JP4374686B2 - Image sharpness determination method, recording medium storing program for performing processing for determining image sharpness, image processing apparatus, and photographic printing apparatus - Google Patents

Description

【００７３】
なお、図３に示すフィルタの係数は一例であり、この係数に限定されるわけではない。また、図３のフィルタは、ガウシアンフィルタとなっているが、このフィルタに限定されるわけではなく、その他、移動平均フィルタやメディアンフィルタであってもよい。
【００７４】
第１エッジ強度算出部６は、ＢＧＲ／輝度変換部４にて得られる元画像の画素値ｏ（ｉ，ｊ）に例えば図４に示すラプラシアンフィルタを作用させて、元画像のエッジ強度ｅｏ（ｉ，ｊ）を第１エッジ強度として算出するものである。なお、図４に示すラプラシアンフィルタの係数は一例であり、この係数に限定されるわけではない。一方、第２エッジ強度算出部７は、平滑化画像作成部５にて得られる平滑化画像の画素値ｂ（ｉ，ｊ）に例えば図４に示すラプラシアンフィルタを作用させて、平滑化画像のエッジ強度ｅｂ（ｉ，ｊ）を第２エッジ強度として算出するものである。
【００７５】
なお、上記のエッジ強度ｅｏ（ｉ，ｊ）、ｅｂ（ｉ，ｊ）は、いずれも、画像中の直線状の領域の各位置（画素位置）における画像データ（濃度値）の変化をグラフとして示したときの濃度勾配に対応するものである。
【００７６】
鮮鋭度判断部８は、元画像のエッジ強度ｅｏ（ｉ，ｊ）と平滑化画像のエッジ強度ｅｂ（ｉ，ｊ）とに基づいて元画像の鮮鋭度を判断するものであるが、その詳細については後述する。
【００７７】
鮮鋭化処理部９は、鮮鋭度判断部８にて元画像の鮮鋭度が低いと判断された場合に、元画像のＢＧＲの画像データに対して例えばラプラシアンフィルタを作用させ、鮮鋭化処理を行うものである。元画像Ｆ（ｉ，ｊ）のラプラシアン画像を▽² Ｆ（ｉ，ｊ）とすれば、鮮鋭化画像の画像Ｇ（ｉ，ｊ）は、ＢＧＲごとに以下の式により求められ、その画像データがＢＧＲごとに露光部３に送られる。
【００７８】
Ｇ（ｉ，ｊ）＝Ｆ（ｉ，ｊ）−▽² Ｆ（ｉ，ｊ）
一方、鮮鋭化処理部９は、鮮鋭度判断部８にて元画像の鮮鋭度が高いと判断された場合には、元画像に対しては上記の鮮鋭化処理を行わず、元画像のＢＧＲの画像データをそのまま露光部３に送る。
【００７９】
次に、鮮鋭度判断部８の詳細について説明する。
【００８０】
鮮鋭度判断部８は、元画像のエッジ強度ｅｏ（ｉ，ｊ）と平滑化画像のエッジ強度ｅｂ（ｉ，ｊ）とに基づいて、以下のような方法で元画像の鮮鋭度を判断する。
【００８１】
まず、鮮鋭度判断部８は、元画像の後述する所定画素（ｉ，ｊ）におけるエッジ強度ｅｏ（ｉ，ｊ）と、上記所定画素と平滑化画像上で対応する画素（ｉ，ｊ）におけるエッジ強度ｅｂ（ｉ，ｊ）とから、エッジ強度比｜ｅｂ（ｉ，ｊ）／ｅｏ（ｉ，ｊ）｜（＝ｆ）の相対度数分布を求める。このようにして求めた相対度数分布の例を図５（ａ）および図５（ｂ）に示す。図５（ａ）は、元画像が元々鮮鋭度の高い画像の場合に得られる相対度数分布を示し、図５（ｂ）は、元画像が鮮鋭度の低いぼけ画像である場合に得られる相対度数分布を示している。これらの図面における縦軸は、全度数に対する相対値、すなわち相対度数を示している（各エッジ強度比ｆの値に対応する度数を全部足し合わせると１になる）。
【００８２】
ここで、上記した元画像の上記所定画素とは、元画像の注目画素（ｉ，ｊ）におけるエッジ強度ｅｏ（ｉ，ｊ）と、当該画素の上下左右の画素におけるエッジ強度ｅｏ（ｉ＋１，ｊ）、ｅｏ（ｉ−１，ｊ）、ｅｏ（ｉ，ｊ−１）およびｅｏ（ｉ，ｊ＋１）とを取り出してそれぞれの絶対値を求めたときに、エッジ強度ｅｏ（ｉ，ｊ）の絶対値が最大となる場合の画素を指す。当該所定画素のエッジ強度がその周囲の画素のエッジ強度よりも高いことから、当該所定画素は、画像中のあるエッジの中でエッジ強度が最も高い部分に対応していることになる。つまり、このような上記所定画素を考えることにより、画像中のエッジ部分を確実に認識することが可能となる。
【００８３】
上記所定画素が画像中のエッジ部分であるか否かの判別に用いる画素、つまり、エッジ強度比ｆを求めるためのエッジ強度ｅｏ（ｉ，ｊ）を決定するのに用いられる画素は、注目画素を含む上記の５画素に限定されるわけではない。例えば注目画素とその上下の画素の３画素、あるいは注目画素とその左右の画素の３画素であってもよく、注目画素とその上下方向に並ぶ４つ以上の画素や、注目画素とその左右方向に並ぶ４つ以上の画素であっても構わない。
【００８４】
つまり、上記エッジ強度ｅｏ（ｉ，ｊ）の決定に用いられる画素は、元画像における注目画素と、上記注目画素の上下方向に位置する画素と上記注目画素の左右方向に位置する画素とのうち少なくとも一方の画素とであればよい。上記エッジ強度ｅｏ（ｉ，ｊ）の決定に、注目画素とその上下左右に隣接する画素との合わせて５画素を用いると、注目画素のエッジ情報を相対度数分布に確実に反映させることができ、後述の鮮鋭度の判断をより適切に行うことができる。また、上記エッジ強度ｅｏ（ｉ，ｊ）の決定に、注目画素とその上下の画素、あるいは注目画素とその左右の画素を用いると、少ない画素数でも、注目画素のエッジ情報を相対度数分布に反映させることができる。
【００８５】
また、注目画素から見て斜めに位置する画素の情報は、注目画素の上下左右に位置する画素にそれぞれ反映されるので、上記の判別に、注目画素とその周囲８画素の計９画素をあえて用いる必要はないが、別にこれら９画素を用いても構わない。
【００８６】
ところで、鮮鋭度の高い画像ほどエッジ部分におけるエッジ強度ｅｏ（ｉ，ｊ）は高くなるので、エッジ部分の画素におけるエッジ強度比ｆの値は小さくなる。したがって、値の小さいエッジ強度比ｆに対応する相対度数が多ければ多いほど、そのような点が画像中に多く存在することになり、この場合、元画像全体が鮮鋭であると言える。しかし、あまりにも小さいエッジ強度比ｆの相対度数の大小を考えても、画像の鮮鋭度の判断を適切に行うことができないことが実験的に分かっている。
【００８７】
そこで、鮮鋭度判断部８は、上記のような相対度数分布を求めると、エッジ強度比ｆが高い値（例えばｆ＝０．３）となる場合の相対度数Ｈと、エッジ強度比ｆが低い値（例えばｆ＝０．２）となる場合の相対度数Ｌとを認識すると共に、これら相対度数の比Ｈ／Ｌを求め、この比Ｈ／Ｌと閾値との大小関係を比較するようになっている。上記閾値を例えば１に設定すれば、単に相対度数Ｈと相対度数Ｌとの大小関係を比較することになる。
【００８８】
閾値が１であり、比Ｈ／Ｌが閾値よりも小さい場合、上記相対度数Ｈが上記相対度数Ｌよりも小さくなる。この場合、より小さいエッジ強度比ｆに対応する相対度数が他方の相対度数よりも大きいので、この場合は、画像全体が鮮鋭であると言える。一方、閾値が１であり、比Ｈ／Ｌが閾値以上の場合は、上記とは逆の原理により、画像全体がぼけていると言える。
【００８９】
なお、上記の閾値は、鮮鋭度の判断の厳しさを調整するパラメータに過ぎず、閾値を１以外の値に設定しても、より小さいエッジ強度比ｆに対応する相対度数と他方の相対度数との相対比較により、画像全体の鮮鋭度を判断できることにかわりはない。
【００９０】
したがって、鮮鋭度判断部８は、比Ｈ／Ｌが閾値以上であれば、元画像がぼけ画像であると判断する一方、比Ｈ／Ｌが閾値よりも小さければ、元画像が鮮鋭度の高い画像であると判断する。このように、本実施形態では、比Ｈ／Ｌと閾値との大小関係に基づいて画像の鮮鋭度を判断するので、上記の比Ｈ／Ｌは、鮮鋭度を判断する対象となる元画像のエッジ鮮鋭度を示しているということができる。
【００９１】
なお、ｆ＝０．２や０．３の場合の相対度数をＨやＬとして採用しているのは、ｆ＝０．１や０．４〜１．０の相対度数を考慮しても、あらゆる画像に対して鮮鋭度を適切に判断できない結果が予め実験的に得られたからである。つまり、ｆ＝０．１や０．４〜１．０の相対度数は、鮮鋭度を判断する上で信用性の薄い値であるので、本実施形態ではそれらの値を採用してはいない。
【００９２】
なお、相対度数Ｈをとるエッジ強度比ｆは上記の０．３に限定されるわけではなく、相対度数分布を作成したときに例えばｆ＝０．２５〜０．３５の範囲内で度数が得られるような値のうち最大のものであればよいことが実験的に分かっている。また、同様に、相対度数Ｌをとるエッジ強度比ｆも上記の０．２に限定されるわけではなく、相対度数分布を作成したときに例えばｆ＝０．１５〜０．２５の範囲内で度数が得られるような値のうち最小のものであればよいことが実験的に分かっている。
【００９３】
つまり、相対度数ＨやＬに対応するそれぞれのエッジ強度比ｆの値は、あらゆる画像に対してその鮮鋭度を判断するのに有効な値であればよい。これにより、鮮鋭度の判断結果が元画像によってばらつくことがない。
【００９４】
次に、画像処理部２での動作について、主に図１のフローチャートに基づいて説明する。
【００９５】
まず、画像取込部１からＢＧＲの各画像データが画像処理部２に送られると、画像処理部２のＢＧＲ／輝度変換部４は、上記ＢＧＲの各画像データから各画素ごとに輝度画像データＹ（画素値ｏ（ｉ，ｊ））を生成し、当該画素値ｏ（ｉ，ｊ）を平滑化画像作成部５および第１エッジ強度算出部６へ送る（ステップ１；以下、ステップは単にＳと略記する）。すると、平滑化画像作成部５は、各画素値ｏ（ｉ，ｊ）に図３のデジタルフィルタの係数をかけ、元画像の平滑化画像を作成する、つまり、平滑化画像の画素値ｂ（ｉ，ｊ）を演算する（Ｓ２；第１の工程）。
【００９６】
次に、第１エッジ強度算出部６は、各画素値ｏ（ｉ，ｊ）に図４のフィルタの係数をかけ、元画像の各画素のエッジ強度ｅｏ（ｉ，ｊ）を算出する（Ｓ３；第３の工程）。一方、第２エッジ強度算出部７は、平滑化画像作成部５にて得られる平滑化画像の画素値ｂ（ｉ，ｊ）に図４のフィルタの係数をかけ、平滑化画像の各画素のエッジ強度ｅｂ（ｉ，ｊ）を算出する（Ｓ４；第３の工程）。
【００９７】
次に、鮮鋭度判断部８は、元画像の所定画素のエッジ強度ｅｏ（ｉ，ｊ）と、上記所定画素と平滑化画像上で対応する画素のエッジ強度ｅｂ（ｉ，ｊ）とから、エッジ強度比｜ｅｂ（ｉ，ｊ）／ｅｏ（ｉ，ｊ）｜（＝ｆ）の相対度数分布を求める（Ｓ５）。なお、上記所定画素のエッジ強度ｅｏ（ｉ，ｊ）の選定については、上述の通りである。つまり、元画像と平滑化画像とでエッジ強度の比をとるか否かを、元画像の注目画素のエッジ強度をその周囲の画素のエッジ強度と比較することによって決定する。
【００９８】
そして、鮮鋭度判断部８は、例えばｆ＝０．３となる場合の相対度数Ｈと、ｆ＝０．２となる場合の相対度数Ｌとから比Ｈ／Ｌを求め、この比Ｈ／Ｌが閾値（例えば１）以上であるか否かを判断する（Ｓ７）。鮮鋭度判断部８は、このＳ７にて、比Ｈ／Ｌが閾値以上であると判断した場合には、元画像がぼけ画像であると判断する一方、比Ｈ／Ｌが閾値よりも小さければ、元画像が鮮鋭度の高い画像であると判断する。なお、Ｓ５〜Ｓ７の工程は、特許請求の範囲に記載の第４の工程に対応している。
【００９９】
鮮鋭化処理部９は、Ｓ７にてぼけ画像と判断された元画像に対しては、元画像のＢＧＲの各画像データに対してラプラシアンフィルタを作用させて鮮鋭化処理を行い（Ｓ８）、処理済みのＢＧＲの各画像データを露光部３に送る。一方、鮮鋭化処理部９は、Ｓ７にて鮮鋭度の高い画像と判断された元画像に対しては、上記の鮮鋭化処理を行わず（Ｓ９）、元画像のＢＧＲの各画像データをそのまま露光部３に送る。露光部３では、鮮鋭化画像のＢＧＲの各画像データまたは元画像のＢＧＲの各画像データに基づいて上述した印画紙の露光が行われることになる。
【０１００】
次に、図５（ａ）または図５（ｂ）に示す相対度数分布を作成し、相対度数の比Ｈ／Ｌと閾値との大小関係を比較することによって、本発明の効果が得られる理由について説明する。
【０１０１】
鮮鋭なエッジとは、画像データの変化区間の幅が小さいエッジであると考えられる。したがって、画像データの変化区間の小さいエッジを抽出して元画像の鮮鋭度を判断できれば、その判断は適切なものとなる。つまり、鮮鋭度の判断においては、画像データの変化区間の大小をどのようにして認識するかがポイントとなる。
【０１０２】
図６は、元画像とそのぼけ画像とで、画像中のあるエッジ部分における画像データの変化を示している。同図中、直線Ａは、元画像における画像データの変化を示し、直線Ｂは、ぼけ画像における画像データの変化を示している。同図に示すように、元画像でのエッジ幅をｗ、平滑化に使用するデジタルフィルタの半径をｒ（定数）とすると、ぼけ画像でのエッジ幅は、ｗ＋２ｒ程度になる。これは、エッジの両端でｒずつエッジの情報が広がるためである。
【０１０３】
ところで、元画像の平滑化によってエッジ幅は大きくなるが、元画像で鮮鋭なエッジほどエッジ幅が小さいため、例えば、ぼけ画像と元画像とにおけるエッジ幅の比、すなわち、（ぼけ画像のエッジ幅）／（元画像のエッジ幅）の値は、元画像が鮮鋭な場合ほど大きくなる。つまり、（ぼけ画像のエッジ幅）／（元画像のエッジ幅）＝（ｗ＋２ｒ）／ｗ＝１＋２ｒ／ｗとなるので、エッジが鮮鋭であれば（ｗが小さければ）、上記エッジ幅比が大きくなる。したがって、このようなエッジ幅比を考えれば、元画像の各エッジの鮮鋭度を適切に判断することができる。これにより、元画像に含まれる複数のエッジのうち、鮮鋭なエッジの情報を用いて画像の鮮鋭度を判断することが可能となる。
【０１０４】
しかし、各エッジ幅の値は、各画像からは簡単に得られないので、各エッジ幅の値から上記エッジ幅比を求めることはできない。そこで、本発明では、デジタルフィルタをかけることで簡単に得られるエッジ強度を利用して、以下のようにして上記エッジ幅比を考えるようにしている。
【０１０５】
上記両画像における画像データの変化量をｈとすれば、元画像のエッジ強度ｅｏはｈ／ｗとなり、ぼけ画像のエッジ強度ｅｂはｈ／（ｗ＋２ｒ）となるので、エッジ強度比ｆは、ｅｂ／ｅｏ＝｛ｈ／（ｗ＋２ｒ）｝／（ｈ／ｗ）＝ｗ／（ｗ＋２ｒ）となる。このとき、エッジ強度比ｆの逆数である１／ｆは、（ｗ＋２ｒ）／ｗ＝１＋２ｒ／ｗとなる。つまり、上記したエッジ幅比は、エッジ強度比ｆの逆数と等価である。したがって、元画像とぼけ画像とで得られるエッジ強度を利用することにより、上記エッジ幅比を考えることができる。
【０１０６】
ただし、エッジ強度比ｆの１個の値だけに基づいて、あるいは、エッジ強度比ｆと閾値との１個の大小関係だけに基づいて元画像全体の鮮鋭度を判断することはできない。なぜならば、上記エッジ強度比ｆは、元画像の一画素とぼけ画像の一画素との間で得られる関係を示しているものに過ぎないからである。つまり、エッジ強度比ｆの一つ一つは、画素によって異なる値であり、どれか一つのエッジ強度比ｆの値で画像全体の鮮鋭度を判断するのは危険だからである。
【０１０７】
そこで、本実施形態では、エッジ強度比ｆの相対度数分布を作成すると共に、互いに異なるエッジ強度比ｆのそれぞれに対応する相対度数の比を考え、上記相対度数の比と閾値との大小関係を比較している。この手法により、エッジ強度比ｆがより小さい値となるような画素、すなわち、逆数１／ｆが大きい値となるような画素の、画像全体に占める割合を客観的に把握することができる。逆数１／ｆが大きい値となるような画素の割合が多ければ、エッジ幅の比の大きい画素の割合が多いことになり、結果的に、元画像に鮮鋭なエッジが多く含まれることになる。
【０１０８】
また、画像データの変化量ｈは、同じ画像でもエッジ間で異なるため、鮮鋭度の評価においては、上記ｈのばらつきの影響を取り除く、つまり、上記ｈについて正規化する必要がある。ここで、ぼけ画像のエッジ強度ｅｂは、上記したようにｈ／（ｗ＋２ｒ）で得られ、ｈの情報を含んでいる。また、元画像のエッジ強度ｅｏは、ｈ／ｗで得られ、やはりｈの情報を含んでいる。しかし、ぼけ画像のエッジ強度ｅｂと元画像のエッジ強度ｅｏとで得られるエッジ強度比ｆを演算することにより、エッジ強度比ｆからｈの情報を除外することができる。つまり、エッジ強度比ｆに正規化の概念を含ませることができる。
【０１０９】
したがって、元画像が画像データの変化量の異なる部分を含んでいても、上記エッジ強度比ｆを演算することによって、画像データの変化量を正規化したときの画像データの変化区間の大小を必然的に見ていることになる。これにより、エッジ強度比ｆの相対度数分布を作成すれば、真に鮮鋭なエッジの情報を確実に上記相対度数分布に反映させることができる。
【０１１０】
したがって、本発明によれば、元画像がどのような画像であっても、上記相対度数分布に基づいて、元画像の鮮鋭度を適切かつ安定して判断することができる。
【０１１１】
また、相対度数分布を作成したり、相対度数の比と閾値との大小関係を比較するのは非常に単純な処理であり、複雑な計算は必要ないので、鮮鋭度の判断は容易なものとなる。また、本発明では、鮮鋭度の判断結果を安定させるために必要な計算量自体も少なくなるので、鮮鋭度の判断を従来よりも迅速に行うことができる。
【０１１２】
ところで、エッジ強度比ｆの単なる度数分布（エッジ強度比ｆの値をとる度数の絶対数の分布）を作成し、互いに異なるエッジ強度比ｆの値に対応する度数（絶対数）の比と閾値との大小関係を比較することによって元画像の鮮鋭度を判断するようにしてもよい。しかし、エッジ強度比ｆの単なる度数分布では、元画像を構成する画素数が変化すれば、その分布形状も変化するので、元画像の画素数に応じた閾値の設定が必要となる。これに対して、エッジ強度比ｆの相対度数分布を作成した場合は、元画像の画素数が異なる場合でも、同等の鮮鋭度の画像についてはほぼ同じ分布形状を得ることができ、元画像の画素数に応じた閾値の設定が不要である。したがって、エッジ強度比ｆの相対度数分布を作成するほうが、鮮鋭度の判断をより容易に行うことができる。
【０１１３】
なお、相対度数分布の横軸におけるエッジ強度比ｆの値の間隔、相対度数ＨやＬに対応するエッジ強度比ｆのとりえる区間、閾値などは、実験や経験に基づいて設定される経験定数であるが、これらを適宜変更することは容易である。
【０１１４】
また、元画像において主要被写体の背景部分がぼけている場合には、そのような背景部分を除いて主要被写体部分に対応する相対度数分布を作成するようにすれば、本発明の方法により主要被写体部分の鮮鋭度を適切に判断することができる。
【０１１５】
以上で説明した処理は、画像の鮮鋭度の判断処理を機能させるためのプログラムで実現される。このプログラムはコンピュータで読み取り可能な記録媒体に格納されている。本発明では、この記録媒体として、図２の画像処理部２で処理が行われるために必要な図示していないメモリ（例えばＲＯＭそのもの）であってもよいし、また図示していないが外部記憶装置としてプログラム読み取り装置が設けられ、そこに記録媒体を挿入することで読み取り可能なプログラムメディアであってもよい。
【０１１６】
上記いずれの場合においても、格納されているプログラムはマイクロプロセッサ（図示せず）のアクセスにより実行される構成であってもよいし、格納されているプログラムを読み出し、読み出したプログラムを画像処理部２の図示されていないプログラム記憶エリアにダウンロードすることにより、そのプログラムが実行される構成であってもよい。この場合、ダウンロード用のプログラムは予め本体装置に格納されているものとする。
【０１１７】
ここで、上記プログラムメディアは、本体と分離可能に構成される記録媒体であり、磁気テープやカセットテープ等のテープ系、フロッピーディスクやハードディスク等の磁気ディスクやＣＤ−ＲＯＭ／ＭＯ／ＭＤ／ＤＶＤ等の光ディスクのディスク系、ＩＣカード（メモリカードを含む）／光カード等のカード系、あるいはマスクＲＯＭ、ＥＰＲＯＭ、ＥＥＰＲＯＭ、フラッシュＲＯＭ等による半導体メモリを含めた固定的にプログラムを担持する媒体であってもよい。
【０１１８】
また、本発明においては、インターネットを含む通信ネットワークと接続可能なシステム構成であることから、通信ネットワークからプログラムをダウンロードするように流動的にプログラムを担持する媒体であってもよい。なお、このように通信ネットワークからプログラムをダウンロードする場合には、そのダウンロード用プログラムは予め本体装置に格納しておくか、あるいは別な記録媒体からインストールされるものであってもよい。
【０１１９】
なお、記録媒体に格納されている内容としてはプログラムに限定されず、データであってもよい。
【０１２０】
以上では、鮮鋭度判断部８における鮮鋭度の判断を、輝度画像データＹを用いて行う場合について説明したが、画像取込部１からのＢＧＲの画像データを用い、ＢＧＲのそれぞれについて鮮鋭度の判断を行うようにしてもよい。この場合、ＢＧＲ／輝度変換部４が不要となるので、画像処理部２の構成をより簡素化することができる。しかし、ＢＧＲ別々に鮮鋭度の判断を行うようにすると、ＢＧＲのそれぞれについて異なった鮮鋭度の判断がされるおそれもあるので、このことを考えれば、本実施形態のように輝度画像データＹを用いて鮮鋭度の判断を行うようにするほうがよい。
【０１２１】
また、以上では、鮮鋭化処理部９が画像取込部１からのＢＧＲの画像データを用い、ＢＧＲのそれぞれについて鮮鋭化処理を行うようにしているが、ＢＧＲ／輝度変換部４にて得られた輝度画像データＹを用いて鮮鋭化処理を行うようにしてもよい。この場合、鮮鋭化処理された画像の輝度画像データｙをＢＧＲの各画像データに変換して露光部３に供給する輝度／ＢＧＲ変換部を設けることが必要となる。
【０１２２】
このとき、輝度／ＢＧＲ変換部にて、ＢＧＲの各画像データは例えば以下のようにして求められる。
【０１２３】
Ｂ＝ｂ＋Ｙ−ｙ
Ｇ＝ｇ＋Ｙ−ｙ
Ｒ＝ｒ＋Ｙ−ｙ
ただし、上記のｂ、ｇ、ｒは、ＢＧＲ／輝度変換部４にて変換される前のＢ、Ｇ、Ｒの各画像データであり、Ｙは、ＢＧＲ／輝度変換部４にて変換された後の輝度画像データであり、ｙは、上記輝度／ＢＧＲ変換部にて変換される前の輝度画像データである。
【０１２４】
なお、以上では、ネガフィルムに記録された画像を読み取ってその鮮鋭度を判断する方法について説明したが、ポジフィルム等、その他の写真フィルムに記録された画像を読み取ってその鮮鋭度を判断する場合にも、本発明を適用することができる。
【０１２５】
また、以上では、本発明の鮮鋭度判断方法を写真焼付装置に適用した例について説明したが、例えばデジタルカメラで取り込んだ画像（デジタル画像）の鮮鋭度を判断する場合や、ＰＣのモニタに表示された画像の鮮鋭度を判断する場合にも本発明を適用することができる。
【０１２６】
また、ソフトフォーカスのようなぼけ画像を作成すべく、元画像の画像データに対して平滑化処理を行う前に、元画像の鮮鋭度を調べる際にも、本発明の方法を利用することができる。
【０１２７】
【発明の効果】
請求項１の発明に係る画像の鮮鋭度判断方法は、以上のように、元画像からその平滑化画像を作成する第１の工程と、上記元画像の第１エッジ強度を算出する第２の工程と、上記平滑化画像の第２エッジ強度を算出する第３の工程と、上記第１エッジ強度と上記第２エッジ強度とに基づいて元画像の鮮鋭度を判断する第４の工程とを有し、上記第４の工程は、さらに、上記第２エッジ強度と上記第１エッジ強度との比と、その度数とに基づいて度数分布を作成する工程と、互いに異なる上記比に対応する度数の比を求める工程と、上記度数の比と閾値との大小関係に基づいて元画像の鮮鋭度を判断する工程とを有している構成である。
【０１２８】
それゆえ、エッジ強度比ｆの度数分布が作成されると共に、互いに異なるエッジ強度比ｆに対応する度数の比と閾値との大小関係が比較される。これにより、エッジ強度比ｆがより小さい値となるような画素、すなわち、逆数１／ｆが大きい値となるような画素の、画像全体に占める割合を客観的に把握することができる。逆数１／ｆが大きい値となるような画素の割合が多ければ、平滑化画像と元画像とにおけるエッジ幅の比ｂ／ａの大きい画素の割合が多いことになり、結果的に、元画像に鮮鋭なエッジが多く含まれることになる。
【０１２９】
また、エッジ強度比ｆを演算すれば、ｆ＝ａ／ｂとなり、エッジ強度比ｆから画像データ変化量であるｈの情報を除外することができる。したがって、元画像が画像データの変化量の異なる部分を含んでいても、上記エッジ強度比ｆを演算することによって、画像データの変化量を正規化したときの画像データの変化区間の大小を必然的に見ていることになる。これにより、エッジ強度比ｆの度数分布を作成すれば、真に鮮鋭なエッジの情報を確実に上記度数分布に反映させることができる。
【０１３０】
したがって、上記構成によれば、元画像がどのような画像であっても、上記度数分布に基づいて、元画像の鮮鋭度を適切かつ安定して判断することができるという効果を奏する。
【０１３１】
また、上記度数分布を作成したり、エッジ強度比と閾値との大小関係を比較するのは非常に単純な処理であり、複雑な計算は必要ないので、鮮鋭度の判断を容易に行うことができるという効果を併せて奏する。
【０１３２】
請求項２の発明に係る画像の鮮鋭度判断方法は、以上のように、請求項１の構成において、上記第４の工程は、上記元画像の注目画素における第１エッジ強度とその周囲の画素における第１エッジ強度との中で、上記注目画素における第１エッジ強度が最大となる場合の、上記注目画素における第１エッジ強度と、上記注目画素と上記平滑化画像上で対応する画素の第２エッジ強度とを用いて、上記第２エッジ強度と上記第１エッジ強度との比を求める工程をさらに含んでいる構成である。
【０１３３】
それゆえ、元画像において周囲の画素よりも第１エッジ強度の高い画素は、画像中で確実にエッジ部分に対応していることが言える。したがって、そのような画素の第１エッジ強度と、第２エッジ強度とを用いてエッジ強度比を求めることにより、このエッジ強度比を用いて作成した度数分布に基づいて行う元画像の鮮鋭度の判断を、元画像のエッジ部分の鮮鋭度を確実に考慮して行うことができる。その結果、請求項１の構成による効果に加えて、鮮鋭度の判断結果の信頼性を確実に向上させることができるという効果を奏する。
【０１３４】
請求項３の発明に係る画像の鮮鋭度判断方法は、以上のように、請求項２の構成において、上記第２エッジ強度と上記第１エッジ強度との比を求めるための上記第１エッジ強度を決定するのに用いられる画素は、元画像における注目画素と、上記注目画素の上下方向に位置する画素と上記注目画素の左右方向に位置する画素とのうち少なくとも一方の画素とである構成である。
【０１３５】
それゆえ、注目画素から見て斜め方向に位置する画素の情報は、注目画素の上下左右に位置する画素にそれぞれ反映されている。したがって、エッジ強度比を求めるための上記第１エッジ強度を決定するのに用いられる画素として、元画像における注目画素と、上記注目画素の上下方向に位置する画素と上記注目画素の左右方向に位置する画素とのうち少なくとも一方の画素とを考えても、元画像のエッジ部分の鮮鋭度を確実に考慮して元画像全体の鮮鋭度の判断を行うことができる。つまり、請求項２に構成による効果に加えて、注目画素の周囲の全ての画素の第１エッジ強度を考えなくても、少ない画素数で上記鮮鋭度の判断を適切に行うことができるという効果を奏する。
【０１３６】
特に、注目画素と、その上下方向および左右方向に位置する画素とを上記決定の考慮に入れれば、上述の効果を確実に得ることができるという効果を併せて奏する。
【０１３７】
請求項４の発明に係る画像の鮮鋭度判断方法は、以上のように、請求項１ないし３のいずれかの構成において、上記度数は、各比に対応する度数を全て足し合わせた全度数に対する相対度数である構成である。
【０１３８】
それゆえ、エッジ強度比とその相対度数とからなる相対度数分布を作成した場合は、元画像の画素数が異なる場合でも、同等の鮮鋭度の画像についてはほぼ同じ分布形状を得ることができる。これにより、元画像の画素数に応じた閾値の設定を不要とすることができ、請求項１ないし３のいずれかの構成による効果に加えて、鮮鋭度の判断をより容易に行うことができるという効果を奏する。
【０１３９】
請求項５の発明に係る、画像の鮮鋭度を判断する処理を行うためのプログラムを記録した記録媒体は、以上のように、元画像からその平滑化画像を作成する第１の処理と、上記元画像の第１エッジ強度を算出する第２の処理と、上記平滑化画像の第２エッジ強度を算出する第３の処理と、上記第１エッジ強度と上記第２エッジ強度とに基づいて元画像の鮮鋭度を判断する第４の処理とをコンピュータに実行させるためのプログラムを記録してなり、上記第４の処理は、さらに、上記第２エッジ強度と上記第１エッジ強度との比と、その度数とに基づいて度数分布を作成する処理と、互いに異なる上記比に対応する度数の比を求める処理と、上記度数の比と閾値との大小関係に基づいて元画像の鮮鋭度を判断する処理とからなっている構成である。
【０１４０】
それゆえ、上記記録媒体のプログラムがコンピュータにて実行されると、エッジ強度比ｆの度数分布が作成されると共に、互いに異なるエッジ強度比ｆに対応する度数の比と閾値との大小関係が比較される。これにより、エッジ強度比ｆがより小さい値となるような画素、すなわち、逆数１／ｆが大きい値となるような画素の、画像全体に占める割合を客観的に把握することができる。逆数１／ｆが大きい値となるような画素の割合が多ければ、平滑化画像と元画像とにおけるエッジ幅の比ｂ／ａの大きい画素の割合が多いことになり、結果的に、元画像に鮮鋭なエッジが多く含まれることになる。
【０１４１】
また、エッジ強度比ｆを演算すれば、ｆ＝ａ／ｂとなり、エッジ強度比ｆから画像データ変化量であるｈの情報を除外することができる。したがって、元画像が画像データの変化量の異なる部分を含んでいても、上記エッジ強度比ｆを演算することによって、画像データの変化量を正規化したときの画像データの変化区間の大小を必然的に見ていることになる。これにより、エッジ強度比ｆの度数分布を作成すれば、真に鮮鋭なエッジの情報を確実に上記度数分布に反映させることができる。
【０１４２】
したがって、本発明の記録媒体を用いてコンピュータを駆動すれば、元画像がどのような画像であっても、上記度数分布に基づいて、元画像の鮮鋭度を適切かつ安定して判断することができるという効果を奏する。
【０１４３】
また、上記度数分布を作成したり、エッジ強度比と閾値との大小関係を比較するのは非常に単純な処理であり、複雑な計算は必要ないので、鮮鋭度の判断を容易に行うことができるという効果を併せて奏する。
【０１４４】
請求項６の発明に係る画像処理装置は、以上のように、元画像からその平滑化画像を作成する平滑化画像作成手段と、上記元画像の第１エッジ強度を算出する第１エッジ強度算出手段と、上記平滑化画像の第２エッジ強度を算出する第２エッジ強度算出手段と、上記第１エッジ強度と上記第２エッジ強度とに基づいて元画像の鮮鋭度を判断する鮮鋭度判断手段とを備え、上記鮮鋭度判断手段は、上記第２エッジ強度と上記第１エッジ強度との比と、その度数とに基づいて度数分布を作成すると共に、互いに異なる上記比に対応する度数の比を求め、上記度数の比と閾値との大小関係に基づいて元画像の鮮鋭度を判断する構成である。
【０１４５】
それゆえ、鮮鋭度判断手段が、エッジ強度比ｆの度数分布が作成されると共に、互いに異なるエッジ強度比ｆに対応する度数の比と閾値との大小関係が比較される。これにより、エッジ強度比ｆがより小さい値となるような画素、すなわち、逆数１／ｆが大きい値となるような画素の、画像全体に占める割合を客観的に把握することができる。逆数１／ｆが大きい値となるような画素の割合が多ければ、平滑化画像と元画像とにおけるエッジ幅の比ｂ／ａの大きい画素の割合が多いことになり、結果的に、元画像に鮮鋭なエッジが多く含まれることになる。
【０１４６】
また、エッジ強度比ｆを演算すれば、ｆ＝ａ／ｂとなり、エッジ強度比ｆから画像データ変化量であるｈの情報を除外することができる。したがって、元画像が画像データの変化量の異なる部分を含んでいても、上記エッジ強度比ｆを演算することによって、画像データの変化量を正規化したときの画像データの変化区間の大小を必然的に見ていることになる。これにより、エッジ強度比ｆの度数分布を作成すれば、真に鮮鋭なエッジの情報を確実に上記度数分布に反映させることができる。
【０１４７】
したがって、上記構成によれば、元画像がどのような画像であっても、上記度数分布に基づいて、元画像の鮮鋭度を適切かつ安定して判断することができるという効果を奏する。
【０１４８】
また、上記度数分布を作成したり、エッジ強度比と閾値との大小関係を比較するのは非常に単純な処理であり、複雑な計算は必要ないので、鮮鋭度の判断を容易に行うことができるという効果を併せて奏する。
【０１４９】
請求項７の発明に係る画像処理装置は、以上のように、請求項６の構成において、上記鮮鋭度判断手段は、上記元画像の注目画素における第１エッジ強度とその周囲の画素における第１エッジ強度との中で、上記注目画素における第１エッジ強度が最大となる場合の、上記注目画素における第１エッジ強度と、上記注目画素と上記平滑化画像上で対応する画素の第２エッジ強度とを用いて、上記第２エッジ強度と上記第１エッジ強度との比を求める構成である。
【０１５０】
それゆえ、元画像において周囲の画素よりも第１エッジ強度の高い画素は、画像中で確実にエッジ部分に対応していることが言える。したがって、そのような画素の第１エッジ強度と、第２エッジ強度とを用いてエッジ強度比を求めることにより、このエッジ強度比を用いて作成した度数分布に基づいて行う元画像の鮮鋭度の判断を、元画像のエッジ部分の鮮鋭度を確実に考慮して行うことができる。その結果、請求項６の構成による効果に加えて、鮮鋭度の判断結果の信頼性を確実に向上させることができる。
【０１５１】
請求項８の発明に係る画像処理装置は、以上のように、請求項７の構成において、上記第２エッジ強度と上記第１エッジ強度との比を求めるための上記第１エッジ強度を決定するのに用いられる画素は、元画像における注目画素と、上記注目画素の上下方向に位置する画素と上記注目画素の左右方向に位置する画素とのうち少なくとも一方の画素とである構成である。
【０１５２】
それゆえ、注目画素から見て斜め方向に位置する画素の情報は、注目画素の上下左右に位置する画素にそれぞれ反映されている。したがって、エッジ強度比を求めるための上記第１エッジ強度を決定するのに用いられる画素として、元画像における注目画素と、上記注目画素の上下方向に位置する画素と上記注目画素の左右方向に位置する画素とのうち少なくとも一方の画素とを考えても、元画像のエッジ部分の鮮鋭度を確実に考慮して元画像全体の鮮鋭度の判断を行うことができる。つまり、請求項７に構成による効果に加えて、注目画素の周囲の全ての画素の第１エッジ強度を考えなくても、少ない画素数で上記鮮鋭度の判断を適切に行うことができるという効果を奏する。
【０１５３】
特に、注目画素と、その上下方向および左右方向に位置する画素とを上記決定の考慮に入れれば、上述の効果を確実に得ることができるという効果を併せて奏する。
【０１５４】
請求項９の発明に係る画像処理装置は、以上のように、請求項６ないし８のいずれかの構成において、上記度数は、上記第２エッジ強度と上記第１エッジ強度との各比に対応する度数を全て足し合わせた全度数に対する相対度数である構成である。
【０１５５】
それゆえ、エッジ強度比とその相対度数とからなる相対度数分布を作成した場合は、元画像の画素数が異なる場合でも、同等の鮮鋭度の画像についてはほぼ同じ分布形状を得ることができる。これにより、元画像の画素数に応じた閾値の設定を不要とすることができ、請求項６ないし８のいずれかの構成による効果に加えて、鮮鋭度の判断をより容易に行うことができるという効果を奏する。
【０１５６】
請求項１０の発明に係る画像処理装置は、以上のように、請求項６ないし９のいずれかの構成において、上記鮮鋭度判断手段での判断結果に応じて元画像に対して鮮鋭化処理を行う鮮鋭化処理手段をさらに備えている構成である。
【０１５７】
それゆえ、鮮鋭化処理手段にて必要に応じて元画像に対する鮮鋭化処理が行われるので、請求項６ないし９のいずれかの構成による効果に加えて、元画像がぼけ画像であってもなくても、最終的には高画質の画像を得ることができるという効果を奏する。
【０１５８】
請求項１１の発明に係る写真焼付装置は、以上のように、請求項６ないし１０のいずれかに記載の画像処理装置と、上記画像処理装置にて鮮鋭化処理された画像の画像データまたは元画像の画像データに基づいて感光材料を露光する露光手段とを備えている構成である。
【０１５９】
それゆえ、請求項６ないし１０のいずれかに記載の画像処理装置にて鮮鋭化処理された画像の画像データまたは元画像の画像データに基づいて、上記露光手段が感光材料を露光することにより、高画質な写真プリントを得ることができるという効果を奏する。
【図面の簡単な説明】
【図１】本発明に係る写真焼付装置の画像処理部における動作の流れを示すフローチャートである。
【図２】上記画像処理部の概略の構成を示すブロック図である。
【図３】平滑化画像を作成するためのフィルタの一例を示す説明図である。
【図４】エッジ強度を算出するためのフィルタの一例を示す説明図である。
【図５】（ａ）は、元画像が鮮鋭度の高い画像である場合に得られる、エッジ強度の比の相対度数分布を示す説明図であり、（ｂ）は、元画像がぼけ画像である場合に得られる、エッジ強度の比の相対度数分布を示す説明図である。
【図６】元画像とそのぼけ画像とで、画像中のあるエッジ部分における画像データの変化を示す説明図である。
【図７】画像中の直線状の領域の各画素位置における画像データの変化を模式的に示す説明図である。
【符号の説明】
２ 画像処理部（画像処理装置、コンピュータ）
３ 露光部（露光手段）
５ 平滑化画像作成部（平滑化画像作成手段）
６ 第１エッジ強度算出部（第１エッジ強度算出手段）
７ 第２エッジ強度算出部（第２エッジ強度算出手段）
８ 鮮鋭度判断部（鮮鋭度判断手段）
９ 鮮鋭化処理部（鮮鋭化処理手段）[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image sharpness determination method for determining image sharpness based on image data obtained by reading a photographic film such as a negative film or image data used on a PC (Personal Computer), for example, The present invention relates to a recording medium on which a program for performing processing for determining sharpness, an image processing device for determining sharpness of an image, and a photographic printing apparatus including the image processing device.
[0002]
[Prior art]
When the original image recorded on the negative film is a blurred image with low sharpness, sharpening processing is performed on the image data of the original image, and a photograph is burned based on the processed image data. A print with high image quality can be obtained. On the other hand, when the original image is originally an image with a high sharpness, a high-quality print can be obtained by burning a photograph as it is based on the image data of the original image without performing the sharpening process. be able to.
[0003]
That is, it may be considered that whether or not to perform the sharpening process is determined by the degree of blurring of the original image, that is, the sharpness of the original image. Therefore, it is first necessary to determine the sharpness of the original image in order to obtain a high-quality print. A method for determining the sharpness of the original image is disclosed in, for example, Japanese Patent Laid-Open Nos. 53-70428 and 61-7443.
[0004]
In Japanese Patent Laid-Open No. 53-70428, blurring of an image is detected as follows. That is, a photographic film is scanned linearly to determine a maximum density gradient at a high bandwidth and a maximum density gradient of image content that is blurred by removing high spatial frequency regions. Then, the quotient of these two density gradients is calculated, and image blur is detected based on the magnitude relationship between the quotient and the threshold value.
[0005]
On the other hand, Japanese Patent Laid-Open No. 61-7443 evaluates the sharpness of an original as follows. That is, a plurality of linear regions (pixels) of the document are scanned, and a scanning signal including density information of the scanned region is generated for each region. Next, a sharp signal and a blur signal are respectively generated based on each scanning signal, and each sharp signal is differentiated to calculate a maximum density gradient x, and each blur signal is differentiated to calculate a maximum density gradient y. Then, by comparing the evaluation value obtained from the ratio between the maximum density gradient x of each sharp signal and the maximum density gradient y of the corresponding blur signal with a reference value that is a function of the density gradient of the sharp signal, Evaluate sharpness.
[0006]
[Problems to be solved by the invention]
However, each of the methods described in the above publications is a method for judging the sharpness of the original image by looking only at the maximum density gradient in the scanning region in the original image (or sharpened image) and the blurred image thereof. In some cases, the sharpness of the entire original image is determined without reflecting the information of the edge portion having the highest sharpness in the scanning region. As a result, there arises a problem that the sharpness cannot be properly determined for any original image.
[0007]
For example, FIG. 7 shows image data (solid lines (1) to (3)) of three types of edge portions (solid lines (1) to (3)) at different positions (pixel positions) in a region when a linear region is considered. (Density value) is schematically shown. In FIG. 7, three types of edges are overlapped for easy comparison.
[0008]
The density gradient p of the three types of edges shown in FIG. 7 can be expressed as follows using the change interval m of the image data and the change amount n of the image data. That is, the density gradient p of the edge of the solid line (1) ₁ Is n ₁ / M ₁ The density gradient p of the edge indicated by the solid line (2) ₂ Is n ₂ / M ₂ The density gradient p of the edge indicated by the solid line (3) _Three Is n ₁ / M _Three Indicated by Where n ₁ > N ₂ And m ₁ > M ₂ > M _Three And Further, as the image data, for example, values of 0 (black) to 255 (white) with 8 bits are considered.
[0009]
For example, when comparing the sharpness of the edge between the solid line {circle over (1)} and the solid line {circle over (3)}, the change amount of the image data is the same n ₁ Therefore, it can be said that the solid line (3) with a large density gradient has sharper edges than the solid line (1).
[0010]
However, when comparing the sharpness of the edge between the solid line (1) and the solid line (2), it is not always possible to determine the sharpness of the edge based only on the density gradient between the solid line (1) and the solid line (2). This is because when the amount of change in image data is different, it can be said that the edge is sharp if the change interval of the image data is short even if the density gradient is small. In the solid line (2), the density gradient is smaller than that in the solid line (1), but the image data changes by a predetermined amount in a section narrower than the solid line (1). Therefore, in practice, the solid line (2) looks sharper than the solid line (1). This means that the magnitude of the density gradient does not necessarily correspond to the magnitude of the edge sharpness, and the magnitude of the change section of the image data corresponds to the magnitude of the edge sharpness.
[0011]
As in the above publications, when a small number of pixels are extracted and the sharpness of the original image is determined from the data, it is necessary to pay attention to the pixel having the highest sharpness (small edge width) in the image. However, in each of the above publications, only the pixel that gives the maximum density gradient is selected in the same scanning region, and therefore the sharpness of the entire original image is determined without selecting the pixel group having the highest sharpness by the above-described principle. There may be cases. As a result, the sharpness of the original image cannot be properly determined.
[0012]
Further, in the method of Japanese Patent Application Laid-Open No. 61-7443, the evaluation values obtained from the ratio of the maximum concentration gradient x and the maximum concentration gradient y are obtained by grouping the maximum concentration gradient y according to the value of the maximum concentration gradient x. This is obtained by summing y / x in groups of However, in this method, it is practically difficult to determine a function of the maximum concentration gradient x and the maximum concentration gradient y that give a reference value. Further, if it is attempted to stably determine the sharpness for any original image, the original amount of information is insufficient, and complicated calculation is required.
[0013]
The present invention has been made to solve the above-described problems, and its purpose is to appropriately and easily and stably determine the sharpness of an original image for any original image. It is an object to provide an image sharpness determination method that can be performed, a recording medium on which a program for performing processing for determining image sharpness, an image processing apparatus, and a photographic printing apparatus are recorded.
[0014]
[Means for Solving the Problems]
In order to solve the above-mentioned problem, the image sharpness determination method according to the first aspect of the present invention calculates a first step of creating a smoothed image from an original image and a first edge strength of the original image. A second step of calculating a second edge strength of the smoothed image, a fourth step of determining the sharpness of the original image based on the first edge strength and the second edge strength. The fourth step further includes a step of creating a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency, and the ratios different from each other. And a step of determining the sharpness of the original image based on the magnitude relationship between the frequency ratio and the threshold value.
[0015]
As the original image, for example, an image corresponding to image data obtained by reading a photographic film such as a negative film or image data used in a PC or the like can be assumed. In the above configuration, the first edge strength of the original image is calculated, while the smoothed image of the original image is created and the second edge strength of the smoothed image is calculated. These first edge strength and second edge strength both correspond to the density gradient in the edge portion. The density gradient generally refers to the ratio between the amount of change in image data at the edge portion and the change interval of image data.
[0016]
Here, the first edge intensity is eo, the second edge intensity is eb, the amount of change in the image data in the original image is h, the change interval of the image data at that time is a, and the amount of change in the image data in the smoothed image is h. The change interval of the image data at that time is denoted by b.
[0017]
The sharpness of each edge included in the original image can be determined by looking at the width of the change interval of the image data at each edge. For example, the edge width ratio b / a between the smoothed image and the original image becomes larger as the edge in the original image becomes sharper, that is, as a becomes smaller. Therefore, considering such an edge width ratio b / a, the sharpness of each edge of the original image can be determined appropriately. As a result, it is possible to determine the sharpness of the image using information on the sharp edge among the plurality of edges included in the original image.
[0018]
On the other hand, since the first edge strength eo is h / a and the second edge strength eb is h / b, the ratio between the second edge strength and the first edge strength (hereinafter referred to as edge strength ratio f). Eb / eo = (h / b) / (h / a) = a / b. This means that 1 / f, which is the reciprocal of the edge strength ratio f, is equivalent to the edge width ratio described above. Therefore, the edge width ratio b / a described above can be considered by using the first edge strength eo and the second edge strength eb.
[0019]
Therefore, in the above configuration, the frequency distribution of the edge strength ratio f is created, and the frequency ratio corresponding to each of the different edge strength ratios f is considered, and the magnitude relationship between the frequency ratio and the threshold value is compared. . As a result, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f has a smaller value, that is, the pixels whose reciprocal 1 / f has a large value, to the entire image. If the ratio of pixels having a large value of the inverse 1 / f is large, the ratio of pixels having a large edge width ratio b / a is large, and as a result, the original image includes many sharp edges. It will be.
[0020]
Further, since the change amount h of the image data differs between edges even in the same image, it is necessary to remove the influence of the variation of h in the evaluation of the sharpness. The second edge strength eb is obtained at h / b, while the first edge strength eo is obtained at h / a, both of which contain h information. However, if the edge intensity ratio f is calculated, f = a / b, and h information can be excluded from the edge intensity ratio f.
[0021]
Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Thereby, if a frequency distribution of the edge strength ratio f is created, information on a truly sharp edge can be reliably reflected in the frequency distribution.
[0022]
Therefore, according to the above configuration, it is possible to determine the sharpness of the original image appropriately and stably based on the frequency distribution, regardless of what the original image is.
[0023]
In addition, creating the frequency distribution and comparing the magnitude relationship between the edge strength ratio and the threshold is a very simple process, and no complicated calculation is required. Therefore, it is possible to easily determine the sharpness. it can.
[0024]
In order to solve the above-described problem, the image sharpness determination method according to the invention of claim 2 is the configuration of claim 1, wherein the fourth step includes the first edge intensity at the target pixel of the original image and Correspondence between the first edge strength at the target pixel and the target pixel and the smoothed image when the first edge strength at the target pixel is the maximum among the first edge strengths at the surrounding pixels. And a step of obtaining a ratio between the second edge strength and the first edge strength using the second edge strength of the pixel to be processed.
[0025]
It can be said that pixels having a first edge intensity higher than that of surrounding pixels in the original image correspond to edge portions in the image. Therefore, the edge intensity ratio is obtained using the first edge intensity of such a pixel and the second edge intensity of the corresponding pixel on the pixel and the smoothed image, and is created using this edge intensity ratio. The determination of the sharpness of the original image performed based on the frequency distribution can be performed with certainty of the sharpness of the edge portion of the original image. As a result, the reliability of the sharpness determination result can be reliably improved.
[0026]
According to a third aspect of the present invention, in order to solve the above-mentioned problem, the image sharpness determination method according to the second aspect of the present invention is the above-described method for obtaining a ratio between the second edge strength and the first edge strength. The pixel used to determine the first edge strength is a target pixel in the original image, at least one of a pixel positioned in the vertical direction of the target pixel and a pixel positioned in the horizontal direction of the target pixel. It is characterized by being.
[0027]
Information of pixels located in an oblique direction when viewed from the target pixel is reflected in pixels positioned above, below, left, and right of the target pixel. Therefore, as the pixels used to determine the first edge strength for obtaining the edge strength ratio, the target pixel in the original image, the pixel positioned in the vertical direction of the target pixel, and the horizontal position of the target pixel Even if at least one of the pixels to be considered is considered, the sharpness of the entire original image can be determined in consideration of the sharpness of the edge portion of the original image. That is, the sharpness determination can be appropriately performed with a small number of pixels without considering the first edge intensity of all the pixels around the pixel of interest.
[0028]
Note that the pixel used to determine the first edge strength may be only the pixel of interest and the pixel positioned in the vertical direction of the pixel of interest, or only the pixel of interest and the pixel positioned in the horizontal direction thereof. Good. In particular, if the pixel of interest and the pixels positioned in the vertical direction and the horizontal direction are taken into consideration in the determination, the above-described effect can be reliably obtained.
[0029]
In order to solve the above-described problem, the image sharpness determination method according to the invention of claim 4 is the configuration according to any one of claims 1 to 3, wherein the frequencies are all the frequencies corresponding to each ratio. It is characterized by relative frequency with respect to all frequencies.
[0030]
For example, in the frequency distribution composed of the edge intensity ratio and the absolute value of the frequency, if the number of pixels constituting the original image changes, the distribution shape also changes. Therefore, the threshold value is set according to the number of pixels of the original image. Necessary. On the other hand, when a relative frequency distribution composed of the edge intensity ratio and its relative frequency is created, even if the number of pixels of the original image is different, it is possible to obtain almost the same distribution shape for images with the same sharpness. it can. Thereby, the setting of the threshold value according to the number of pixels of the original image can be made unnecessary, and the sharpness can be determined more easily.
[0031]
According to a fifth aspect of the present invention, there is provided a recording medium on which a program for performing a process for determining the sharpness of an image is recorded. In order to solve the above problem, a first smoothing image is created from an original image. Processing, second processing for calculating the first edge strength of the original image, third processing for calculating the second edge strength of the smoothed image, the first edge strength and the second edge strength, And recording a program for causing the computer to execute a fourth process for determining the sharpness of the original image, and the fourth process further includes the second edge strength and the first edge strength. A frequency distribution based on the ratio and the frequency, a process for obtaining a frequency ratio corresponding to the above-mentioned ratios different from each other, and an original image based on the magnitude relationship between the frequency ratio and the threshold The process of judging the sharpness It is characterized in that there.
[0032]
As the original image, for example, an image corresponding to image data obtained by reading a photographic film such as a negative film or image data used in a PC or the like can be assumed. When the program of the recording medium is executed by a computer, the first edge strength of the original image is calculated, while the smoothed image of the original image is created and the second edge strength of the smoothed image is calculated. Is done. These first edge strength and second edge strength both correspond to the density gradient in the edge portion. The density gradient generally refers to the ratio between the amount of change in image data at the edge portion and the change interval of image data.
[0033]
Here, the first edge intensity is eo, the second edge intensity is eb, the amount of change in the image data in the original image is h, the change interval of the image data at that time is a, and the amount of change in the image data in the smoothed image is h. The change interval of the image data at that time is denoted by b.
[0034]
The sharpness of each edge included in the original image can be determined by looking at the width of the change interval of the image data at each edge. For example, the edge width ratio b / a between the smoothed image and the original image becomes larger as the edge in the original image becomes sharper, that is, as a becomes smaller. Therefore, considering such an edge width ratio b / a, the sharpness of each edge of the original image can be determined appropriately. As a result, it is possible to determine the sharpness of the image using information on the sharp edge among the plurality of edges included in the original image.
[0035]
On the other hand, since the first edge strength eo is h / a and the second edge strength eb is h / b, the ratio between the second edge strength and the first edge strength (hereinafter referred to as edge strength ratio f). Eb / eo = (h / b) / (h / a) = a / b. This means that 1 / f, which is the reciprocal of the edge strength ratio f, is equivalent to the edge width ratio described above. Therefore, the edge width ratio b / a described above can be considered by using the first edge strength eo and the second edge strength eb.
[0036]
Therefore, in the above configuration, the frequency distribution of the edge strength ratio f is created, and the frequency ratio corresponding to each of the different edge strength ratios f is considered, and the magnitude relationship between the frequency ratio and the threshold value is compared. . As a result, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f has a smaller value, that is, the pixels whose reciprocal 1 / f has a large value, to the entire image. If the ratio of pixels having a large value of the inverse 1 / f is large, the ratio of pixels having a large edge width ratio b / a is large, and as a result, the original image includes many sharp edges. It will be.
[0037]
Further, since the change amount h of the image data differs between edges even in the same image, it is necessary to remove the influence of the variation of h in the evaluation of the sharpness. The second edge strength eb is obtained at h / b, while the first edge strength eo is obtained at h / a, both of which contain h information. However, if the edge intensity ratio f is calculated, f = a / b, and h information can be excluded from the edge intensity ratio f.
[0038]
Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Thereby, if a frequency distribution of the edge strength ratio f is created, information on a truly sharp edge can be reliably reflected in the frequency distribution.
[0039]
Therefore, by driving the computer using the recording medium of the present invention, it is possible to determine the original image sharpness appropriately and stably based on the frequency distribution, regardless of what the original image is. Can do.
[0040]
In addition, creating the frequency distribution and comparing the magnitude relationship between the edge strength ratio and the threshold is a very simple process, and no complicated calculation is required. Therefore, it is possible to easily determine the sharpness. it can.
[0041]
In order to solve the above problems, an image processing apparatus according to a sixth aspect of the present invention provides a smoothed image creating means for creating a smoothed image from an original image, and a first edge strength for calculating the first edge strength of the original image. The sharpness of the original image is determined based on one edge strength calculating means, second edge strength calculating means for calculating the second edge strength of the smoothed image, and the first edge strength and the second edge strength. Sharpness determination means, and the sharpness determination means creates a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency, and supports different ratios. The ratio of the frequencies to be obtained is obtained, and the sharpness of the original image is determined based on the magnitude relationship between the ratio of the frequencies and the threshold value.
[0042]
As the original image, for example, an image corresponding to image data obtained by reading a photographic film such as a negative film or image data used in a PC or the like can be assumed. The first edge strength calculating means calculates the first edge strength of the original image, while the second edge strength calculating means is the second edge strength of the smoothed image of the original image created by the smoothed image creating means. Is calculated. These first edge strength and second edge strength both correspond to the density gradient in the edge portion. The density gradient generally refers to the ratio between the amount of change in image data at the edge portion and the change interval of image data.
[0043]
Here, the first edge intensity is eo, the second edge intensity is eb, the amount of change in the image data in the original image is h, the change interval of the image data at that time is a, and the amount of change in the image data in the smoothed image is h. The change interval of the image data at that time is denoted by b.
[0044]
The sharpness of each edge included in the original image can be determined by looking at the width of the change interval of the image data at each edge. For example, the edge width ratio b / a between the smoothed image and the original image becomes larger as the edge in the original image becomes sharper, that is, as a becomes smaller. Therefore, considering such an edge width ratio b / a, the sharpness of each edge of the original image can be determined appropriately. As a result, it is possible to determine the sharpness of the image using information on the sharp edge among the plurality of edges included in the original image.
[0045]
On the other hand, since the first edge strength eo is h / a and the second edge strength eb is h / b, the ratio between the second edge strength and the first edge strength (hereinafter referred to as edge strength ratio f). Eb / eo = (h / b) / (h / a) = a / b. This means that 1 / f, which is the reciprocal of the edge strength ratio f, is equivalent to the edge width ratio described above. Therefore, the edge width ratio b / a described above can be considered by using the first edge strength eo and the second edge strength eb.
[0046]
Therefore, in the above configuration, the sharpness determination means creates a frequency distribution of the edge strength ratio f, considers the frequency ratio corresponding to each of the different edge strength ratios f, and determines the magnitude of the frequency ratio and the threshold value. Comparing relationships. As a result, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f is smaller, that is, the pixels whose reciprocal 1 / f is large, to the entire image. If the ratio of pixels having a large value of the inverse 1 / f is large, the ratio of pixels having a large edge width ratio b / a is large, and as a result, the original image includes many sharp edges. It will be.
[0047]
Further, since the change amount h of the image data differs between edges even in the same image, it is necessary to remove the influence of the variation of h in the evaluation of the sharpness. The second edge strength eb is obtained at h / b, while the first edge strength eo is obtained at h / a, both of which contain h information. However, if the edge intensity ratio f is calculated, f = a / b, and h information can be excluded from the edge intensity ratio f.
[0048]
Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Thereby, if a frequency distribution of the edge strength ratio f is created, information on a truly sharp edge can be reliably reflected in the frequency distribution.
[0049]
Therefore, according to the above configuration, it is possible to appropriately and stably determine the sharpness of the original image based on the frequency distribution, regardless of what the original image is.
[0050]
In addition, creating the frequency distribution and comparing the magnitude relationship between the edge strength ratio and the threshold is a very simple process, and no complicated calculation is required. Therefore, it is possible to easily determine the sharpness. it can.
[0051]
According to a seventh aspect of the present invention, in order to solve the above-described problem, in the configuration of the sixth aspect, the sharpness determining means includes the first edge intensity at the target pixel of the original image and its surroundings. Among the first edge intensities in the pixel, the first edge intensity in the target pixel and the corresponding pixel on the target pixel and the smoothed image when the first edge intensity in the target pixel is maximum. A ratio between the second edge strength and the first edge strength is obtained using the second edge strength.
[0052]
It can be said that pixels having a first edge intensity higher than that of surrounding pixels in the original image correspond to edge portions in the image. Therefore, the edge intensity ratio is obtained using the first edge intensity of such a pixel and the second edge intensity of the corresponding pixel on the pixel and the smoothed image, and is created using this edge intensity ratio. The determination of the sharpness of the original image performed based on the frequency distribution can be performed with certainty of the sharpness of the edge portion of the original image. As a result, the reliability of the sharpness determination result can be reliably improved.
[0053]
In order to solve the above problems, an image processing apparatus according to an eighth aspect of the present invention provides the first edge for obtaining a ratio between the second edge strength and the first edge strength in the configuration of the seventh aspect. The pixels used to determine the intensity are at least one of a target pixel in the original image, a pixel positioned in the vertical direction of the target pixel, and a pixel positioned in the horizontal direction of the target pixel. It is characterized by.
[0054]
Information of pixels located in an oblique direction when viewed from the target pixel is reflected in pixels positioned above, below, left, and right of the target pixel. Therefore, as the pixels used to determine the first edge strength for obtaining the edge strength ratio, the target pixel in the original image, the pixel positioned in the vertical direction of the target pixel, and the horizontal position of the target pixel Even if at least one of the pixels to be considered is considered, the sharpness of the entire original image can be determined in consideration of the sharpness of the edge portion of the original image. That is, the sharpness determination can be appropriately performed with a small number of pixels without considering the first edge intensity of all the pixels around the pixel of interest.
[0055]
Note that the pixel used to determine the first edge strength may be only the pixel of interest and the pixel positioned in the vertical direction of the pixel of interest, or only the pixel of interest and the pixel positioned in the horizontal direction thereof. Good. In particular, if the pixel of interest and the pixels positioned in the vertical direction and the horizontal direction are taken into consideration in the determination, the above-described effect can be reliably obtained.
[0056]
In order to solve the above-described problem, an image processing apparatus according to a ninth aspect of the present invention is the configuration according to any one of the sixth to eighth aspects, wherein the frequency is the second edge strength and the first edge strength. It is characterized by a relative frequency with respect to the total frequency obtained by adding all frequencies corresponding to each ratio.
[0057]
For example, in the frequency distribution composed of the edge intensity ratio and the absolute value of the frequency, if the number of pixels constituting the original image changes, the distribution shape also changes. Therefore, the threshold value is set according to the number of pixels of the original image. Necessary. On the other hand, when a relative frequency distribution composed of the edge intensity ratio and its relative frequency is created, even if the number of pixels of the original image is different, it is possible to obtain almost the same distribution shape for images with the same sharpness. it can. Thereby, the setting of the threshold value according to the number of pixels of the original image can be made unnecessary, and the sharpness can be determined more easily.
[0058]
In order to solve the above-described problem, an image processing apparatus according to a tenth aspect of the present invention is the configuration according to any one of the sixth to ninth aspects, wherein an original image is processed according to a determination result by the sharpness determination means. A sharpening processing means for performing the sharpening processing is further provided.
[0059]
According to the above configuration, when the sharpening determination unit determines that the original image is, for example, a blurred image, the sharpening processing unit performs sharpening processing on the original image. On the other hand, when the sharpening determination means determines that the original image is originally an image with high sharpness, the sharpening processing by the sharpening processing means is not performed. Therefore, a high-quality image can be finally obtained regardless of whether the original image is a blurred image. For example, if the image is burned as a photograph, a high-quality photographic print is obtained, and if the image is displayed on a monitor, the display image has a high image quality.
[0060]
In order to solve the above-described problems, a photographic printing apparatus according to an eleventh aspect of the present invention is the image processing apparatus according to any one of the sixth to tenth aspects, and an image sharpened by the image processing apparatus. And an exposure unit that exposes the photosensitive material based on the image data or the image data of the original image.
[0061]
As the exposure means, for example, irradiation / non-irradiation of light to the photosensitive material can be controlled for each pixel based on image data sent from the image processing apparatus according to any one of claims 6 to 10. A configuration including a light modulation element such as a PLZT exposure head, DMD, or LCD can be considered. The exposure means exposes the photosensitive material based on the image data of the image sharpened by the image processing apparatus or the image data of the original image, whereby a high-quality photographic print can be obtained.
[0062]
DETAILED DESCRIPTION OF THE INVENTION
An embodiment of the present invention will be described below with reference to FIGS.
[0063]
The photographic printing apparatus according to the present embodiment prints an image on a photographic paper by exposing the photographic paper, which is a photosensitive material, based on image data of each color of BGR, for example. As shown in FIG. A capture unit 1, an image processing unit 2 (image processing apparatus), and an exposure unit 3 (exposure means) are provided.
[0064]
The image capturing unit 1 is a scanner that captures an image (hereinafter also referred to as an original image) recorded on a negative film by measuring light transmitted through the negative film. For example, a light source that irradiates light on the negative film And a rotary filter provided with each color filter of BGR and a CCD (Charge Coupled Device) camera (hereinafter simply referred to as a CCD). The rotary filter is rotated so that the light of each color of BGR sequentially reaches the CCD, and the light transmitted through the negative film is received by the CCD for each BGR, so that the CCD generates an electrical signal corresponding to the amount of light received for each BGR. The image is sent to the image processing unit 2. Thereby, image data (pixel value) corresponding to the density of each pixel of the original image is obtained for each BGR. In the case where the CCD is constituted by a three-plate type, the above rotation filter is not necessary.
[0065]
The image processing unit 2 determines the sharpness of the original image based on the image data for each BGR sent from the image capturing unit 1, and performs the sharpening process as necessary based on the determination result. The details will be described later. The image processing unit 2 may be configured by a microprocessor and / or DSP (Digital Signal Processor) incorporated in the photographic printing apparatus, or may be configured by a PC (Personal Computer) provided outside the apparatus. Good. The image processing unit 2 also includes a memory that temporarily stores image data from the image capturing unit 1 and a control unit (both not shown) that controls the exposure operation in the exposure unit 3.
[0066]
The exposure unit 3 controls the irradiation / non-irradiation of light to the photographic paper for each pixel based on the BGR image data sent from the image processing unit 2, and prints the image on the photographic paper. As means for controlling the light irradiation, for example, a PLZT exposure head, DMD (digital micromirror device), LCD (liquid crystal display device), LED panel, laser, FOCRT (Fiber Optic Cathode Ray Tube), CRT, etc. can be considered. . Needless to say, when a non-self-emitting control means such as a PLZT exposure head, DMD, or LCD is used, a light source is required separately. Further, if necessary, a condenser lens such as a BGR rotary filter or a printing lens is also arranged.
[0067]
That is, in the photographic printing apparatus having the above configuration, when the image capturing unit 1 captures an original image recorded on a negative film and sends each image data of BGR to the image processing unit 2, the image processing unit 2 The sharpness of the original image is determined based on the data. When the image processing unit 2 determines that the original image is sharp, it sends the image data of the original image to the exposure unit 3 as it is. On the other hand, when the image processing unit 2 determines that the original image is a blurred image, A sharpening process is performed using the image data, and the processed image data is sent to the exposure unit 3. In the exposure unit 3, each pixel of the control unit is controlled based on the image data of the original image or the sharpened image data, and the printing paper is irradiated with light obtained through each of the pixels, thereby printing the image. A color image is printed on the paper.
[0068]
Next, the image processing unit 2 that is a feature of the present invention will be described.
[0069]
The image processing unit 2 includes a BGR / luminance conversion unit 4, a smoothed image creation unit 5 (smoothed image creation unit), a first edge strength calculation unit 6 (first edge strength calculation unit), and a second edge strength calculation unit 7. (Second edge strength calculation means), a sharpness determination section 8 (sharpness determination means) and a sharpening processing section 9 (sharpening processing means).
[0070]
The BGR / luminance conversion unit 4 converts each pixel value of BGR obtained by the image capturing unit 1 into luminance image data Y. The luminance image data Y is calculated by the following equation, for example. In the following description, unless otherwise specified, the pixel value is the luminance image data Y.
[0071]
Y = (R + G + B) / 3
The smoothed image creating unit 5 creates a smoothed image (blurred image) of the original image using, for example, the weight w (x, y) of the digital filter shown in FIG. Specifically, the digital filter is x _min ≦ x ≦ x _max , Y _min ≦ y ≦ y _max The smoothed image creation unit 5 calculates the pixel of the smoothed image from the pixel value o (i, j) of the original image obtained by the BGR / luminance conversion unit 4 according to Equation (1). Calculate the value b (i, j).
[0072]
[Expression 1]

[0073]
Note that the coefficients of the filter shown in FIG. 3 are merely examples, and the present invention is not limited to these coefficients. 3 is a Gaussian filter, it is not limited to this filter, but may be a moving average filter or a median filter.
[0074]
The first edge strength calculation unit 6 applies, for example, a Laplacian filter shown in FIG. 4 to the pixel value o (i, j) of the original image obtained by the BGR / luminance conversion unit 4 to thereby apply the edge strength eo ( i, j) is calculated as the first edge strength. Note that the coefficient of the Laplacian filter shown in FIG. 4 is an example, and is not limited to this coefficient. On the other hand, the second edge strength calculation unit 7 applies, for example, a Laplacian filter shown in FIG. 4 to the pixel value b (i, j) of the smoothed image obtained by the smoothed image creation unit 5 to thereby generate the smoothed image. The edge strength eb (i, j) is calculated as the second edge strength.
[0075]
Note that the edge intensities eo (i, j) and eb (i, j) described above are graphs of changes in image data (density values) at respective positions (pixel positions) in a linear region in the image. This corresponds to the concentration gradient shown.
[0076]
The sharpness determination unit 8 determines the sharpness of the original image based on the edge strength eo (i, j) of the original image and the edge strength eb (i, j) of the smoothed image. Will be described later.
[0077]
When the sharpness determination unit 8 determines that the sharpness of the original image is low, the sharpening processing unit 9 performs a sharpening process, for example, by applying a Laplacian filter to the BGR image data of the original image. Is. The Laplacian image of the original image F (i, j) ² Assuming that F (i, j), the image G (i, j) of the sharpened image is obtained by the following equation for each BGR, and the image data is sent to the exposure unit 3 for each BGR.
[0078]
G (i, j) = F (i, j)-▽ ² F (i, j)
On the other hand, when the sharpness determination unit 8 determines that the sharpness of the original image is high, the sharpening processing unit 9 does not perform the above-described sharpening process on the original image and performs BGR of the original image. Are sent to the exposure unit 3 as they are.
[0079]
Next, details of the sharpness determination unit 8 will be described.
[0080]
The sharpness determination unit 8 determines the sharpness of the original image by the following method based on the edge strength eo (i, j) of the original image and the edge strength eb (i, j) of the smoothed image. .
[0081]
First, the sharpness determination unit 8 performs edge intensity eo (i, j) at a predetermined pixel (i, j), which will be described later, of the original image and a pixel (i, j) corresponding to the predetermined pixel on the smoothed image. From the edge strength eb (i, j), the relative frequency distribution of the edge strength ratio | eb (i, j) / eo (i, j) | (= f) is obtained. An example of the relative frequency distribution thus obtained is shown in FIGS. 5 (a) and 5 (b). FIG. 5A shows a relative frequency distribution obtained when the original image is originally an image with high sharpness, and FIG. 5B shows a relative frequency obtained when the original image is a blurred image with low sharpness. The frequency distribution is shown. The vertical axis in these drawings indicates the relative value with respect to all frequencies, that is, the relative frequency (when the frequencies corresponding to the values of the edge intensity ratios f are all added, the value is 1).
[0082]
Here, the predetermined pixels of the original image are the edge intensity eo (i, j) at the target pixel (i, j) of the original image and the edge intensity eo (i + 1, j) at the upper, lower, left, and right pixels of the pixel. ), Eo (i−1, j), eo (i, j−1), and eo (i, j + 1) are extracted and the absolute values thereof are obtained, the absolute value of the edge strength eo (i, j) The pixel when the value is the maximum. Since the edge intensity of the predetermined pixel is higher than the edge intensity of surrounding pixels, the predetermined pixel corresponds to a portion having the highest edge intensity among certain edges in the image. That is, by considering such a predetermined pixel, it is possible to reliably recognize the edge portion in the image.
[0083]
The pixel used to determine whether or not the predetermined pixel is an edge portion in the image, that is, the pixel used to determine the edge intensity eo (i, j) for obtaining the edge intensity ratio f is the pixel of interest It is not necessarily limited to the above five pixels including For example, the pixel of interest and three pixels above and below it, or three pixels of the pixel of interest and its left and right pixels, four or more pixels aligned in the vertical direction with the pixel of interest, and the pixel of interest and its horizontal direction There may be four or more pixels arranged in a row.
[0084]
That is, the pixels used for determining the edge strength eo (i, j) are the target pixel in the original image, the pixel positioned in the vertical direction of the target pixel, and the pixel positioned in the horizontal direction of the target pixel. It may be at least one pixel. When the edge intensity eo (i, j) is determined using five pixels including the pixel of interest and the pixels adjacent to the top, bottom, left, and right, the edge information of the pixel of interest can be reliably reflected in the relative frequency distribution. Therefore, it is possible to more appropriately determine the sharpness described later. In addition, when the target pixel and its upper and lower pixels, or the target pixel and its left and right pixels are used for the determination of the edge strength eo (i, j), the edge information of the target pixel is displayed in the relative frequency distribution even with a small number of pixels. It can be reflected.
[0085]
In addition, the information on the pixels located obliquely as viewed from the target pixel is reflected on the pixels positioned on the top, bottom, left, and right of the target pixel. Although it is not necessary to use these, these 9 pixels may be used separately.
[0086]
By the way, since the edge strength eo (i, j) in the edge portion is higher as the sharpness is higher, the value of the edge strength ratio f in the pixel in the edge portion is smaller. Therefore, the greater the relative frequency corresponding to the edge intensity ratio f having a smaller value, the more such points exist in the image. In this case, it can be said that the entire original image is sharp. However, it has been experimentally found that the sharpness of an image cannot be determined appropriately even if the relative frequency of the edge intensity ratio f is too small.
[0087]
Therefore, when the sharpness determination unit 8 obtains the relative frequency distribution as described above, the relative frequency H when the edge intensity ratio f is a high value (for example, f = 0.3) and the edge intensity ratio f are low. Recognizing the relative frequency L in the case of a value (for example, f = 0.2), the ratio H / L of these relative frequencies is obtained, and the magnitude relationship between the ratio H / L and the threshold value is compared. ing. If the threshold is set to 1, for example, the magnitude relationship between the relative frequency H and the relative frequency L is simply compared.
[0088]
When the threshold value is 1 and the ratio H / L is smaller than the threshold value, the relative frequency H is smaller than the relative frequency L. In this case, since the relative frequency corresponding to the smaller edge intensity ratio f is larger than the other relative frequency, it can be said that the entire image is sharp in this case. On the other hand, when the threshold is 1 and the ratio H / L is equal to or greater than the threshold, it can be said that the entire image is blurred based on the principle opposite to the above.
[0089]
Note that the above threshold is only a parameter for adjusting the severity of sharpness determination, and even if the threshold is set to a value other than 1, the relative frequency corresponding to the smaller edge strength ratio f and the other relative frequency are set. There is no change that the sharpness of the entire image can be determined by relative comparison with.
[0090]
Therefore, the sharpness determination unit 8 determines that the original image is a blurred image if the ratio H / L is equal to or greater than the threshold, while the original image has a high sharpness if the ratio H / L is smaller than the threshold. Judged to be an image. As described above, in this embodiment, the sharpness of the image is determined based on the magnitude relationship between the ratio H / L and the threshold value. Therefore, the above ratio H / L is determined based on the original image whose sharpness is to be determined. It can be said that the edge sharpness is shown.
[0091]
In addition, the relative frequency in the case of f = 0.2 or 0.3 is adopted as H or L, even if the relative frequency of f = 0.1 or 0.4 to 1.0 is considered. This is because a result in which the sharpness cannot be properly determined for every image has been experimentally obtained in advance. That is, the relative frequencies of f = 0.1 and 0.4 to 1.0 are values that are not reliable in judging the sharpness, and thus these values are not adopted in this embodiment.
[0092]
Note that the edge intensity ratio f taking the relative frequency H is not limited to the above 0.3, and when the relative frequency distribution is created, for example, the frequency is obtained within a range of f = 0.25 to 0.35. It has been empirically found that the largest possible value is sufficient. Similarly, the edge intensity ratio f taking the relative frequency L is not limited to the above 0.2, and when the relative frequency distribution is created, for example, within the range of f = 0.15 to 0.25. It has been experimentally found that the smallest value that can be obtained is sufficient.
[0093]
That is, the values of the edge intensity ratios f corresponding to the relative frequencies H and L may be values that are effective for determining the sharpness of any image. As a result, the sharpness determination result does not vary depending on the original image.
[0094]
Next, the operation of the image processing unit 2 will be described mainly based on the flowchart of FIG.
[0095]
First, when each image data of BGR is sent from the image capturing unit 1 to the image processing unit 2, the BGR / luminance conversion unit 4 of the image processing unit 2 performs luminance image data for each pixel from each image data of the BGR. Y (pixel value o (i, j)) is generated, and the pixel value o (i, j) is sent to the smoothed image creating unit 5 and the first edge intensity calculating unit 6 (step 1; hereinafter, the steps are simply Abbreviated as S). Then, the smoothed image creation unit 5 multiplies each pixel value o (i, j) by the coefficient of the digital filter of FIG. 3 to create a smoothed image of the original image, that is, the pixel value b ( i, j) is calculated (S2; first step).
[0096]
Next, the first edge strength calculator 6 multiplies each pixel value o (i, j) by the filter coefficient of FIG. 4 to calculate the edge strength eo (i, j) of each pixel of the original image (S3). A third step). On the other hand, the second edge strength calculation unit 7 multiplies the pixel value b (i, j) of the smoothed image obtained by the smoothed image creation unit 5 by the coefficient of the filter in FIG. Edge strength eb (i, j) is calculated (S4; third step).
[0097]
Next, the sharpness determination unit 8 determines from the edge intensity eo (i, j) of the predetermined pixel of the original image and the edge intensity eb (i, j) of the pixel corresponding to the predetermined pixel on the smoothed image. The relative frequency distribution of the edge intensity ratio | eb (i, j) / eo (i, j) | (= f) is obtained (S5). The selection of the edge intensity eo (i, j) of the predetermined pixel is as described above. In other words, whether or not to take the ratio of edge strength between the original image and the smoothed image is determined by comparing the edge strength of the target pixel of the original image with the edge strength of surrounding pixels.
[0098]
Then, the sharpness determination unit 8 obtains the ratio H / L from the relative frequency H when, for example, f = 0.3 and the relative frequency L when f = 0.2, and this ratio H / L Is greater than or equal to a threshold (for example, 1) (S7). If the sharpness determination unit 8 determines in S7 that the ratio H / L is equal to or greater than the threshold value, the sharpness determination unit 8 determines that the original image is a blurred image, while the ratio H / L is smaller than the threshold value. The original image is determined to be an image with high sharpness. In addition, the process of S5-S7 respond | corresponds to the 4th process as described in a claim.
[0099]
The sharpening processing unit 9 performs a sharpening process on the original image determined as a blurred image in S7 by applying a Laplacian filter to each BGR image data of the original image (S8). Each image data of the completed BGR is sent to the exposure unit 3. On the other hand, the sharpening processing unit 9 does not perform the above-described sharpening process on the original image determined to be an image with a high sharpness in S7 (S9), and the BGR image data of the original image is used as it is. It is sent to the exposure unit 3. In the exposure unit 3, the above-described photographic paper is exposed based on each BGR image data of the sharpened image or each BGR image data of the original image.
[0100]
Next, the reason why the effects of the present invention can be obtained by creating the relative frequency distribution shown in FIG. 5A or 5B and comparing the relative frequency ratio H / L with the threshold value. Will be described.
[0101]
A sharp edge is considered to be an edge having a small width of a change section of image data. Accordingly, if the sharpness of the original image can be determined by extracting a small edge in the change interval of the image data, the determination is appropriate. That is, in determining the sharpness, the point is how to recognize the size of the change interval of the image data.
[0102]
FIG. 6 shows a change in image data at an edge portion in the image between the original image and its blurred image. In the figure, a straight line A indicates a change in image data in the original image, and a straight line B indicates a change in image data in the blurred image. As shown in the figure, if the edge width in the original image is w and the radius of the digital filter used for smoothing is r (constant), the edge width in the blurred image is about w + 2r. This is because edge information spreads by r at both ends of the edge.
[0103]
By the way, although the edge width is increased by smoothing the original image, the sharper edge in the original image has a smaller edge width. For example, the ratio of the edge width between the blurred image and the original image, that is, (the edge width of the blurred image) ) / (Edge width of original image) increases as the original image becomes sharper. That is, (edge width of blurred image) / (edge width of original image) = (w + 2r) / w = 1 + 2r / w, so if the edge is sharp (if w is small), the edge width ratio is large. Become. Therefore, considering such an edge width ratio, the sharpness of each edge of the original image can be appropriately determined. As a result, it is possible to determine the sharpness of the image using information on the sharp edge among the plurality of edges included in the original image.
[0104]
However, since the value of each edge width cannot be easily obtained from each image, the edge width ratio cannot be obtained from the value of each edge width. Therefore, in the present invention, the edge width ratio is considered as follows using the edge strength that can be easily obtained by applying a digital filter.
[0105]
If the change amount of the image data in both the images is h, the edge strength eo of the original image is h / w, and the edge strength eb of the blurred image is h / (w + 2r), so the edge strength ratio f is eb / Eo = {h / (w + 2r)} / (h / w) = w / (w + 2r). At this time, 1 / f which is the reciprocal of the edge intensity ratio f is (w + 2r) / w = 1 + 2r / w. That is, the above edge width ratio is equivalent to the reciprocal of the edge strength ratio f. Therefore, the edge width ratio can be considered by using the edge strength obtained from the original image and the blurred image.
[0106]
However, the sharpness of the entire original image cannot be determined based on only one value of the edge intensity ratio f or only on the basis of one magnitude relationship between the edge intensity ratio f and the threshold value. This is because the edge intensity ratio f merely indicates the relationship obtained between one pixel of the original image and one pixel of the blurred image. That is, each of the edge intensity ratios f is a value that varies depending on the pixel, and it is dangerous to determine the sharpness of the entire image with any one of the edge intensity ratios f.
[0107]
Therefore, in the present embodiment, the relative frequency distribution of the edge strength ratio f is created, and the relative frequency ratio corresponding to each of the different edge strength ratios f is considered, and the magnitude relationship between the relative frequency ratio and the threshold value is determined. Comparing. By this method, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f has a smaller value, that is, the pixels whose reciprocal 1 / f has a large value, to the entire image. If the ratio of pixels with a large reciprocal 1 / f is large, the ratio of pixels having a large edge width ratio is large, and as a result, the original image includes many sharp edges. .
[0108]
Further, since the change amount h of the image data varies between edges even in the same image, it is necessary to remove the influence of the variation of h in the evaluation of the sharpness, that is, to normalize the h. Here, the edge intensity eb of the blurred image is obtained by h / (w + 2r) as described above, and includes information on h. Further, the edge strength eo of the original image is obtained by h / w, and also includes h information. However, by calculating the edge strength ratio f obtained from the edge strength eb of the blurred image and the edge strength eo of the original image, information on h can be excluded from the edge strength ratio f. That is, the concept of normalization can be included in the edge intensity ratio f.
[0109]
Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Accordingly, if a relative frequency distribution of the edge intensity ratio f is created, information on a truly sharp edge can be reliably reflected in the relative frequency distribution.
[0110]
Therefore, according to the present invention, it is possible to appropriately and stably determine the sharpness of the original image based on the relative frequency distribution, regardless of what the original image is.
[0111]
In addition, creating a relative frequency distribution and comparing the magnitude relationship between the relative frequency ratio and the threshold is a very simple process and does not require complicated calculations. Become. Further, in the present invention, the amount of calculation necessary for stabilizing the sharpness determination result is also reduced, so that the sharpness determination can be performed more quickly than before.
[0112]
By the way, a simple frequency distribution of edge intensity ratio f (absolute frequency distribution taking the value of edge intensity ratio f) is created, and the ratio of frequency (absolute number) corresponding to different values of edge intensity ratio f and a threshold value. It is also possible to determine the sharpness of the original image by comparing the magnitude relationship with. However, in the simple frequency distribution of the edge intensity ratio f, if the number of pixels constituting the original image changes, the distribution shape also changes. Therefore, it is necessary to set a threshold according to the number of pixels of the original image. On the other hand, when the relative frequency distribution of the edge intensity ratio f is created, even if the number of pixels of the original image is different, almost the same distribution shape can be obtained for images with the same sharpness. It is not necessary to set a threshold according to the number of pixels. Therefore, it is easier to determine the sharpness by creating a relative frequency distribution of the edge intensity ratio f.
[0113]
Note that the interval between the values of the edge intensity ratio f on the horizontal axis of the relative frequency distribution, the interval of the edge intensity ratio f corresponding to the relative frequencies H and L, threshold values, and the like are empirical constants set based on experiments and experience. However, it is easy to change these as appropriate.
[0114]
In addition, when the background portion of the main subject is blurred in the original image, the main subject can be obtained by the method of the present invention by creating a relative frequency distribution corresponding to the main subject portion excluding such a background portion. It is possible to appropriately determine the sharpness of the portion.
[0115]
The processing described above is realized by a program for causing the image sharpness determination processing to function. This program is stored in a computer-readable recording medium. In the present invention, the recording medium may be a memory (not shown) (for example, a ROM itself) necessary for processing by the image processing unit 2 of FIG. 2, or an external storage (not shown). A program reading device may be provided as a device, and a program medium that can be read by inserting a recording medium therein may be used.
[0116]
In any of the above cases, the stored program may be executed by accessing a microprocessor (not shown), or the stored program is read out and the read program is read out by the image processing unit 2. The program may be executed by downloading to a program storage area (not shown). In this case, it is assumed that the download program is stored in the main device in advance.
[0117]
Here, the program medium is a recording medium configured to be separable from the main body, such as a tape system such as a magnetic tape or a cassette tape, a magnetic disk such as a floppy disk or a hard disk, a CD-ROM / MO / MD / DVD, or the like. A medium carrying a fixed program including a disk system of an optical disk, a card system such as an IC card (including a memory card) / optical card, or a semiconductor memory such as a mask ROM, EPROM, EEPROM, flash ROM, etc. Also good.
[0118]
In the present invention, since the system configuration is connectable to a communication network including the Internet, it may be a medium that carries the program in a fluid manner so as to download the program from the communication network. When the program is downloaded from the communication network in this way, the download program may be stored in the main device in advance, or may be installed from another recording medium.
[0119]
The content stored in the recording medium is not limited to a program, and may be data.
[0120]
The case where the sharpness determination in the sharpness determination unit 8 is performed using the luminance image data Y has been described above. However, the BGR image data from the image capturing unit 1 is used to determine the sharpness of each BGR. You may make it judge. In this case, since the BGR / luminance conversion unit 4 is not necessary, the configuration of the image processing unit 2 can be further simplified. However, if the determination of the sharpness is performed separately for each BGR, there is a risk that a different sharpness may be determined for each of the BGRs. In view of this, the luminance image data Y is converted as in the present embodiment. It is better to use it to determine the sharpness.
[0121]
In the above description, the sharpening processing unit 9 uses the BGR image data from the image capturing unit 1 to perform the sharpening process for each of the BGRs. The sharpening process may be performed using the luminance image data Y. In this case, it is necessary to provide a luminance / BGR conversion unit that converts the luminance image data y of the sharpened image into BGR image data and supplies the image data to the exposure unit 3.
[0122]
At this time, each image data of BGR is obtained in the luminance / BGR conversion unit as follows, for example.
[0123]
B = b + Y−y
G = g + Y-y
R = r + Y-y
However, the above b, g, and r are B, G, and R image data before being converted by the BGR / luminance conversion unit 4, and Y is converted by the BGR / luminance conversion unit 4. This is luminance image data after, and y is luminance image data before being converted by the luminance / BGR converter.
[0124]
In the above description, the method for reading the image recorded on the negative film and determining the sharpness thereof has been described. However, when the image recorded on other photographic film such as a positive film is read and the sharpness is determined. Also, the present invention can be applied.
[0125]
Further, the example in which the sharpness determination method of the present invention is applied to a photographic printing apparatus has been described above. However, for example, when determining the sharpness of an image (digital image) captured by a digital camera or displayed on a PC monitor The present invention can also be applied to the determination of the sharpness of a captured image.
[0126]
The method of the present invention can also be used when examining the sharpness of an original image before performing smoothing processing on the image data of the original image in order to create a blurred image such as soft focus. it can.
[0127]
【The invention's effect】
As described above, the image sharpness determination method according to the first aspect of the present invention includes the first step of creating the smoothed image from the original image, and the second step of calculating the first edge strength of the original image. A step, a third step of calculating the second edge strength of the smoothed image, and a fourth step of determining the sharpness of the original image based on the first edge strength and the second edge strength. And the fourth step further includes the step of creating a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency, and the frequencies corresponding to the different ratios. And a step of determining the sharpness of the original image based on the magnitude relationship between the frequency ratio and the threshold value.
[0128]
Therefore, the frequency distribution of the edge strength ratio f is created, and the magnitude relationship between the frequency ratio corresponding to the different edge strength ratios f and the threshold is compared. As a result, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f has a smaller value, that is, the pixels whose reciprocal 1 / f has a large value, to the entire image. If the ratio of the pixels having a large value of the reciprocal 1 / f is large, the ratio of pixels having a large edge width ratio b / a between the smoothed image and the original image is large. Will contain many sharp edges.
[0129]
Further, if the edge intensity ratio f is calculated, f = a / b, and the information of h that is the image data change amount can be excluded from the edge intensity ratio f. Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Thereby, if a frequency distribution of the edge strength ratio f is created, information on a truly sharp edge can be reliably reflected in the frequency distribution.
[0130]
Therefore, according to the above configuration, there is an effect that the sharpness of the original image can be determined appropriately and stably based on the frequency distribution regardless of the original image.
[0131]
In addition, creating the frequency distribution and comparing the magnitude relationship between the edge strength ratio and the threshold is a very simple process, and no complicated calculation is required. Therefore, it is possible to easily determine the sharpness. It also has the effect of being able to.
[0132]
As described above, in the image sharpness determination method according to the invention of claim 2, in the configuration of claim 1, the fourth step includes the first edge intensity and the surrounding pixels in the target pixel of the original image. Among the first edge intensities in the first pixel, the first edge strength in the target pixel and the first of the corresponding pixels on the smoothed image when the first edge strength in the target pixel is maximum. The method further includes a step of obtaining a ratio between the second edge strength and the first edge strength using two edge strengths.
[0133]
Therefore, it can be said that a pixel having a first edge intensity higher than that of surrounding pixels in the original image corresponds to an edge portion in the image. Therefore, by obtaining the edge intensity ratio using the first edge intensity and the second edge intensity of such a pixel, the sharpness of the original image performed based on the frequency distribution created using this edge intensity ratio is calculated. The determination can be made with certainty of the sharpness of the edge portion of the original image. As a result, in addition to the effect of the configuration of claim 1, the reliability of the sharpness determination result can be improved reliably.
[0134]
As described above, the image sharpness determination method according to the invention of claim 3 is the first edge strength for obtaining a ratio between the second edge strength and the first edge strength in the configuration of claim 2. The pixel used for determining the pixel is a pixel of interest in the original image, and at least one of a pixel located in the vertical direction of the pixel of interest and a pixel located in the horizontal direction of the pixel of interest. is there.
[0135]
Therefore, the information on the pixels located in the oblique direction when viewed from the target pixel is reflected in the pixels positioned above, below, left, and right of the target pixel. Therefore, as the pixels used to determine the first edge strength for obtaining the edge strength ratio, the target pixel in the original image, the pixel positioned in the vertical direction of the target pixel, and the horizontal position of the target pixel Even if at least one of the pixels to be considered is considered, the sharpness of the entire original image can be determined in consideration of the sharpness of the edge portion of the original image. In other words, in addition to the effect of the configuration according to claim 2, the sharpness determination can be appropriately performed with a small number of pixels without considering the first edge strength of all the pixels around the target pixel. Play.
[0136]
In particular, if the pixel of interest and the pixels positioned in the vertical and horizontal directions are taken into consideration in the determination, the above-described effect can be obtained with certainty.
[0137]
As described above, in the image sharpness determination method according to the invention of claim 4, in the configuration according to any one of claims 1 to 3, the frequency corresponds to the total frequency obtained by adding all frequencies corresponding to each ratio. It is the structure which is a relative frequency.
[0138]
Therefore, when a relative frequency distribution composed of the edge intensity ratio and its relative frequency is created, even if the number of pixels of the original image is different, substantially the same distribution shape can be obtained for images with the same sharpness. This makes it unnecessary to set a threshold according to the number of pixels of the original image, and in addition to the effect of any one of the first to third aspects, the sharpness can be more easily determined. There is an effect.
[0139]
According to the invention of claim 5, the recording medium on which the program for determining the sharpness of the image is recorded, as described above, the first process for creating the smoothed image from the original image, and the above Based on the second processing for calculating the first edge strength of the original image, the third processing for calculating the second edge strength of the smoothed image, and the first edge strength and the second edge strength. A program for causing a computer to execute a fourth process for determining the sharpness of an image is recorded, and the fourth process further includes a ratio between the second edge intensity and the first edge intensity. The processing for creating a frequency distribution based on the frequency, the processing for determining the frequency ratio corresponding to the above-mentioned ratios different from each other, and the sharpness of the original image based on the magnitude relationship between the frequency ratio and the threshold The process consists of .
[0140]
Therefore, when the program of the recording medium is executed by a computer, a frequency distribution of the edge strength ratio f is created and the magnitude relationship between the frequency ratio corresponding to different edge strength ratios f and the threshold is compared. Is done. As a result, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f has a smaller value, that is, the pixels whose reciprocal 1 / f has a large value, to the entire image. If the ratio of the pixels having a large value of the reciprocal 1 / f is large, the ratio of pixels having a large edge width ratio b / a between the smoothed image and the original image is large. Will contain many sharp edges.
[0141]
Further, if the edge intensity ratio f is calculated, f = a / b, and the information of h that is the image data change amount can be excluded from the edge intensity ratio f. Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Thereby, if a frequency distribution of the edge strength ratio f is created, information on a truly sharp edge can be reliably reflected in the frequency distribution.
[0142]
Therefore, if the computer is driven using the recording medium of the present invention, the sharpness of the original image can be determined appropriately and stably based on the frequency distribution, regardless of what the original image is. There is an effect that can be done.
[0143]
In addition, creating the frequency distribution and comparing the magnitude relationship between the edge strength ratio and the threshold is a very simple process, and no complicated calculation is required. Therefore, it is possible to easily determine the sharpness. It also has the effect of being able to.
[0144]
As described above, the image processing apparatus according to the sixth aspect of the present invention includes a smoothed image creating unit that creates a smoothed image from an original image, and a first edge strength calculation that calculates a first edge strength of the original image. Means, second edge strength calculating means for calculating the second edge strength of the smoothed image, and sharpness determining means for determining the sharpness of the original image based on the first edge strength and the second edge strength. The sharpness determination means creates a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency, and the ratio of the frequencies corresponding to the different ratios. And the sharpness of the original image is determined based on the magnitude relationship between the frequency ratio and the threshold.
[0145]
Therefore, the sharpness determination means creates a frequency distribution of the edge strength ratio f, and compares the magnitude relationship between the frequency ratio corresponding to the different edge strength ratios f and the threshold value. As a result, it is possible to objectively grasp the ratio of the pixels whose edge intensity ratio f has a smaller value, that is, the pixels whose reciprocal 1 / f has a large value, to the entire image. If the ratio of the pixels having a large value of the reciprocal 1 / f is large, the ratio of pixels having a large edge width ratio b / a between the smoothed image and the original image is large. Will contain many sharp edges.
[0146]
Further, if the edge intensity ratio f is calculated, f = a / b, and the information of h that is the image data change amount can be excluded from the edge intensity ratio f. Therefore, even if the original image includes a portion where the change amount of the image data is different, the size of the change interval of the image data when the change amount of the image data is normalized is necessarily calculated by calculating the edge intensity ratio f. Will be watching. Thereby, if a frequency distribution of the edge strength ratio f is created, information on a truly sharp edge can be reliably reflected in the frequency distribution.
[0147]
Therefore, according to the above configuration, there is an effect that the sharpness of the original image can be determined appropriately and stably based on the frequency distribution regardless of the original image.
[0148]
In addition, creating the frequency distribution and comparing the magnitude relationship between the edge strength ratio and the threshold is a very simple process, and no complicated calculation is required. Therefore, it is possible to easily determine the sharpness. It also has the effect of being able to.
[0149]
As described above, in the image processing apparatus according to the seventh aspect of the present invention, in the configuration of the sixth aspect, the sharpness determining means includes the first edge intensity in the target pixel of the original image and the first in the surrounding pixels. The first edge strength at the target pixel and the second edge strength of the pixel corresponding to the target pixel and the smoothed image when the first edge strength at the target pixel is the maximum among the edge strengths. The ratio between the second edge strength and the first edge strength is obtained by using.
[0150]
Therefore, it can be said that a pixel having a first edge intensity higher than that of surrounding pixels in the original image corresponds to an edge portion in the image. Therefore, by obtaining the edge intensity ratio using the first edge intensity and the second edge intensity of such a pixel, the sharpness of the original image performed based on the frequency distribution created using this edge intensity ratio is calculated. The determination can be made with certainty of the sharpness of the edge portion of the original image. As a result, in addition to the effect of the configuration of the sixth aspect, the reliability of the sharpness determination result can be reliably improved.
[0151]
As described above, the image processing apparatus according to an eighth aspect of the present invention determines the first edge strength for obtaining a ratio between the second edge strength and the first edge strength in the configuration of the seventh aspect. The pixel used in the above configuration is a target pixel in the original image, and at least one of a pixel positioned in the vertical direction of the target pixel and a pixel positioned in the horizontal direction of the target pixel.
[0152]
Therefore, the information on the pixels located in the oblique direction when viewed from the target pixel is reflected in the pixels positioned above, below, left, and right of the target pixel. Therefore, as the pixels used to determine the first edge strength for obtaining the edge strength ratio, the target pixel in the original image, the pixel positioned in the vertical direction of the target pixel, and the horizontal position of the target pixel Even if at least one of the pixels to be considered is considered, the sharpness of the entire original image can be determined in consideration of the sharpness of the edge portion of the original image. That is, in addition to the effect of the configuration according to the seventh aspect, the sharpness can be appropriately determined with a small number of pixels without considering the first edge intensity of all the pixels around the target pixel. Play.
[0153]
In particular, if the pixel of interest and the pixels positioned in the vertical and horizontal directions are taken into consideration in the determination, the above-described effect can be obtained with certainty.
[0154]
As described above, in the image processing apparatus according to the ninth aspect, in the configuration according to any one of the sixth to eighth aspects, the frequency corresponds to each ratio between the second edge strength and the first edge strength. It is the structure which is a relative frequency with respect to the total frequency which added all the frequency to do.
[0155]
Therefore, when a relative frequency distribution composed of the edge intensity ratio and its relative frequency is created, even if the number of pixels of the original image is different, substantially the same distribution shape can be obtained for images with the same sharpness. This makes it unnecessary to set a threshold according to the number of pixels of the original image, and in addition to the effect of any one of claims 6 to 8, the sharpness can be more easily determined. There is an effect.
[0156]
As described above, an image processing apparatus according to a tenth aspect of the present invention is the configuration according to any one of the sixth to ninth aspects, wherein the original image is subjected to a sharpening process according to a determination result by the sharpness determination means. It is the structure further equipped with the sharpening process means to perform.
[0157]
Therefore, since the sharpening processing unit performs sharpening processing on the original image as necessary, in addition to the effect of the configuration according to any one of claims 6 to 9, the original image may or may not be a blurred image. However, there is an effect that a high-quality image can be finally obtained.
[0158]
As described above, a photographic printing apparatus according to an eleventh aspect of the present invention is the image processing apparatus according to any one of the sixth to tenth aspects, and the image data or the original of the image sharpened by the image processing apparatus. And an exposure unit that exposes the photosensitive material based on the image data of the image.
[0159]
Therefore, based on the image data of the image sharpened by the image processing apparatus according to any one of claims 6 to 10 or the image data of the original image, the exposure means exposes the photosensitive material, There is an effect that a high-quality photo print can be obtained.
[Brief description of the drawings]
FIG. 1 is a flowchart showing a flow of operations in an image processing unit of a photographic printing apparatus according to the present invention.
FIG. 2 is a block diagram illustrating a schematic configuration of the image processing unit.
FIG. 3 is an explanatory diagram illustrating an example of a filter for creating a smoothed image.
FIG. 4 is an explanatory diagram illustrating an example of a filter for calculating edge strength.
FIG. 5A is an explanatory diagram showing a relative frequency distribution of the ratio of edge strengths obtained when the original image is an image with high sharpness, and FIG. 5B is an blurred image of the original image. It is explanatory drawing which shows the relative frequency distribution of ratio of edge strength obtained in a certain case.
FIG. 6 is an explanatory diagram illustrating a change in image data at an edge portion in an image between the original image and the blurred image.
FIG. 7 is an explanatory diagram schematically showing a change in image data at each pixel position in a linear region in an image.
[Explanation of symbols]
2 Image processing unit (image processing device, computer)
3 Exposure section (exposure means)
5 Smoothed image creating unit (smoothed image creating means)
6 1st edge strength calculation part (1st edge strength calculation means)
7 Second edge strength calculator (second edge strength calculator)
8 Sharpness judgment part (sharpness judgment means)
9 Sharpening processing part (sharpening processing means)

Claims (9)

A first step of creating the smoothed image from the original image;
A second step of calculating a first edge strength of the original image;
A third step of calculating a second edge strength of the smoothed image;
A fourth step of determining the sharpness of the original image based on the first edge strength and the second edge strength;
The fourth step further includes:
Creating a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency;
Obtaining a ratio of frequencies corresponding to the above-mentioned ratios different from each other;
Determining the sharpness of the original image based on the magnitude relationship between the frequency ratio and the threshold value.
And
In the fourth step, when the first edge intensity at the target pixel is the maximum among the first edge intensity at the target pixel of the original image and the first edge intensity at the surrounding pixels, the attention is paid. A step of obtaining a ratio between the second edge strength and the first edge strength by using the first edge strength in the pixel and the second edge strength of the pixel of interest and the corresponding pixel on the smoothed image; A sharpness determination method for an image, comprising : The pixel used to determine the first edge strength for determining the ratio between the second edge strength and the first edge strength is:
The pixel of interest in the original image,
The image sharpness determination method according to claim 1 , wherein the pixel is at least one of a pixel positioned in a vertical direction of the target pixel and a pixel positioned in a horizontal direction of the target pixel. 3. The image according to claim 1, wherein the frequency is a relative frequency with respect to a total frequency obtained by adding all frequencies corresponding to respective ratios of the second edge strength and the first edge strength. 4. Sharpness judgment method. A first process for creating the smoothed image from the original image;
A second process for calculating the first edge strength of the original image;
A third process for calculating the second edge strength of the smoothed image;
A program for causing the computer to execute a fourth process for determining the sharpness of the original image based on the first edge strength and the second edge strength;
The fourth process further includes:
A process of creating a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency;
A process for obtaining a ratio of frequencies corresponding to the above-mentioned ratios different from each other;
A process for determining the sharpness of the original image based on the magnitude relationship between the frequency ratio and the threshold ,
The fourth processing is performed when the first edge intensity at the target pixel is the maximum among the first edge intensity at the target pixel of the original image and the first edge intensity at the surrounding pixels. A process of obtaining a ratio between the second edge strength and the first edge strength using the first edge strength of the pixel and the second edge strength of the pixel of interest and the corresponding pixel on the smoothed image; A recording medium on which a program for performing processing for determining the sharpness of an image is included . Smoothed image creating means for creating the smoothed image from the original image;
First edge strength calculating means for calculating a first edge strength of the original image;
Second edge strength calculating means for calculating a second edge strength of the smoothed image;
Sharpness determination means for determining the sharpness of the original image based on the first edge strength and the second edge strength,
The sharpness determination means creates a frequency distribution based on the ratio between the second edge strength and the first edge strength and the frequency, and obtains a frequency ratio corresponding to the different ratios, Based on the magnitude relationship between the frequency ratio and the threshold, the sharpness of the original image is determined , and the first edge intensity at the target pixel of the original image and the first edge intensity at the surrounding pixels are When the first edge intensity at the target pixel is maximized, the second edge intensity of the corresponding pixel on the target pixel and the smoothed image using the first edge intensity at the target pixel and the second edge intensity is used. An image processing apparatus for obtaining a ratio between an edge strength and the first edge strength . The pixel used to determine the first edge strength for determining the ratio between the second edge strength and the first edge strength is:
The pixel of interest in the original image,
The image processing apparatus according to claim 5 , wherein the image processing apparatus is at least one of a pixel positioned in a vertical direction of the target pixel and a pixel positioned in a horizontal direction of the target pixel. The image processing according to claim 5 or 6 , wherein the frequency is a relative frequency with respect to a total frequency obtained by adding all frequencies corresponding to respective ratios of the second edge strength and the first edge strength. apparatus. The image processing apparatus according to claim 5 , further comprising a sharpening processing unit that performs a sharpening process on the original image in accordance with a determination result by the sharpness determination unit. . An image processing apparatus according to any one of claims 5 to 8 ,
A photographic printing apparatus comprising: an exposure unit that exposes a photosensitive material based on image data of an image sharpened by the image processing apparatus or image data of an original image.

Images