的に得られる処理済信号Ｒ´，Ｇ´，Ｂ´から再生されるカラー画像の鮮鋭度を強調し、フィルムの粒状に基づくノイズ成分を除去するとともに、特定濃度領域における粒状性をさらに抑制し、良好な画質の再生画像を得ることができる。
【００６０】
なお、本実施例においては、原信号輝度算出手段５２ｃによって原信号Ｓ_F の濃度信号（ＲＧＢ）から輝度信号Ｙ_FHを算出し、この輝度信号Ｙ_FHに依存して強度抑制処理を行っているが、本発明は、これに限定されず、原信号輝度算出手段５２ｃを用いず、原信号Ｓ_F の濃度信号（ＲＧＢ）をそのまま用い、原信号Ｓ_F の濃度信号（ＲＧＢ）、例えばＲＧＢ濃度信号の平均値に依存して強度抑制処理を行ってもよい。この場合には、画像特性取得手段５２としては、強調処理手段３８ｃに入力された原信号Ｓ_F をそのまま濃度信号（ＲＧＢ）として用いて３色の平均値を求め、この３色の平均値を出力するものであればよい。
また、図示例においては、例えば、特定濃度領域として所定輝度値より大きい領域を設定し、図６（ｂ）に示すような輝度依存テーブルを用いているが、本発明はこれに限定されず、特定濃度領域としてどのような濃度（輝度）領域を設定しても良いし、また、どのような輝度依存テーブルを用いてもよい。
【００６１】
さらに、本発明の具体的第４実施例による画像処理装置の強調処理手段について説明する。図７（ａ）は、本発明の具体的第４実施例による画像処理装置の強調処理手段３８ｄにおいて行われるエッジ依存強調抑制処理の詳細を説明するためのブロック図である。
図７（ａ）に示すように、本発明の第３実施例による画像処理装置１４の強調処理手段３８ｄは、画像特性としてエッジを用いるもので、エッジとして低周波数成分抽出の対象としたマスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ij（ｉ：主走査方向の画素位置、ｊ：副走査方向の画素位置）の輝度信号Ｙ_ijの主副走査方向の差信号に依存して強調抑制処理をおこなうものである。従って、図７（ａ）に示す強調処理手段３８ｄにおいては、マスク内信号を構成するマスクメモリ５１およびエッジ検出手段５３は、図２に示す強調処理手段３８における画像特性取得手段５２に相当するエッジ信号取得手段５２ｄを構成し、エッジ依存ゲイン算出手段５４ｄは、図２に示す画像特性依存ゲイン算出手段５４にとして機能するものである。
【００６２】
すなわち、エッジ信号取得手段５２ｄは、原信号Ｓ_F からマスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijを抽出するマスクメモリ５１と、マスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijから輝度信号Ｙ_ijを抽出する輝度信号抽出手段と、この輝度信号の主副走査方向の差信号を算出する差信号算出手段とを有するエッジ検出手段５３とから構成される。ここで、エッジ検出手段５３の輝度信号抽出手段は、まず、マスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijの輝度信号Ｙ_ijを前述したＹＩＱ規定への変換式（２）によって算出する。次に、エッジ検出手段５３の差信号算出手段は、輝度信号Ｙ_ijの主副走査方向の差を検出エッジ（指数）Ｅとして、下記式（６）によって算出する。ここで、下記式（６）において、Ａ，Ｂ，Ｃ，Ｄは、図７（ｂ）に示すように、輝度信号Ｙ_ijに関する左右上下の画素値の和である。
Ｅ＝｜Ａ−Ｂ｜＋｜Ｃ−Ｄ｜ ……（６）
【００６３】
また、エッジ依存ゲイン算出手段５４ｄは、エッジ信号取得手段５２ｄのエッジ検出手段５３によって検出されたエッジＥに依存する強度関数Ｗを、例えば図７（ｃ）に示すように検出エッジＥに依存させて、すなわち検出エッジＥが小さい平坦部では小さく、検出エッジＥが大きいエッジ部では大きく設定することにより、この強度関数Ｗと基本となるゲインＭ₀ およびゲインＨ₀ とから上記式（３）によってゲインＭおよびＨを算出するものである。
なお、本実施例においては、エッジ信号取得手段５２ｄをマスクメモリ５１およびエッジ検出手段５３によって構成し、マスクメモリ５１によって原信号Ｓ_F から抽出対象マスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijを抽出し、このマスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijからエッジ検出手段５３によって前記式（２）に基づいて輝度信号Ｙ_ijを求め、得られた輝度信号Ｙ_ijに基づいて上記式（６）によってエッジＥを検出し、ゲインＭおよびＨを、輝度信号Ｙ_ijに基づく検出エッジＥに依存して強度抑制処理を行っているが、本発明は、これに限定されず、エッジ検出手段５３において前記式（２）による輝度信号Ｙ_ijを算出することなく、低周波数成分抽出の対象としたマスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijそのものの主副走査方向の差信号をエッジＥとして上記式（６）によって検出し、ゲインＭおよびＨを、この差信号に基づく検出エッジＥに依存して強度抑制処理を行ってもよい。この時、上記式（６）におけるＡ，Ｂ，Ｃ，Ｄは、図７（ｂ）に示すように、マスク内信号Ｒ_ij，Ｇ_ij，Ｂ_ijの平均値などに関する左右上下の画素値の和を用いればよい。
【００６４】
このように、本実施例においては、例えば、図７（ｃ）に示すようなエッジ依存テーブルを用いるので、エッジである場合、すなわち検出エッジＥの値が大きい場合には、強度関数Ｗの値を１，０として、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ および高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ とする。これに対し、エッジでない平坦部の場合、すなわち検出エッジＥの値が所定値以下（小さい所定範囲の値）の場合には、強度関数Ｗの値を１．０よりから０．０まで単調に減少させ、徐々に小さくして、中間周波数成分Ｙ_M のゲインＭを基本となるゲインＭ₀ より、高周波数成分Ｙ_H のゲインＨを基本となるゲインＨ₀ より小さくする。
こうすることにより、本実施例においては、処理済成分Ｙ_M ´，Ｙ_H ´を平坦部でさらに小さくして、最終的に得られる処理済信号Ｒ´，Ｇ´，Ｂ´から再生されるカラー画像の鮮鋭度を強調し、フィルムの粒状に基づくノイズ成分を除去するとともに、画像のエッジを検出し、エッジのみを強調し、鮮鋭度強調による平坦部におけるノイズをさらに抑制し、良好な画質の再生画像を得ることができる。
また、図示例においては、例えば、エッジとしてマスク内の左右上下の画素値の和により検出エッジＥの値を設定し、図７（ｃ）に示すようなエッジ依存テーブルを用いているが、本発明はこれに限定されず、エッジとしてどのような検出エッジＥの値を設定しても良いし、また、どのようなエッジ依存テーブルを用いてもよい。
【００６５】
以上、本発明の画像処理方法を実施する本発明の画像処理装置を構成する粒状抑制シャープネス強調処理手段について、画像特性が、それぞれコントラスト、コントラストのハイライト部およびシャドー部、特定画像濃度ならびにエッジである場合の具体的実施例について説明したが、本発明はこれに限定されず、その他の画像特性を用いてもよいことは勿論であり、画像特性に応じて画像特性取得手段および画像特性依存ゲイン算出手段を設定すればよい。
なお、上述した実施例においては、中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHをＹＩＱ規定に変換してゲイン処理を行うようにしているが、ＹＩＱ規定に変換する必要はなく、中間・高周波数成分Ｒ_MH，Ｇ_MH，Ｂ_MHを中間周波数成分Ｒ_M ，Ｇ_M ，Ｂ_M および高周波数成分Ｒ_H ，Ｇ_H ，Ｂ_H に分解し、各成分をＹＩＱ規定に変換することなくゲイン処理を施すようにしてもよいものである。但し、ＹＩＱ規定に変換後に、輝度成分にのみ基づいてゲイン処理を施した方が、フィルム粒状に起因するざらつきを大きく抑制することができる。
【００６６】
以上、本発明の画像処理方法および装置について詳細に説明したが、本発明は上記実施例に限定はされず、本発明の要旨を逸脱しない範囲において、各種の改良および変更を行ってもよいのはもちろんである。
【００６７】
【発明の効果】
以上詳細に説明したように、本発明による画像処理方法および装置は、画像信号を低・中間・高周波数成分に分解し、フィルム粒状に起因するざらつきを含む中間周波数成分を抑制し、エッジ、テクスチャ等を含む高周波数成分を強調する際に、中間周波数成分の抑制強度および高周波数成分の強調強度を画像特性、例えば、コントラスト、コントラストのハイライト部およびシャドー部、特定濃度、ならびにエッジに依存して調整するようにしたため、処理後の画像信号のカラー再生画像は、鮮鋭度が強調され、かつフィルム粒状に基づくノイズ成分を除去され、さらに平坦部分の粒状性が抑えられ、エッジ部の偽輪郭が防止され、特定濃度領域の粒状性が抑えられ、画像のエッジを検出し、エッジのみの鮮鋭度が強調された、良好な画質の再生画像を得ることができる。
【００６８】
また、本発明によれば、中間・高周波数成分の輝度成分についてのみ処理を行うことにより、フィルム粒状に基づく輝度成分のざらつきを抑制することができるため、さらに画質の良好な再生画像を得ることができる。
また、本発明によれば、カラー画像信号の中間・高周波数成分のＲＧＢ３色をＹＩＱ規定に変換した場合、色成分であるＩ成分およびＱ成分は通常の被写体では殆ど成分を持たないものであるため、Ｉ成分およびＱ成分はフィルム粒状に起因する色のざらつきとみなすことができる。したがって、画像信号から分解された高周波数成分および中間周波数成分の輝度成分であるＹ成分にのみ基づいて強調抑制処理および合成を行うことにより、さらに、フィルム粒状に起因する色のざらつきを抑制し、良好な再生画像を得ることができる。
【図面の簡単な説明】
【図１】 本発明に係る画像処理方法を実施する画像処理装置を適用したデジタルカラー画像再生システムの一実施形態のブロック図である。
【図２】 図１に示すデジタルカラー画像再生システムに適用される本発明の画像処理装置の一実施形態のブロック部である。
【図３】 カラー原画像信号の低・中間・高周波数成分の分布を表すグラフである。
【図４】 （ａ）は、図２に示す画像処理装置の具体的第１実施例のブロック図であり、（ｂ）は、（ａ）に示す画像処理装置に用いられるコントラスト依存テーブルの一例のグラフである。
【図５】 （ａ）は、図２に示す画像処理装置の具体的第２実施例のブロック図であり、（ｂ）は、（ａ）に示す画像処理装置に用いられるコントラストのハイライト／シャドー依存テーブルの一例のグラフである。
【図６】 （ａ）は、図２に示す画像処理装置の具体的第３実施例のブロック図であり、（ｂ）は、（ａ）に示す画像処理装置に用いられる特定濃度依存テーブルの一例のグラフである。
【図７】 （ａ）は、図２に示す画像処理装置の具体的第４実施例のブロック図であり、（ｂ）は、（ａ）に示す画像処理装置において実施されるエッジ検出の方法を説明する説明図であり、（ｃ）は、（ａ）に示す画像処理装置に用いられるエッジ依存テーブルの一例のグラフである。
【符号の説明】
１０ デジタルカラー画像プリントシステム
１２ 読取手段
１４ 画像処理装置
１６ 再生手段
１８ ＣＣＤアレイ
２０ 集光レンズ
２２ フィルタタレット
２４ Ａ／Ｄ変換手段
２６ ＣＣＤ補正手段
２８ 対数変換手段
３０ オートセットアップ演算部
３２ 色・階調処理手段
３４ ＣＲＴ
３６ モニタ表示アンドユーザインターフェイス
３８ 処理手段
４０ プリンタ
４２，４８ ローバスフィルタ
４４，５０ 減算手段
５１ マスクメモリ
５２ 画像特性取得手段
５２ａ コントラスト信号取得手段
５２ｃ 原信号輝度算出手段
５２ｄ エッジ信号取得手段
５３ エッジ検出手段
５４ 画像特性依存ゲイン算出手段
５４ａ コントラスト依存ゲイン算出手段
５４ｂ ハイライト／シャドー判定・ゲイン算出手段
５４ｃ 輝度信号依存ゲイン算出手段
５４ｄ エッジ依存ゲイン算出手段
５６，５８ アンプ
６０，６２ 加算手段
ＣＩ カラー画像
Ｐ 可視（再生）像
Ｚ 記録材料（媒体）[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image processing method and apparatus, and more particularly to an image processing method and apparatus for performing predetermined image processing on a color image signal obtained by reading a color image.
[0002]
[Prior art]
A color image such as a photographic film is photoelectrically read by a sensor such as a CCD to obtain image signals for each of the three primary colors red (R), green (G) and blue (B). Thus, the image signal after the image processing is reproduced as a visible image on the recording material. In this method, before obtaining the RGB three-color image signal, first, a color image is photoelectrically read at a rough scanning interval to perform a pre-scan to read the outline of the color image, and based on the data obtained by this pre-scan. 2. Description of the Related Art There is known a system configured to set various parameters when performing image processing and then perform fine scanning that is read at fine scanning intervals to obtain an image signal.
[0003]
As image processing performed in such a system, for example, various methods for enhancing image sharpness by performing image processing on an image signal representing a given image have been proposed. For example, a technique is known in which the image signal is subjected to a blur mask process to enhance the sharpness of the image (Image Analysis Handbook, P.549, The University of Tokyo Press, Mikio Takagi, supervised by Yoshihisa Shimoda).
However, although the above-described blur mask processing can enhance sharpness, it also emphasizes the roughness due to the graininess of the film at the same time as the enhancement of sharpness. As a result, a good reproduced image with reduced noise is obtained. I can't.
[0004]
  For this reason, various image processing methods for suppressing image noise such as graininess conspicuous in a flat portion of the image and enhancing the sharpness of the image, for example, enhancing the sharpness of only the edge portion or texture portion of the image have been proposed. ing.
  For example, U.S. Pat. No. 4,812,903 discloses a process for decomposing RGB three-color image signals into luminance signals and color signals, performing nonlinear processing on the low frequency components of the luminance signals, and emphasizing the high frequency components. The processed luminance signal and color signal are combined to suppress the granularity of the reproduced image and increase the sharpness.AdjustA processing method has been proposed.
[0005]
  Japanese Patent Application Laid-Open No. 63-26783 discloses that a luminance signal and other color signals (hue, saturation, etc.) are extracted from an image signal representing a color image, and a spatial filter process is performed on the luminance signal to obtain a spatial signal. The global information and the spatial detailed information are calculated, and the spatial general information and the spatial detailed information are subjected to predetermined emphasis processing, and the processed global information and the detailed information are combined to generate a new luminance signal. The processed image in which the new brightness signal and the color signal are synthesized and converted into a predetermined color image signal, natural sharpness enhancement processing with little change in color tone is performed, and grain is suppressed An image processing method capable of obtaining the above has been proposed.
  However, in the image processing methods disclosed in these publications, since the high frequency components of the color are not emphasized, the roughness of the film grain can be suppressed as compared with the blur mask process, but the luminance component caused by the film grain The roughness isstillThere is a problem of remaining as.
[0006]
Furthermore, Japanese Patent Laid-Open No. 3-502975 discloses that the sharpness enhancement coefficient K is changed in accordance with the characteristic part of the image in the following formula (1) when performing the blur mask process, thereby further improving the sharpness of the image. A method for emphasis has been proposed.
S '= S_org+ K '(S_org-S_us) (1)
Where S_orgIs the original image signal, S_usIs a blur mask signal.
In this method, a local dispersion value plotted against the number of appearances of flat portions, textures, and edge portions having a lot of noise caused by film grain of an image is obtained, and a coefficient K is set as a function of the local dispersion value. is there. That is, in a normal image, the local variance value of the flat portion is small, and the local variance values of the texture and the edge portion are sequentially large. Therefore, the coefficient K of the image signal of the flat portion is obtained based on the local variance value. In this method, the coefficient K of the image signal of the texture and the edge portion is obtained based on the local dispersion value. Therefore, the coefficient K is reduced for the flat portion, and the coefficient K is increased for the texture and the edge portion to suppress noise and obtain an image with enhanced sharpness.
[0007]
However, in this method, although it is possible to enhance the sharpness by suppressing the film granularity, textures and edges having a small amplitude of the image signal are difficult to separate from the local dispersion of the flat portion when the local dispersion is obtained, There is a problem in that textures and edges that must be observed with a high degree of sharpness may be suppressed in the same way as noise in flat portions.
[0008]
For this reason, Japanese Patent Application Laid-Open No. 9-22460 relating to the application of the present applicant discloses that a color original image signal is decomposed into a low frequency component, an intermediate frequency component and a high frequency component, and the high frequency component is emphasized. After the emphasis suppression processing is performed, the high frequency component and intermediate frequency component after processing and the low frequency component are synthesized. Preferably, after decomposition, the luminance component is further extracted from the intermediate frequency component and high frequency component. An image processing method and apparatus for performing enhancement suppression processing and synthesis processing based only on luminance components are disclosed. This grain suppression sharpness enhancement process suppresses intermediate frequency components including roughness due to film grain, and emphasizes high frequency components including edges, textures, etc., so that roughness is suppressed and sharpness is enhanced. A reproduced image with good image quality can be obtained.
[0009]
[Problems to be solved by the invention]
However, the image noise includes various frequency components including a noise component based on the grain of the film. Even in the grain-suppressed sharpness enhancement processing disclosed in Japanese Patent Laid-Open No. 9-22460, the noise is sufficient. Depending on the balance between emphasis of high frequency components and suppression of intermediate frequency components, the sharpness may not be fully enhanced, and if the sharpness is excessively emphasized. There is a problem that a false contour is generated at the edge.
[0010]
An object of the present invention is to solve the above-mentioned problems of the prior art, enhance the sharpness of a color image, remove a noise component based on film grain, further suppress graininess of a flat part, and counterfeit edges. An image processing method capable of obtaining a reproduced image with good image quality by preventing contours, suppressing graininess of a specific density region, detecting an edge of an image, and enhancing the sharpness of only the edge, and To provide the equipment.
[0011]
[Means for Solving the Problems]
In the original image signal representing a general color image, the present inventor is a high-frequency component of the original image signal that affects the sharpness of the reproduced image. This is mainly contained in the intermediate frequency component, but since the image noise contains various frequency components, the noise may not be sufficiently suppressed, such as edges and textures. As a result of earnest research on grain suppression sharpness enhancement processing that can sufficiently remove noise components based on film grain without reducing sharpness of image, enhancement that emphasizes high frequency components and suppression of intermediate frequency components By performing suppression processing depending on image characteristics, such as contrast, contrast highlights and shadows, specific image density, brightness, and edges And finding that it is possible to achieve the above object, and have reached the present invention.
[0012]
  That is, the present invention is an image processing method for performing predetermined image processing on an original image signal representing a predetermined color image, calculating a luminance signal of the original image signal, and converting the original image signal into a low frequency component A high frequency gain for separating the intermediate frequency component and the high frequency component and emphasizing the high frequency component of the original image signalOf the original image signalWhile setting according to the luminance signal, an intermediate frequency gain for suppressing the intermediate frequency component of the original image signal,Of the original image signalThis is set according to the luminance signal, and the high frequency component is emphasized according to the high frequency gain, and the intermediate frequency component is suppressed according to the intermediate frequency gain. An image processing method characterized in that a processed image signal is obtained by synthesizing the processed high frequency component and intermediate frequency component and the low frequency componentIn the decomposition of the original image signal, the image processing is performed in the step of setting the high frequency gain and the intermediate frequency gain by using at least the low frequency component of the decomposed frequency components as RGB data. For each target pixel, a detected edge index represented by the sum of the difference in luminance signal between pixels adjacent in the main scanning direction and the difference in luminance signal between pixels adjacent in the sub-scanning direction is The high frequency gain and the intermediate frequency gain having a magnitude corresponding to the detected edge index are set for each pixel.An image processing method characterized by the above is provided.
[0013]
Here, the low frequency component, intermediate frequency component, and high frequency component of the original image signal refer to frequency components distributed as shown in FIG. 3, and the intermediate frequency component is data after processing. Is a frequency component distributed with a peak in the vicinity of 1/3 of the output Nyquist frequency when the image is reproduced as a visible image, and the low frequency component is the frequency at which the output Nyquist frequency is zero. The high frequency component means a component distributed with the peak of the output Nyquist frequency, and further, a component in which the sum of the low, middle and high frequency components is 1 at each frequency. That's what it says.
[0014]
  The luminance signal of the original image signal is preferably a signal representing a Y component when the RGB color data of the intermediate / high frequency component is subjected to YIQ specified conversion.
[0015]
  Prior to decomposing the original image signal, a basic high frequency gain for enhancing the high frequency component of the original image signal based on RGB color data of the original image signal, and the original image signal A step of setting a basic intermediate frequency gain for suppressing the intermediate frequency component of the step, wherein the step of setting the high frequency gain and the intermediate frequency gain adjusts the basic high frequency gain and the basic intermediate frequency gain. An intensity coefficient to be set according to the luminance signal, the high frequency gain is calculated and set by multiplying the basic high frequency gain by the intensity coefficient according to the luminance signal, and the basic intermediate frequency It is preferable to calculate and set the intermediate frequency gain by multiplying the frequency gain by the intensity factor corresponding to the luminance signal. .
[0016]
  In the step of setting the high frequency gain and the intermediate frequency gain,
The intensity coefficient is determined according to a detected edge index calculated according to the luminance signal, and the intensity coefficient is set to 1.0 when the detected edge index is larger than a predetermined value. When the index is smaller than the predetermined value, it is preferable that the index is set to monotonously increase from 0.0 to 1.0 at a predetermined rate according to the magnitude of the detected edge index.
[0017]
  The present invention is also an image processing apparatus for performing predetermined image processing on an original image signal representing a predetermined color image, a means for calculating a luminance signal of the original image signal, and reducing the original image signal. Means for decomposing into a frequency component, an intermediate frequency component, and a high frequency component, and a high frequency gain for enhancing the high frequency component of the original image signal,Of the original image signalWhile setting according to the luminance signal, an intermediate frequency gain for suppressing the intermediate frequency component of the original image signal,Of the original image signalA means for setting according to the luminance signal, and an image characteristic dependent enhancement suppressing process for enhancing the high frequency component according to the high frequency gain and suppressing the intermediate frequency component according to the intermediate frequency gain. An image processing apparatus comprising: means; and a high-frequency component and an intermediate frequency component after processing, and a means for synthesizing the low-frequency component to obtain a processed image signal,The means for decomposing performs decomposition using at least the low frequency component among the respective frequency components after decomposition as RGB data, and the means for setting the high frequency gain and the intermediate frequency gain is a target for performing the image processing. For each of the pixels, a detected edge index represented by the sum of the difference in luminance signal between pixels adjacent in the main scanning direction and the difference in luminance signal between pixels adjacent in the sub-scanning direction is obtained. The high frequency gain and the intermediate frequency gain having a magnitude corresponding to the detected edge index are set for each pixel.An image processing apparatus characterized by the above is provided.
[0018]
  Also,The luminance signal of the original image signal is preferably a signal representing a Y component when the RGB color data of the intermediate / high frequency component is subjected to YIQ specified conversion.
[0019]
  Prior to decomposing the original image signal, a basic high frequency gain for enhancing the high frequency component of the original image signal based on RGB color data of the original image signal, and the original image signal And a means for setting a basic intermediate frequency gain for suppressing the intermediate frequency component, and the means for setting the high frequency gain and the intermediate frequency gain adjusts the basic high frequency gain and the basic intermediate frequency gain. An intensity coefficient to be set according to the luminance signal, the high frequency gain is calculated and set by multiplying the basic high frequency gain by the intensity coefficient according to the luminance signal, and the basic intermediate frequency It is preferable to calculate and set the intermediate frequency gain by multiplying the frequency gain by the intensity coefficient corresponding to the luminance signal.
[0020]
  Also,In the means for setting the high frequency gain and the intermediate frequency gain,
The intensity coefficient is determined according to a detected edge index calculated according to the luminance signal, and the intensity coefficient is set to 1.0 when the detected edge index is larger than a predetermined value. When the index is smaller than the predetermined value, it is preferable that the index is set to monotonously increase from 0.0 to 1.0 at a predetermined rate according to the magnitude of the detected edge index.
[0021]
DETAILED DESCRIPTION OF THE INVENTION
An image processing method and apparatus according to the present invention will be described in detail below with reference to preferred embodiments shown in the accompanying drawings.
[0022]
FIG. 1 is a block diagram of an embodiment of a digital color image reproduction system that reads an image from a color photograph to which an image processing apparatus that performs an image processing method according to the present invention is applied and reproduces the image on a recording material.
As shown in the figure, a digital color image reproduction system (hereinafter simply referred to as a reproduction system) 10 includes a reading unit 12 that reads an image from a color photographic film, and an image representing a color photographic film image CI obtained by the reading unit 12. The image processing means 14 for performing image processing including image processing based on the image processing method of the present invention on the signal, and the image signal subjected to image processing by the image processing means 14 as a visible image P on the recording material Z And reproducing means 16 for recording.
[0023]
The reading means 12 has a CCD array 18 for photoelectrically reading the color original image signals R, G, B from the color image CI such as a negative film or a reversal film, and the light from the color image CI is added to the CCD array 18. Has an imaging lens 20 for forming an image. In this embodiment, the CCD array 18 is composed of 2760 × 1840 pixels, and image data is rotated while rotating the filter turret 22 provided with the three color separation filters of red (R), green (G), and (B) blue. By performing this scanning, a full-color image can be obtained in a frame sequential manner. Further, the CCD array 18 is corrected by an A / D conversion means 24 for digitally converting an image signal representing a color image detected by the CCD array 18, a CCD correction means 26 for correcting the CCD array 18, and a CCD correction means 26. And a logarithmic conversion means 28 having a built-in look-up table for logarithmically converting the image signal representing the color image. Before obtaining the three RGB image signals, the reading unit 12 first performs a pre-scan to read the outline of the color image CI by photoelectrically reading the color image CI at a coarse scan interval, and then performing pre-scan data S._PFine scan data S is obtained by performing a fine scan that is read at fine scan intervals._FIt is configured to obtain.
[0024]
The image processing means 14 uses prescan data S_PAn auto setup calculation unit (hereinafter referred to as a calculation unit) 30 for setting parameters such as gradation processing in fine scan based on the above, and fine scan data S based on the parameters set by this calculation unit 30_FColor / gradation processing means 32 for performing color / gradation processing of the image and prescan data S_PA monitor display and user interface 36 for connecting the CRT 34 that reproduces the image as a visible image and the calculation unit 30, and a granularity suppression sharpness that performs a granularity suppression process and a sharpness enhancement process on the color image signal that is a feature of the present invention. And an emphasis processing means (hereinafter referred to as emphasis processing means) 38.
Further, the reproducing means 16 has a printer 40 for recording a color image signal on a recording material Z as a visible reproduced image P.
[0025]
Below, the operation of each means and its components of the playback system 10 will be described.
First, in the reproduction system 10, a pre-scan is performed by the reading unit 12 for reading an outline of the color image CI from the color image CI such as a negative film or a reversal film at a coarse scan interval. Three color pre-scan data S obtained by this pre-scan_PIs converted into digital data by the A / D conversion means 24, corrected by the CCD correction means 26, and logarithmically amplified by the logarithmic conversion means 28, and the arithmetic unit 30 of the image processing means 14 and a monitor display and user interface (hereinafter referred to as interface). )).
[0026]
Next, in the image processing unit 14, the pre-scan data S input to the interface 36._PIs displayed as a visible image on the CRT 34, and a signal S representing the selection result is selected by the user selecting a sharpness processing menu 34A displayed separately from the visible image on the CRT 34.₁Is input to the interface 36 and the signal S₁Is input to the arithmetic unit 30. In the arithmetic unit 30, the pre-scan data and the signal S₁Based on the above, parameters for color / gradation processing performed later by the color / gradation processing means 32 are set. A part of the parameters is input to an emphasis processing means 38 that performs an image processing method of the present invention, which will be described later.
[0027]
Here, the details of parameter setting will be described. First, in the calculation unit 30, the input pre-scan data S_PBased on the above, the temperature range and print size of the color image CI are obtained. Further, here, the signal S input from the CRT 34 via the interface 36.₁The gain M multiplied by the intermediate frequency component in the enhancement suppression processing performed in the enhancement processing means 38 based on₀And gain H multiplied by high frequency components₀Etc., and if necessary, these gains M₀And H₀The type and intensity (image characteristic dependent intensity table (LUT)) of the image characteristics that are dependent upon the adjustment are also set. Further, in the calculation unit 30, parameters for color / gradation processing performed in the color / gradation processing unit 32 are also obtained and input to the enhancement processing unit 38 and the color / gradation processing unit 32.
[0028]
Next, the reading unit 12 performs a fine scan for reading the color image CI at a fine scan interval, and the fine scan data S for three colors._FIs obtained as a color image signal. Fine scan data S_FIs converted into digital data by the A / D conversion means 24, corrected by the CCD correction means 26, logarithmically amplified by the logarithmic conversion means 28, and input to the color / gradation processing means 32. In the color / gradation processing means 32, fine scan data S_FIs subjected to color / gradation processing and input to the emphasis processing means 38.
[0029]
  In the following, the emphasis suppression process, which is a feature of the present invention and is performed in the granularity suppression sharpness emphasis processing means 38, will be described.
  FIG. 2 is a block diagram for explaining details of the emphasis suppression processing performed by the emphasis processing means 38.
  As shown in the figure, the enhancement processing means 38 constitutes the image processing apparatus of the present invention, and is a 9 × 9 first row.PaSfilter (hereinafter referred to as LPF) 42, first subtraction means 44, luminance calculation means 46, 5 × 5 second LPF 48, second subtraction means 50, and image characteristic acquisition means (hereinafter referred to as acquisition means). 52, an image characteristic dependent gain calculating means (hereinafter referred to as gain calculating means) 54, a first amplifier 56, a second amplifier 58, a first adding means 60, and a second adding means 62.
  Here, the first LPF 42, the first subtracting means 44, the luminance calculating means 46, the second LPF 48 and the second subtracting means 50 constitute a disassembling means of the present invention. The gain calculating means 54, the first amplifier 56, and the second amplifier 58 constitute an emphasis suppression processing means of the present invention, and the first adding means 60 and the second adding means 62 constitute a synthesizing means of the present invention. .
[0030]
In the enhancement processing means 38 shown in FIG. 2, the input fine scan data (hereinafter referred to as the original signal) S_F(RGB) is subjected to filtering processing by the first LPF 42 described below, and the original signal S_FLow-frequency component R of (RGB)_L, G_L, B_LIs extracted.
[0031]
[Expression 1]

[0032]
In the first subtracting means 44, the original signal S_FTo low frequency component (low frequency signal) R_L, G_L, B_LIs subtracted from the intermediate and high frequency component R_MH, G_MH, B_MHTo extract. Low frequency component R after being extracted in this way_L, G_L, B_LDoes not include roughness in the color image, fine texture, or graininess of the film. On the other hand, the intermediate frequency component R_M, G_M, B_MIncludes roughness due to film grain, and high frequency component R_H, G_H, B_HIncludes edges and fine textures in the color image.
[0033]
Here, the low frequency component, the intermediate frequency component, and the high frequency component of the original signal are obtained when gains M and H multiplied by intermediate and high frequency components (described later) distributed as shown in FIG. 3 are set to 1.0. This refers to the frequency component, and the intermediate frequency component R_M, G_M, B_MIs the output Nyquist frequency f when the processed data is reproduced as a visible image P._SDistribution H with a peak near 1/3 of / 2_MIs a low frequency component R_L, G_L, B_LAnd distribution H with a peak at 0 frequency_LThe high frequency component R_H, G_H, B_HIs the output Nyquist frequency f_SDistribution H with a peak at / 2_HThe component which becomes. In the present embodiment, the Nyquist frequency refers to the Nyquist frequency when recording on the recording medium Z is performed at 300 dpi. Here, in FIG. 3, the sum of the frequency components is 1 at each frequency.
[0034]
Next, in the luminance calculation means 46, the intermediate / high frequency component R decomposed by the first subtraction means 44._MH, G_MH, B_MHA luminance component is extracted from. The extraction of the luminance component is the original signal S_FMiddle and high frequency component R_MH, G_MH, B_MHY component converted to YIQ standard_MHRepresents the luminance component of the data. Here, the conversion to the YIQ standard is performed by the following equation (2).
[0035]
[Expression 2]

[0036]
Here, the component I which is the color component after conversion to the YIQ standard_MHAnd ingredient Q_MHContains color roughness due to film grain, so component I_MHAnd ingredient Q_MHIs set to 0 here to suppress color roughness caused by film grain. Here, the component I which is a color component_MHAnd ingredient Q_MHIt has been empirically found that an image of a general subject has almost no component. Therefore, component I_MHAnd ingredient Q_MHIs regarded as a color roughness caused by film grain, and is set to 0, whereby a good reproduced image in which the roughness is suppressed can be obtained.
[0037]
Component Y_MHIs filtered by a 5 × 5 second LPF 48 as shown below to obtain a component Y_MHIntermediate frequency component Y_MGet.
[0038]
[Equation 3]

[0039]
Further, in the second subtracting means 50, the component Y_MHTo intermediate frequency component Y_MBy subtracting component Y_MHHigh frequency component Y_HGet.
[0040]
On the other hand, in the image characteristic acquisition unit 52, the gain M obtained by the arithmetic unit 30 described above.₀And gain H₀Image characteristics that are dependent upon the adjustment of the image, such as contrast, contrast highlights and shadows, specific image density and edges, etc._FIt is calculated based on (RGB). Where gain M₀And gain H₀There may be one kind of image characteristic used to make it depend when adjusting the image quality, or two or more kinds. The type of image characteristic used here is input to the CRT 34 or the like by the operator, input to the calculation unit 30 via the interface 36 from the CRT 34, and input to the image characteristic acquisition unit of the enhancement processing unit 38 from the calculation unit 30. The calculation unit 30 may be set based on an input signal from the CRT 34 or may be automatically set from the image itself.
The signal processing corresponding to the image characteristics performed in the acquisition unit 52 will be described later according to specific individual image characteristics.
[0041]
Thus, when the image characteristic is acquired by the acquisition unit 52, the image characteristic dependent gain calculation unit 54 determines the gain M obtained by the calculation unit 30 described above.₀And gain H₀Is set to an image characteristic-dependent intensity W for adjustment depending on the acquired image characteristic. The image characteristic-dependent intensity W set here may be set by the gain calculation unit 54 in accordance with the image and the image characteristic, but the intensity is previously stored in a memory (not shown) provided in the gain calculation unit 54 or the like. A plurality of functions and image characteristic dependent intensity tables (LUTs) are preferably prepared and may be selected according to the image and image characteristics. It should be noted that an intensity function, an image characteristic dependent intensity LUT, and the like may be prepared in advance in the calculation unit 30, and a necessary intensity function, an image characteristic dependent intensity LUT, and the like may be received.
[0042]
In this way, the image characteristic dependent intensity W set in accordance with the image characteristic in the gain calculating unit 54 is the gain M obtained in the arithmetic unit 30, respectively.₀And gain H₀Is multiplied by the following equation (3) to obtain an intermediate frequency component Y_MImage characteristic-dependent gain M and high-frequency component Y_HAn image characteristic dependent gain H for emphasizing the image depending on the image characteristic is calculated.
Gain M = Gain M₀× W
Gain H = Gain H₀× W …… (3)
Here, in the calculation unit 30, the intermediate frequency component Y that originally contains a relatively large amount of roughness of the luminance component based on the film grain._MBy setting the gain of the image to be relatively low, the feeling of roughness is suppressed, and the high frequency component Y of the luminance component on which the sharpness of the image depends_HThe gain M is set so that the sharpness of the processed image can be enhanced by relatively increasing the gain H of the image.₀And gain H₀Is gain M₀<Gain H₀It is set to become. Therefore, the image characteristic dependent gain M and the gain H calculated by the gain calculating unit 54 are set so that the gain M <the gain H.
[0043]
By the way, in the arithmetic unit 30, for example, when the color image CI is an under negative, the roughness due to the film granularity is conspicuous, and the granularity is considerably large when the gradation is set to improve the gradation characteristics. Gain M because it results in a bad image₀Is set fairly low. For this reason, the gain M is also set to be very low depending on the image characteristics by the gain calculating means 54. This makes it possible to strongly suppress graininess depending on the image characteristics. Even if it depends on the print size, the calculation unit 30 provides an optimum gain M.₀And gain H₀Is set. Furthermore, as described above, when the user selects a desired menu from several sharpness enhancement processing menus, the gain M corresponding to this menu is selected.₀And gain H₀Is stored as a table, and the optimum gain M is selected according to the menu selection.₀And gain H₀It is preferable to be able to select. This makes it possible to perform processing for each image or according to the user's preference.
Thus, the optimum gain M according to the print size and the user's preference in the arithmetic unit 30 is obtained.₀And gain H₀Therefore, it goes without saying that the gains M and H set depending on the image characteristics by the gain calculating means 54 are also optimum.
[0044]
  By the way, the image characteristic dependent intensity W uses the same image characteristic dependent intensity for the gain M for suppressing the intermediate frequency component and the gain H for enhancing the high frequency component, but the present invention is limited to this. Without gain M and gain H respectivelyDifferentImage characteristic dependent intensity may be used.
  In the above-described embodiment, the basic gain M₀And gain H₀Is calculated or set by the calculation unit 30, and the image characteristic dependent intensity W is first calculated by the gain calculating unit 54, and the image characteristic dependent gain M and the gain H are calculated by the above equation (3). Is not limited to this, but the basic gain M₀And gain H₀May be obtained directly by the gain calculation means 54 without being obtained by the calculation unit 30, or a basic gain M may be obtained.₀And gain H₀Alternatively, the image characteristic dependent gain M and the gain H may be directly calculated without obtaining the image characteristic dependent intensity W.
[0045]
Next, as shown in the following equation (4), the image characteristic-dependent gain M and the gain H calculated by the gain calculating unit 54 are components obtained by the second LPF 48 in the first and second amplifiers 56 and 58, respectively. Y_MHIntermediate frequency component Y_MAnd the component Y obtained by the second subtracting means 50_MHHigh frequency component Y_HEach processed component Y_M', Y_H'Is obtained.
Y_M'= Gain M × Y_M
Y_H'= Gain H × Y_H                            (4)
Subsequently, in the first addition means 60, as shown in the following formula (5), processed components Y obtained by the first and second amplifiers 56 and 58, respectively._M'And Y_H'Is synthesized and component Y_MH'Is obtained.
Y_MH'= Y_M'+ Y_H′ …… (5)
(= Gain M × Y_M+ Gain H × Y_H)
[0046]
Here, as described above, in the gain calculation means 54, the gain M and the gain H are set so that the gain M <the gain H. That is, since the roughness of the luminance component based on the film grain is relatively large in the intermediate frequency component, the component Y_MBy setting the gain M to be relatively low depending on the image characteristics, it is possible to appropriately suppress the feeling of roughness depending on the image characteristics. Further, since the sharpness of the image depends on the high frequency component of the luminance component, the high frequency component Y of the luminance component_HThe gain H of the processed image is made relatively large depending on the image characteristics, whereby the sharpness of the processed image can be appropriately enhanced depending on the image characteristics.
[0047]
Then, in the second addition means 62, the component Y thus obtained is obtained._MH'Is the original signal S described above_FLow frequency component R_L, G_L, B_LTo obtain processed signals R ′, G ′, and B ′. At this time, the above-mentioned component I_MHAnd ingredient Q_MHSince the value of is set to 0, the processed luminance component Y_MHWhen 'is inversely converted to correspond to RGB data, all three RGB data are component Y_MHIt becomes the same value as ′. Therefore, the processed luminance component Y_MHThe result of synthesis without reverse conversion of ′ is the same as the case of reverse conversion. Therefore, the luminance component Y processed in order to simplify the processing_MHIt is made to synthesize | combine without reversely transforming '.
Thereafter, the processed signals R ′, G ′, and B ′ are input to the reproducing unit 16 and reproduced as a visible image P on the recording material Z by the printer 40.
[0048]
In the reproduced visible image P reproduced in this way, the color components of the intermediate and high frequency components of the data including roughness due to film grain are set to 0, and the luminance components of the intermediate and high frequency components are further reduced. Of which, intermediate frequency component Y_MGain M is suppressed depending on the image characteristics, and the high frequency component Y_HSince the gain H of the image is enhanced depending on the image characteristics, the sharpness is appropriately enhanced in any image, and the roughness due to film grain is sufficiently suppressed.
[0049]
Next, specific examples of the image processing apparatus of the present invention that implement the image processing method of the present invention will be described.
The embodiment of the granularity suppression sharpness enhancement processing means 38 shown in FIGS. 4 to 7 includes the image characteristic acquisition means 52 and the image when the image characteristics are contrast, contrast highlight and shadow, specific image density, and edge, respectively. A specific example of the characteristic-dependent gain calculating means 54 is shown. Except for these, it is the same as the granularity-suppressing sharpness enhancement processing means 38 shown in FIG. Description is omitted.
[0050]
First, the enhancement processing means of the image processing apparatus according to the first specific embodiment of the present invention will be described. FIG. 4A is a block diagram for explaining the details of the contrast-dependent enhancement suppressing process performed in the enhancement processing unit 38a of the image processing apparatus according to the first specific example of the present invention.
As shown in FIG. 4A, the enhancement processing means 38a of the image processing apparatus 14 according to the first embodiment of the present invention uses contrast as the image characteristic, and the original calculated by the first subtraction means 44 as contrast. Signal S_FAnd low frequency signal R_L, G_L, B_LIntermediate / high frequency component R which is the difference signal from_MH, G_MH, B_MHAnd the difference signal R_MH, G_MH, B_MHThe luminance component (luminance signal) Y calculated by the luminance calculation means 46 from_MHThe emphasis suppression processing is performed depending on the above. Therefore, in the enhancement processing means 38a shown in FIG. 4A, the first subtraction means 44 and the luminance calculation means 46 constituting the decomposition means correspond to the image characteristic acquisition means 52 in the enhancement processing means 38 shown in FIG. Contrast (signal) acquisition means 52a is also configured, and the contrast dependent gain calculation means 54a functions as the image characteristic dependent gain calculation means 54 shown in FIG.
[0051]
  That is, the contrast signal acquisition unit 52a_FAnd low frequency signal R_L, G_L, B_LIntermediate / high frequency component R which is the difference signal from_MH, G_MH, B_MHFirst subtracting means 44 for calculatingThisDifference signal R_MH, G_MH, B_MHTo luminance signal Y according to the above equation (2)_MHAnd luminance calculation means 46 for calculating.
  Further, the gain calculating unit 54a is a difference signal (intermediate / high frequency component) R acquired by the luminance calculating unit 46 functioning as the image characteristic acquiring unit 52._MH, G_MH, B_MHLuminance signal Y_MHThe intensity function W depending on the intensity function W is set to be dependent on the contrast as shown in the contrast dependence table shown in FIG. Gain M₀And gain H₀From the above, the gains M and H are calculated by the above equation (3).
  In this embodiment, the contrast signal acquisition means 52a is constituted by the first subtraction means 44 and the luminance calculation means 46, and the gains M and H are set to the difference signal (intermediate / high frequency component) R._MH, G_MH, B_MHLuminance signal Y_MHHowever, the present invention is not limited to this, and the contrast signal acquisition unit 52a is configured only by the first subtraction unit 44, and the gains M and H are set to the difference signal (intermediate / intermediate). High frequency component) R_MH, G_MH, B_MHFor example, the intensity suppression processing may be performed depending on the average value of these three colors.
[0052]
In this way, in this embodiment, for example, a contrast dependence table as shown in FIG. 4B is used. Therefore, when the contrast is high, that is, the luminance signal Y of the difference signal._MHIs large, the intensity function W is set to 1, 0 and the intermediate frequency component Y_MGain M based on₀And high frequency component Y_HGain H based on₀And On the other hand, when the contrast is low, that is, the luminance signal Y of the difference signal_MHWhen the absolute value of is a value in a predetermined range, the value of the intensity function W is made smaller than 1.0 and the intermediate frequency component Y_MGain M based on₀Higher frequency component Y_HGain H based on₀Make it smaller.
By doing so, in this embodiment, the processed component Y_M', Y_H′ Is further reduced in the low contrast portion, the sharpness of the color image reproduced from the final processed signals R ′, G ′, and B ′ is emphasized, and noise components based on the grain of the film are removed. At the same time, it is possible to further suppress graininess in a flat portion having a low contrast, and obtain a reproduced image with good image quality.
[0053]
Next, the enhancement processing means of the image processing apparatus according to the second specific embodiment of the present invention will be described. FIG. 5A is a block diagram for explaining the details of the highlight part and shadow part dependence emphasis suppression processing by the contrast dependent method performed in the emphasis processing means 38b of the image processing apparatus according to the second specific example of the present invention. FIG.
As shown in FIG. 5 (a), the enhancement processing means 38b of the image processing apparatus 14 according to the second embodiment of the present invention uses contrast as an image characteristic, and operates each of the contrast highlight and shadow portions independently. The original signal S calculated by the first subtracting means 44 as contrast._FAnd low frequency signal R_L, G_L, B_LIntermediate / high frequency component R which is the difference signal from_MH, G_MH, B_MHAnd the difference signal R_MH, G_MH, B_MHThe contrast highlight portion and the shadow portion are determined or detected based on the sign of the difference signal R._MH, G_MH, B_MHThe luminance component (luminance signal) Y calculated by the luminance calculation means 46 from_MHEmphasis suppression processing is performed depending on the sign of.
[0054]
  Therefore, the emphasis processing unit 38b shown in FIG. 5A includes an emphasis processing unit 38a shown in FIG. 4A and a highlight / corresponding to the image characteristic dependent gain calculation unit 54 in the enhancement processing unit 38 shown in FIG. The shadow determination / gain calculation unit 54b not only calculates the difference signal corresponding to the contrast acquired by the contrast signal acquisition unit 52a or its luminance signal, but also the highlight portion and shadow portion of the contrast, that is, whether the difference signal is positive or negative or the luminance signal thereof. Except for determining positive / negative, and adjusting the values of the gain M and gain H in the contrast-dependent gain calculating means 54a depending on the determined highlight portion and shadow portion (the difference signal and the positive / negative of its luminance signal). Functions exactly the same.
  That is, in the enhancement processing means 38b shown in FIG. 5A, the first subtraction means 44 and the luminance calculation means 46 constituting the decomposition means are similar to the enhancement processing means 38a shown in FIG. A contrast (signal) acquisition means 52a corresponding to the image characteristic acquisition means 52 in the enhancement processing means 38 shown in FIG. 2 is also configured, and the highlight / shadow determination / gain calculation means 54b is an image characteristic dependent gain calculation means 5 shown in FIG.4 andAnd function.
[0055]
Here, the highlight / shadow determination / gain calculation means 54b is the difference signal (intermediate / high frequency component) R acquired by the luminance calculation means 46 functioning as the image characteristic acquisition means 52._MH, G_MH, B_MHLuminance signal Y_MHThe luminance signal Y determined_MHThe intensity function W depending on the positive / negative is dependent on the contrast and the highlight side and the shadow side as in the contrast dependence table shown in FIG. 5B, for example, the low contrast is small and the high contrast highlight side. The intensity function W and the basic gain M can be increased by setting a larger value on the shadow side where the contrast is large.₀And gain H₀From the above, the gains M and H are calculated by the above equation (3).
Also in this embodiment, the contrast signal acquisition means 52a is constituted by the first subtraction means 44 and the luminance calculation means 46, and the gains M and H are set to the difference signal (intermediate / high frequency component) R._MH, G_MH, B_MHLuminance signal Y_MHHowever, the present invention is not limited to this, and the contrast signal acquisition unit 52a is configured by only the first subtraction unit 44, and the gains M and H are set to the difference signal ( Intermediate / high frequency component) R_MH, G_MH, B_MHDepending on the positive / negative of, for example, the positive / negative of the average value of these three colors, the intensity suppression process may be performed.
[0056]
In this way, in this embodiment, for example, a contrast dependence table as shown in FIG. 5B is used. Therefore, when the contrast is high on the highlight side, that is, the luminance signal Y of the difference signal._MHIs positive and its absolute value is large, the value of the intensity function W is set to 1, 0, and the intermediate frequency component Y_MGain M based on₀And high frequency component Y_HGain H based on₀When the contrast is high on the shadow side, that is, the luminance signal Y of the difference signal_MHIs negative and its absolute value is large, the value of the intensity function W is made larger than 1, 0, and the intermediate frequency component Y_MGain M based on₀Higher frequency component Y_HGain H based on₀Make it even bigger. On the other hand, when the contrast is low, that is, the luminance signal Y of the difference signal_MHWhen the absolute value of is a value in a predetermined range, the value of the intensity function W is made smaller than 1.0 and the intermediate frequency component Y_MGain M based on₀Higher frequency component Y_HGain H based on₀Make it smaller.
By doing so, in this embodiment, the processed component Y_M', Y_HFrom the processed signals R ′, G ′, and B ′ that are finally obtained, ′ is further reduced in the low-contrast portion and is further increased on the shadow side of the high-contrast portion than on the highlight side of the high-contrast portion. It enhances the sharpness of the color image to be reproduced, removes noise components based on film grain, prevents false contours at the edges, and obtains a reproduced image with good image quality.
[0057]
Subsequently, the enhancement processing means of the image processing apparatus according to the third specific example of the present invention will be described. FIG. 6A is a block diagram for explaining the details of the specific density dependent enhancement suppressing process performed in the enhancement processing unit 38c of the image processing apparatus according to the third specific example of the present invention.
As shown in FIG. 6A, the enhancement processing means 38c of the image processing apparatus 14 according to the third embodiment of the present invention uses a specific density as the image characteristic, and the original signal S as the specific density._FThis density signal (RGB signal) is used and this original signal S_FLuminance component (luminance signal) Y calculated from the density signal (RGB) of_FThe emphasis suppression processing is performed depending on the above. Therefore, in the enhancement processing unit 38c shown in FIG. 6A, the original signal luminance calculation unit 52c functions as the image characteristic acquisition unit 52 in the enhancement processing unit 38 shown in FIG. 2, and the luminance signal dependent gain calculation unit 54c It functions as the image characteristic dependent gain calculating means 54 shown in FIG.
[0058]
That is, the original signal luminance calculating means 52c is connected to the original signal S._FThe luminance signal Y according to the conversion formula (2) from the density signal (RGB) of the above to the YIQ standard described above_FIs calculated.
Further, the gain calculation unit 54 c is a luminance signal Y calculated by the original signal luminance calculation unit 52 c that functions as the image characteristic acquisition unit 52._FIs dependent on the luminance signal, for example, as in the luminance signal dependency table shown in FIG. 6B, that is, the luminance function is large when the luminance signal is equal to or smaller than a predetermined value, and is predetermined as the luminance signal becomes larger than the predetermined value. By setting the intensity function W so as to decrease monotonously, that is, gradually decreasing in a specific density region (specific luminance region), this intensity function W and a basic gain M₀And gain H₀From the above, the gains M and H are calculated by the above equation (3).
[0059]
In this way, in this embodiment, for example, a luminance signal dependency table as shown in FIG. 6B is used. Therefore, when the luminance signal is equal to or smaller than a predetermined value, the value of the intensity function W is set to 1.0. , Intermediate frequency component Y_MGain M based on₀And high frequency component Y_HGain H based on₀And On the other hand, when the luminance signal is larger than the predetermined value, the value of the intensity function W is set to monotonously decrease at a predetermined rate from 1.0 to 0.0 as the luminance signal increases. Frequency component Y_MGain M based on₀To high frequency component Y_HGain H based on₀To 0.0 in a monotonous manner at a predetermined rate.
By doing so, in this embodiment, the processed component Y_M', Y_H'Is further gradually reduced in a specific density (brightness) region where the luminance signal is larger than a predetermined value, and the sharpness of the color image reproduced from the final processed signals R', G ', B' is emphasized. In addition, the noise component based on the grain of the film can be removed, and the graininess in the specific density region can be further suppressed to obtain a reproduced image with good image quality.
[0060]
In the present embodiment, the original signal S is calculated by the original signal luminance calculating means 52c._FDensity signal (RGB) to luminance signal Y_FHTo calculate the luminance signal Y_FHHowever, the present invention is not limited to this, and the original signal S is not used, and the original signal S is not used._FOriginal density signal (RGB) is used as it is, and the original signal S_FThe intensity suppression processing may be performed depending on the density signal (RGB), for example, the average value of the RGB density signals. In this case, as the image characteristic acquisition unit 52, the original signal S input to the enhancement processing unit 38c._FIs used as a density signal (RGB) as it is, an average value of three colors is obtained, and the average value of these three colors may be output.
In the illustrated example, for example, an area larger than a predetermined luminance value is set as the specific density area, and the luminance dependence table as shown in FIG. 6B is used. However, the present invention is not limited to this, Any density (luminance) area may be set as the specific density area, and any luminance dependence table may be used.
[0061]
Furthermore, the enhancement processing means of the image processing apparatus according to the fourth specific example of the present invention will be described. FIG. 7A is a block diagram for explaining the details of the edge-dependent enhancement suppressing process performed in the enhancement processing unit 38d of the image processing apparatus according to the fourth specific example of the present invention.
As shown in FIG. 7A, the emphasis processing unit 38d of the image processing apparatus 14 according to the third embodiment of the present invention uses an edge as an image characteristic, and the inside of a mask targeted for low frequency component extraction as an edge. Signal R_ij, G_ij, B_ijLuminance signal Y (i: pixel position in the main scanning direction, j: pixel position in the sub-scanning direction)_ijThe emphasis suppression process is performed depending on the difference signal in the main / sub scanning direction. Therefore, in the enhancement processing means 38d shown in FIG. 7A, the mask memory 51 and the edge detection means 53 constituting the in-mask signal are edges corresponding to the image characteristic acquisition means 52 in the enhancement processing means 38 shown in FIG. The signal acquisition means 52d is configured, and the edge dependent gain calculation means 54d functions as the image characteristic dependent gain calculation means 54 shown in FIG.
[0062]
That is, the edge signal acquisition unit 52d receives the original signal S._FTo mask signal R_ij, G_ij, B_ijThe mask memory 51 for extracting the signal R and the in-mask signal R_ij, G_ij, B_ijTo luminance signal Y_ijAnd an edge detection means 53 having difference signal calculation means for calculating a difference signal in the main / sub-scanning direction of the luminance signal. Here, the luminance signal extraction means of the edge detection means 53 first performs the in-mask signal R._ij, G_ij, B_ijLuminance signal Y_ijIs calculated by the conversion formula (2) to the YIQ standard described above. Next, the difference signal calculation means of the edge detection means 53 is the luminance signal Y_ijAs the detected edge (index) E, the difference in the main / sub scanning direction is calculated by the following equation (6). Here, in the following equation (6), A, B, C, and D are luminance signals Y as shown in FIG._ijIs the sum of the left, right, top, and bottom pixel values.
E = | A−B | + | C−D | (6)
[0063]
Further, the edge dependent gain calculating means 54d makes the intensity function W depending on the edge E detected by the edge detecting means 53 of the edge signal acquiring means 52d dependent on the detected edge E as shown in FIG. 7C, for example. In other words, the intensity function W and the basic gain M are set to be small in the flat portion where the detection edge E is small and large in the edge portion where the detection edge E is large.₀And gain H₀From the above, the gains M and H are calculated by the above equation (3).
In this embodiment, the edge signal acquisition means 52d is constituted by the mask memory 51 and the edge detection means 53, and the original signal S is obtained by the mask memory 51._FExtraction target mask signal R_ij, G_ij, B_ijAnd the signal R in the mask R_ij, G_ij, B_ijFrom the luminance signal Y based on the above equation (2)._ijAnd the obtained luminance signal Y_ijBased on the above, the edge E is detected by the above equation (6), and the gains M and H are determined as the luminance signal Y._ijHowever, the present invention is not limited to this, and the edge detection means 53 uses the luminance signal Y according to the above equation (2)._ijIn-mask signal R targeted for low-frequency component extraction without calculating_ij, G_ij, B_ijThe difference signal in the main / sub scanning direction itself may be detected as the edge E by the above equation (6), and the gains M and H may be subjected to intensity suppression processing depending on the detected edge E based on the difference signal. At this time, as shown in FIG. 7B, A, B, C, and D in the above equation (6)_ij, G_ij, B_ijThe sum of the left and right and upper and lower pixel values relating to the average value of the image may be used.
[0064]
In this way, in this embodiment, for example, an edge dependence table as shown in FIG. 7C is used. Therefore, in the case of an edge, that is, when the value of the detected edge E is large, the value of the intensity function W Is 1, 0, and the intermediate frequency component Y_MGain M based on₀And high frequency component Y_HGain H based on₀And On the other hand, in the case of a flat portion that is not an edge, that is, when the value of the detected edge E is equal to or smaller than a predetermined value (a small predetermined range value), the value of the intensity function W is monotonically from 1.0 to 0.0. Decrease and gradually reduce the intermediate frequency component Y_MGain M based on₀Higher frequency component Y_HGain H based on₀Make it smaller.
By doing so, in this embodiment, the processed component Y_M', Y_H′ Is further reduced on the flat part to enhance the sharpness of the color image reproduced from the final processed signals R ′, G ′, B ′, and to remove noise components based on the grain of the film. The edge of the image is detected, only the edge is emphasized, and the noise in the flat portion due to the sharpness enhancement is further suppressed, so that a reproduced image with good image quality can be obtained.
In the illustrated example, for example, the value of the detected edge E is set as the edge by the sum of the left, right, top and bottom pixel values in the mask, and an edge dependence table as shown in FIG. The invention is not limited to this, and any detected edge E value may be set as an edge, and any edge dependence table may be used.
[0065]
As described above, with respect to the granularity suppression sharpness enhancement processing means constituting the image processing apparatus of the present invention that implements the image processing method of the present invention, the image characteristics are contrast, contrast highlight portion and shadow portion, specific image density, and edge, respectively. Although a specific embodiment in a certain case has been described, the present invention is not limited to this, and other image characteristics may be used. Of course, an image characteristic acquisition unit and an image characteristic dependent gain may be used according to the image characteristics. What is necessary is just to set a calculation means.
In the above-described embodiment, the intermediate / high frequency component R_MH, G_MH, B_MHIs converted to the YIQ standard and gain processing is performed, but it is not necessary to convert the YIQ standard to the intermediate / high frequency component R_MH, G_MH, B_MHIs the intermediate frequency component R_M, G_M, B_MAnd high frequency component R_H, G_H, B_HIn other words, the gain processing may be performed without converting each component into the YIQ standard. However, when the gain processing is performed based only on the luminance component after the conversion to the YIQ standard, roughness due to film grain can be greatly suppressed.
[0066]
Although the image processing method and apparatus of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various improvements and modifications may be made without departing from the spirit of the present invention. Of course.
[0067]
【The invention's effect】
As described above in detail, the image processing method and apparatus according to the present invention decomposes an image signal into low, medium, and high frequency components, suppresses intermediate frequency components including roughness due to film grain, edge, texture When emphasizing high frequency components, such as, etc., the suppression strength of the intermediate frequency component and the enhancement strength of the high frequency component depend on the image characteristics such as contrast, contrast highlight and shadow, specific density, and edge. Therefore, the color reproduction image of the processed image signal is enhanced in sharpness, the noise component based on film grain is removed, the graininess of the flat part is further suppressed, and the false contour of the edge part is reduced. Good image quality with reduced image quality, reduced graininess in specific density areas, detected image edges, and enhanced edge sharpness It is possible to obtain a reproduced image.
[0068]
In addition, according to the present invention, it is possible to suppress the roughness of the luminance component based on the film granularity by performing processing only on the luminance component of the intermediate / high frequency component, and therefore, it is possible to obtain a reproduced image with better image quality. Can do.
Further, according to the present invention, when the RGB three colors of the middle and high frequency components of the color image signal are converted into YIQ standards, the I component and the Q component which are color components have almost no component in a normal subject. Therefore, the I component and the Q component can be regarded as color roughness due to film granularity. Therefore, by performing enhancement suppression processing and synthesis based only on the Y component that is the luminance component of the high frequency component and the intermediate frequency component decomposed from the image signal, further suppresses color roughness due to film grain, A good reproduction image can be obtained.
[Brief description of the drawings]
FIG. 1 is a block diagram of an embodiment of a digital color image reproduction system to which an image processing apparatus that performs an image processing method according to the present invention is applied.
FIG. 2 is a block diagram of an embodiment of an image processing apparatus of the present invention applied to the digital color image reproduction system shown in FIG.
FIG. 3 is a graph showing the distribution of low, medium and high frequency components of a color original image signal.
4A is a block diagram of a specific first embodiment of the image processing apparatus shown in FIG. 2, and FIG. 4B is an example of a contrast dependence table used in the image processing apparatus shown in FIG. It is a graph of.
5A is a block diagram of a specific second embodiment of the image processing apparatus shown in FIG. 2, and FIG. 5B is a highlight / contrast of contrast used in the image processing apparatus shown in FIG. It is a graph of an example of a shadow dependence table.
6A is a block diagram of a specific third embodiment of the image processing apparatus shown in FIG. 2, and FIG. 6B is a specific density dependence table used in the image processing apparatus shown in FIG. It is an example of a graph.
7A is a block diagram of a specific fourth embodiment of the image processing apparatus shown in FIG. 2, and FIG. 7B is an edge detection method performed in the image processing apparatus shown in FIG. (C) is a graph of an example of an edge dependence table used in the image processing apparatus shown in (a).
[Explanation of symbols]
10 Digital color image printing system
12 Reading means
14 Image processing device
16 Reproduction means
18 CCD array
20 Condensing lens
22 Filter turret
24 A / D conversion means
26 CCD correction means
28 Logarithmic conversion means
30 Auto setup calculation section
32 color / gradation processing means
34 CRT
36 Monitor display and user interface
38 Processing means
40 Printer
42,48 low bass filter
44, 50 Subtraction means
51 Mask memory
52 Image characteristic acquisition means
52a Contrast signal acquisition means
52c Original signal luminance calculation means
52d Edge signal acquisition means
53 Edge detection means
54 Image characteristic dependent gain calculation means
54a Contrast-dependent gain calculating means
54b Highlight / shadow determination / gain calculation means
54c Luminance signal dependent gain calculation means
54d Edge-dependent gain calculation means
56,58 amplifier
60, 62 addition means
CI color image
P Visible (reproduced) image
Z Recording material (medium)

Claims (8)

An image processing method for performing predetermined image processing on an original image signal representing a predetermined color image,
Calculating a luminance signal of the original image signal;
Decomposing the original image signal into a low frequency component, an intermediate frequency component, and a high frequency component;
An intermediate frequency gain for setting a high frequency gain for enhancing the high frequency component of the original image signal in accordance with the luminance signal of the original image signal and suppressing the intermediate frequency component of the original image signal Is set according to the luminance signal of the original image signal ,
While emphasizing the high frequency component according to the high frequency gain, suppressing the intermediate frequency component according to the intermediate frequency gain, performing an image characteristic dependence enhancement suppression process,
An image processing method characterized in that a processed image signal is obtained by synthesizing the high frequency component and the intermediate frequency component after the processing, and the low frequency component ,
In the decomposition of the original image signal, at least the low frequency component among the respective frequency components after the decomposition is RGB data,
In the step of setting the high frequency gain and the intermediate frequency gain,
For each pixel to be subjected to the image processing, it is represented by the sum of the difference in luminance signal between pixels adjacent in the main scanning direction and the difference in luminance signal between pixels adjacent in the sub-scanning direction. And detecting the detected edge index and setting the high frequency gain and the intermediate frequency gain having a magnitude corresponding to the detected edge index for each pixel . 2. The image processing method according to claim 1 , wherein the luminance signal of the original image signal is a signal representing a Y component when the RGB color data of the intermediate / high frequency component is subjected to YIQ specified conversion. Prior to decomposing the original image signal, based on RGB color data of the original image signal, a basic high frequency gain for enhancing the high frequency component of the original image signal, and the original image signal Setting a basic intermediate frequency gain to suppress the intermediate frequency component;
In the step of setting the high frequency gain and the intermediate frequency gain,
An intensity coefficient for adjusting the basic high frequency gain and the basic intermediate frequency gain is set according to the luminance signal,
The high frequency gain is calculated and set by multiplying the basic high frequency gain by the intensity coefficient according to the luminance signal, and the basic intermediate frequency gain is multiplied by the intensity coefficient according to the luminance signal. 3. The image processing method according to claim 1, wherein the intermediate frequency gain is calculated and set. In the step of setting the high frequency gain and the intermediate frequency gain,
The intensity coefficient is determined according to a detected edge index calculated according to the luminance signal, and the intensity coefficient is set to 1.0 when the detected edge index is larger than a predetermined value , and the detected edge 4. The method according to claim 1 , wherein when the index is smaller than the predetermined value, the index is set to monotonically increase from 0.0 to 1.0 at a predetermined rate according to the magnitude of the detected edge index . The image processing method according to any one of the above. An image processing apparatus that performs predetermined image processing on an original image signal representing a predetermined color image,
Means for calculating a luminance signal of the original image signal;
Means for decomposing the original image signal into a low frequency component, an intermediate frequency component, and a high frequency component;
The high-frequency gain for emphasizing the high frequency components of the original image signal, and sets in response to said luminance signal of the original image signal, an intermediate for suppressing the intermediate frequency component of the original image signal Means for setting a frequency gain according to the luminance signal of the original image signal ;
Means for emphasizing the high frequency component according to the high frequency gain and suppressing the intermediate frequency component according to the intermediate frequency gain;
An image processing apparatus comprising: a high-frequency component and an intermediate frequency component after processing, and a means for synthesizing the low-frequency component to obtain a processed image signal,
The means for decomposing the RGB data at least the low frequency component of each frequency component after the decomposition,
The means for setting the high frequency gain and the intermediate frequency gain are:
For each pixel to be subjected to the image processing, it is represented by the sum of the difference in luminance signal between pixels adjacent in the main scanning direction and the difference in luminance signal between pixels adjacent in the sub-scanning direction. And detecting the detected edge index and setting the high frequency gain and the intermediate frequency gain having a magnitude corresponding to the detected edge index for each pixel . 6. The image processing apparatus according to claim 5 , wherein the luminance signal of the original image signal is a signal representing a Y component when the RGB color data of the intermediate / high frequency component is subjected to YIQ specified conversion. Prior to decomposing the original image signal, based on RGB color data of the original image signal, a basic high frequency gain for enhancing the high frequency component of the original image signal, and the original image signal Means for setting a basic intermediate frequency gain for suppressing the intermediate frequency component;
In the means for setting the high frequency gain and the intermediate frequency gain,
An intensity coefficient for adjusting the basic high frequency gain and the basic intermediate frequency gain is set according to the luminance signal,
The high frequency gain is calculated and set by multiplying the basic high frequency gain by the intensity coefficient according to the luminance signal, and the basic intermediate frequency gain is multiplied by the intensity coefficient according to the luminance signal. The image processing apparatus according to claim 5, wherein the intermediate frequency gain is calculated and set. In the means for setting the high frequency gain and the intermediate frequency gain,
The intensity coefficient is determined according to a detected edge index calculated according to the luminance signal, and the intensity coefficient is set to 1.0 when the detected edge index is larger than a predetermined value. if the exponent is less than the predetermined value, according to claim 5-6, characterized in that set to monotonously increases at a predetermined rate until 0.0 from 1.0 in accordance with the size of the detected edge index The image processing apparatus according to any one of the above.

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