JP3897370B2 - Imaging device - Google Patents

Description

また、全てのサンプルポイントグループに含ませることができない場合は、同サンプルポイントを基準とする新たなサンプルポイントグループを作成する。（ｓｔｅｐ６．２と同じ処理）
（ｓｔｅｐ７）
全てのサンプルポイントにおいて、ステップ６の処理が終了したら、ステップ６で作られた一つあるいは複数個のサンプルポイントグループの中から、本当の白のグループをさがすわけであるが、実際にはどれが白であるかわからない。そこで、輝度の高いものは白であるという仮定をして、前記複数のサンプルポイントグループの輝度情報ＧｐＢｒｉｇｈｔｎｅｓｓを用いて、輝度の大きいものに重み付けを行う。重み付けは以下の式で行なう。また、本重み付け処理を行うか行わないかは、ユーザが予め設定可能である。
【００３９】

８．１
ステップ４で求め座標にあらわしたホワイト点（Ｘ１，Ｙ１）（Ｘ２，Ｙ２）が所定範囲内にないものとステップ５（５）式で判別されたならば、図６に示すように同座標点を所定範囲枠上に移動し、範囲枠上の座標（Ｘ’，Ｙ’）から次式を用いて、Ｍａ１’、Ｍａ２’、Ｙｅ１’、Ｙｅ２’を新たに求め直す。
【００４０】
Ｍａ１’＝（１＋Ｙ１’）＊Ｇｒ１
Ｍａ２’＝（１＋Ｙ２’）＊Ｇｒ２
Ｙｅ１’＝（１＋Ｘ１’）＊Ｃｙ１
Ｙｅ２’＝（１＋Ｘ２’）＊Ｃｙ２
８．２
但し、座標点の移動の仕方は図のように、座標点に対して最も近い所定範囲枠上の座標に移動するものとする。この座標移動処理を色クリップ処理とよぶ。この色クリップされたサンプルポイントの総数をＳＮ２ とし、色クリップによって求められる積分値をＭａ１’，Ｍａ２’，Ｇｒ１’，Ｇｒ２’，Ｃｙ１’，Ｃｙ２’，Ｙｅ１’，Ｙｅ２’とする。
【００４１】
（ｓｔｅｐ９）
９．１
ステップ６及び７で得られた全てのサンプルポイントグループに対して、以下の式を用いて、白判別範囲内の積分値（ＳＭａ１，ＳＭａ２，ＳＧｒ１，ＳＧｒ２，ＳＣｙ１，ＳＣｙ２，ＳＹｅ１，ＳＹｅ２）を求める。
【００４２】
ＳＭａ１＝ＳＭａ１＋ＧｐＭａ１＊ＧｐＷｅｉｇｈｔ
ＳＭａ２＝ＳＭａ２＋ＧｐＭａ２＊ＧｐＷｅｉｇｈｔ
ＳＧｒ１＝ＳＧｒ１＋ＧｐＧｒ１＊ＧｐＷｅｉｇｈｔ
ＳＧｒ２＝ＳＧｒ２＋ＧｐＧｒ２＊ＧｐＷｅｉｇｈｔ
ＳＣｙ１＝ＳＣｙ１＋ＧｐＣｙ１＊ＧｐＷｅｉｇｈｔ
ＳＣｙ２＝ＳＣｙ２＋ＧｐＣｙ２＊ＧｐＷｅｉｇｈｔ
ＳＹｅ１＝ＳＹｅ１＋ＧｐＹｅ１＊ＧｐＷｅｉｇｈｔ
ＳＹｅ２＝ＳＹｅ２＋ＧｐＹｅ２＊ＧｐＷｅｉｇｈｔ
９．２
また、同時に白とみなされたサンプルポイント数ＳＮ１を求める。
【００４３】
ＳＮ１＝ＳＮ１＋ＧｐＮｕｍｂｅｒ
（ｓｔｅｐ１０）
サンプル数（ＳＮ１＋ＳＮ２）が０または所定以上得られていなければ、ホワイトバランス調整データとして、所定の色温度（例えば５０００Ｋ）のホワイトバランス調整値を用いる。
【００４４】
（ｓｔｅｐ１１）
白撮影時の平均輝度レベルとしての、
ＳＹ＝（ＳＭａ１＋ＳＭａ２＋ＳＧｒ１＋ＳＧｒ２＋ＳＣｙ１＋ＳＣｙ２＋ＳＹｅ１＋ＳＹｅ２）／８
を求め、この平均輝度レベルに対する各色の積分値の比率を求める。
【００４５】

クリップ時の平均輝度レベルとしての
ＳＹ’＝（ＳＭａ１’＋ＳＭａ２’＋ＳＧｒ１’＋ＳＧｒ２’＋ＳＣｙ１’＋ＳＣｙ２’＋ＳＹｅ１’＋ＳＹｅ２’）／８
を求め、この平均輝度レベルに対する各色の積分値の比率を求める。
【００４６】

ステップ１１及び１２で得られた、各色の積分値の比率と、白判別範囲内の積分サンプル数ＳＮ１ と色クリップによる積分サンプル数ＳＮ２ より、ホワイトバランス調整データ（ｗｍｇ１，ｗｇ１，ｗｃｙ１，ｗｙｅ１，ｗｍｇ２，ｗｇ２，ｗｃｙ２，ｗｙｅ２）を作る。
【００４７】
例えば、

のような処理を施す。これらの値をホワイトバランス調整データとして記憶する。
【００４８】
上記処理で得られたホワイトバランス調整データを、撮像素子から得られた画素毎の信号値にかけることでホワイトバランスをとることができる。
【００４９】
以上、撮像素子からの信号値でホワイトバランスのための座標を作り、その座標におおいて白領域に入ったサンプル点に対し、白いものは相対的に輝度値が高いという仮定のもとに重み付けを行なった後、そのサンプル点で積分を行なう処理をするので、画像中に白が少ない場合であっても、重み付けにより、他の色に影響されホワイトバランスが大きくずれることを回避することが可能である。
【００５０】
また、撮像素子からの出力信号をフィルタ配列毎にブロック化する手段と、其の複数ブロックを任意にあるいは千鳥状に間引く手段の少なくとも一つ以上の手段を備えていることで、撮像素子の全ての画素に対して計算を行わずにすみ、処理の高速化が実現できる。
【００５１】
また、前記分割手段によって分割されたブロック中に、飽和画素があるか否かを判断する手段、ノイズ画素はあるか否かを判断する手段、ブロック内に画像のエッジか含まれるか否かを判断する手段の少なくともひとつ以上を備えた適正判断手段を備えていることから、参照ブロックが、被写体の色温度を求めるのに適したブロックか否かを判断できる。
【００５２】
また、色フィルタ配列上、ある色フィルタの画素の信号値に隣接した別の色のフィルタの光が漏れこみ、その結果、同一被写体の同一ブロック内における同一色の画素の値が互いに異なるということに起因する被写体の色温度を判別できないといった問題点を、白板を撮影し、同一ブロック内における同一色の画素の信号値が同じになるようある係数を各色フィルタ毎にかけることにより回避することが可能となる。
【００５３】
また、被写体の照度情報、フリッカー情報、フラッシュ光の有無等の情報から、前記白判別範囲を変化させることにより、光源が蛍光燈の場合の緑成分補正や、フラッシュ時のホワイトバランス、日中シンクロ撮影時におけるホワイトバランスをより正確にとることが可能となる。
【００５４】
また、（Ｒ−Ｙ）／Ｙ，（Ｂ−Ｙ）／Ｙに代わって（Ｍａ−Ｇｒ）／Ｇｒまたは（Ｍａ−Ｇｒ）／Ｍａと（Ｙｅ−Ｃｙ）／Ｃｙまたは（Ｙｅ−Ｃｙ）／Ｙｅによって座標を作り色温度の検出をすることにより、（Ｍａ，Ｇｒ，Ｃｙ，Ｙｅ）の色フィルタを有する撮像素子の読み出し信号から直接に色温度検出ができるため、本露光前の色温度検出の為の露光および信号処理を省略することができ、簡易でかつ正確な色温度検出が可能となる。また、白色部分を少量しか含まない被写体撮影時にあっても（Ｍａ−Ｇｒ）／Ｇｒ＝ａ，（Ｙｅ−Ｃｙ）／Ｃｙ＝ｂの形で白色判別範囲内の座標を与えることにより、白色判別範囲内におけるＭａ’＝（１＋ａ）＊Ｇｒ，Ｙｅ’＝（１＋ｂ）＊Ｃｙの形の簡易な処理で撮像素子出力を置き換えることができ、前記撮影条件にあってもホワイトバランスが大きくずれないホワイトバランス調整が可能となる。
【００５５】
以上、本実施例はフィルタが４色の場合を考えたが、３色の場合でも同様の操作でホワイトバランス調整データを得ることができるのは明白である。
【００５６】
（実施例２）
図８は本発明の第２の実施例に係る電子カメラの信号処理の流れを示した図である。本実施例における撮像素子はフィールド読み出しを行なうため、図１１に示すように撮像素子からの出力は垂直方向２画素が加算されて読み出される。この図において、
Ｗｂ＝Ｍａ＋Ｃｙ
Ｇｒ＝Ｇ＋Ｙｅ
Ｇｂ＝Ｃｙ＋Ｇ
Ｗｒ＝Ｙｅ＋Ｍａ
である。色フィルタが（Ｍａ、Ｇ 、Ｃｙ、Ｙｅ）から（Ｗｂ、Ｇｒ、Ｇｂ、Ｗｒ）に変わったものと考えるとフレーム読み出しとほぼ同じ処理を行なうことになる。
【００５７】
まず、オプティカルブラック領域における各フィルタ出力の積分値を用いて黒レベルの調整を行なう。次に、ホワイトバランス処理を行ない、白点におけるＷｂ、Ｇｒ、Ｇｂ、Ｗｒの出力ゲインが同じになるようにする。
【００５８】
輝度信号（Ｙ）を作るには、色フィルタによるモアレを除去するために水平ローパスフィルタがかけられた後、アパーチャー補正を行なう。ここでは、水平、垂直にそれぞれハイパスフィルタがかけられ、ゲインを調整、アパチャー信号の振幅の小さいものにはその振幅が大きくなるように、また振幅の大きいものにはその振幅が小さくなるようなＰｅａｋ Ｔｏ Ｐｅａｋ処理が施され、水平、垂直が足され、さらにゲインをかけて、輝度成分（Ｙｎ）に加えられる。
【００５９】
色差信号（Ｒ−Ｙ，Ｂ−Ｙ）を作るには、まず同時化回路で４色の信号を同時化し、撮像面全領域に４つの色信号が割り当てられるよう画素補間を行なう。次に４×３のマトリクスを用いてＷｂＧｒＧｂＷｒ信号をＲＧＢ信号に変換する。このとき、マトリクスは、ホワイトバランス情報から被写体の色温度を判別して、その色温度における色再現の最もよくなるようなマトリクスが用いられる。次に、ＲＧＢ信号をＲ−Ｙ、Ｂ−Ｙ信号に変換し、モアレ低減のためのローパスフィルタをかけ、Ｙ信号を参考に飽和の色消し処理を行なう。
【００６０】
このようにして作られた、輝度信号（Ｙ）と色差信号（Ｒ−Ｙ，Ｂ−Ｙ）は、ＲＧＢ信号に変換され、ガンマ補正処理を行なった後、記録される。
【００６１】
次に、本発明の主眼点である、ホワイトバランス処理について詳細に説明する。ＣＣＤ補色フィルターが図１１（ａ）のように配列している場合、図の８画素配列を単位ブロックとして、この単位ブロックの繰り返しで全体の配列が成り立っている。ここで、フィールド読み出しを行なうため、１フィールドでは、図１１（ｂ）のような信号が読み出される。
【００６２】
以下、ホワイトバランス処理を図９，図１０のフローチャートを参照して説明する。
【００６３】
（ｓｔｅｐ１）白判別範囲の設定
予め白板を様々な色温度で撮影し、その時の、
（（Ｗｒ−Ｇｂ）−（Ｗｂ−Ｇｒ））／（Ｗｒ＋Ｇｂ）をＸ軸
（（Ｗｒ−Ｇｂ）＋（Ｗｂ−Ｇｒ））／（Ｗｂ＋Ｇｒ）をＹ軸
とし、プロットしたものを図１３に示す。実施例１と同様に、被写体の照度、フリッカーの有無でＸ軸の幅を変化させ、また、フラッシュの有無、被写体の照度によってＹ軸の幅を変化させる。
【００６４】
（ｓｔｅｐ２）サンプルポイント抽出
図１１に示すような加算後の画素４画素単位（Ｗｂ，Ｇｂ，Ｇｒ，Ｗｒ）を１サンプルポイントと呼び、新たなサンプリングポイントを選択する。
【００６５】
（ｓｔｅｐ３）
３．１ 飽和判別
サンプルポイント４画素に飽和画素が含まれるか否かを判断し、次式を一つでも満たさない場合、飽和画素があると判断し、本サンプルポイントは使用しないで、ステップ２に戻る。
【００６６】
Ｗｂ＜ＢｒｉｇｈｔｎｅｓｓＴｈｒｅｓｈｏｌｄＷｂ
Ｇｂ＜ＢｒｉｇｈｔｎｅｓｓＴｈｒｅｓｈｏｌｄＧｂ
Ｇｒ＜ＢｒｉｇｈｔｎｅｓｓＴｈｒｅｓｈｏｌｄＧｒ
Ｗｒ＜ＢｒｉｇｈｔｎｅｓｓＴｈｒｅｓｈｏｌｄＷｒ
３．２ ノイズ判別
サンプルポイント４画素が、Ｓ／Ｎが悪い場合、つまり次式を満たさない場合、ノイズ画素であると判断し、本サンプルポイントは使用しないで、ステップ２に戻る。
【００６７】
（Ｗｂ＋Ｇｂ＋Ｇｒ＋Ｗｒ）／４＞ＤａｒｋＴｈｒｅｓｈｏｌｄ
（ｓｔｅｐ４）
サンプルポイントにおいて、以下の式の値を求める。
【００６８】
Ｘ１＝（（Ｗｒ−Ｇｂ）−（Ｗｂ−Ｇｒ））／（Ｗｒ＋Ｇｂ） （１）
Ｙ１＝（（Ｗｒ−Ｇｂ）＋（Ｗｂ−Ｇｒ））／（Ｗｂ＋Ｇｒ） （２）
（ｓｔｅｐ５）
（（Ｗｒ−Ｇｂ）−（Ｗｂ−Ｇｒ））／（Ｗｒ＋Ｇｂ）をＸ軸、（（Ｗｒ−Ｇｂ）＋（Ｗｂ−Ｇｒ））／（Ｗｂ＋Ｇｒ）をＹ軸にとり、式（１）（２）が、ＸＹ軸上に設けた所定の領域内にある場合、つまり以下の条件式を満たす場合、
ａ＜Ｘ１＜ｂ、ｃ＜Ｙ１＜ｄ （３）
同サンプルポイントをＷＢ設定するためのデータとして有効とみなされ、ステップ４へ進み、式（３）を満たさない場合はステップ８に進む。
【００６９】
（ｓｔｅｐ６）
６．１
まず、同サンプルポイントにおいて、以下の式を用いて、ＷＢ座標におけるサンプルポイントのＸＹ軸値の平均値、及び、輝度値を求める。
【００７０】
ＡｖｅｒａｇｅＸ＝Ｘ１
ＡｖｅｒａｇｅＹ＝Ｙ１
ＡｖｅｒａｇｅＢｒｉｇｈｔｎｅｓｓ＝（Ｗｂ＋Ｇｒ＋Ｇｂ＋Ｗｒ）／２
６．２
同サンプルポイントがＷＢ設定有効データとみなされた最初のサンプルポイントである場合は、図７に示すような値をパラメータとして持つサンプルポイントグループを作り、ステップ６．１で求めた値、及び、同ポイントの画素値を代入する。
【００７１】
ＧｐＸ＝ＡｖｅｒａｇｅＸ
ＧｐＹ＝ＡｖｅｒａｇｅＹ
ＧｐＢｒｉｇｈｔｎｅｓｓ＝ＡｖｅｒａｇｅＢｒｉｇｈｔｎｅｓｓ
ＧｐＷｂ＝Ｗｂ
ＧｐＧｒ＝Ｇｒ
ＧｐＧｂ＝Ｇｂ
ＧｐＷｒ＝Ｗｒ
ＧｐＮｕｍｂｅｒ＝１
ＧｐＷｅｉｇｈｔ＝１
６．３
また、同サンプルポイントがＷＢ設定有効データとみなされた最初でないサンプルポイントである場合は、既存のサンプルポイントグループのＧｐＸ、ＧｐＹ、ＧｐＢｒｉｇｈｔｎｅｓｓの値を用いて、以下の条件式を満たすときに、同サンプルポイントはそのサンプルポイントグループに含まれると判断し、サンプルポイントグループに含ませる。
【００７２】

また、全てのサンプルポイントグループに含ませることができない場合は、同サンプルポイントを基準とする新たなサンプルポイントグループを作成する。（ｓｔｅｐ６．２と同じ処理）
（ｓｔｅｐ７）
全てのサンプルポイントにおいて、ステップ６の処理が終了したら、ステップ６で作られた一つあるいは複数個のサンプルポイントグループの中から、本当の白のグループをさがすわけであるが、実際にはどれが白であるかわからない。そこで、輝度の高いものは白であるという仮定をして、前記複数のサンプルポイントグループの輝度情報ＧｐＢｒｉｇｈｔｎｅｓｓを用いて、輝度の大きいものに重み付けを行う。重み付けは以下の式で行なう。また、本重み付け処理を行うか行わないかは、ユーザが予め設定可能である。
【００７３】

８．１
ステップ４で求め座標にあらわしたホワイト点（Ｘ１，Ｙ１）（Ｘ２，Ｙ２）が所定範囲内にないものとステップ５（３）式で判別されたならば、同座標点を所定範囲枠上に移動し、ＷＢ’、Ｗｒ’を新たに求め直す。
【００７４】
８．２
この色クリップされたサンプルポイントの総数をＳＮ２とし、色クリップによって求められる積分値をＷｂ’，Ｇｒ’，Ｇｂ’，Ｗｒ’とする。
【００７５】
（ｓｔｅｐ９）
９．１
ステップ６及び７で得られた全てのサンプルポイントグループに対して、以下の式を用いて、白判別範囲内の積分値（ＳＷｂ，ＳＧｒ，ＳＧｂ，ＳＷｒ）を求める。
【００７６】
ＳＷｂ＝ＳＷｂ＋ＧｐＷｂ＊ＧｐＷｅｉｇｈｔ
ＳＧｒ＝ＳＧｒ＋ＧｐＧｒ＊ＧｐＷｅｉｇｈｔ
ＳＧｂ＝ＳＧｂ＋ＧｐＧｂ＊ＧｐＷｅｉｇｈｔ
ＳＷｒ＝ＳＷｒ＋ＧｐＷｒ＊ＧｐＷｅｉｇｈｔ
９．２
また、同時に白とみなされたサンプルポイント数ＳＮ１を求める。
【００７７】
ＳＮ１＝ＳＮ１＋ＧｐＮｕｍｂｅｒ
（ｓｔｅｐ１０）
サンプル数（ＳＮ１＋ＳＮ２）が０または所定以上得られていなければ、ホワイトバランス調整データとして、所定の色温度（例えば５０００Ｋ）のホワイトバランス調整値を用いる。
【００７８】
（ｓｔｅｐ１１）
白撮影時の平均輝度レベルとしての、
ＳＹ＝（ＳＷｂ＋ＳＧｒ＋ＳＧｂ＋ＳＷｒ）／４
を求め、この平均輝度レベルに対する各色の積分値の比率を求める。
【００７９】
ｇｗｂ＝ＳＹ／（２＊ＳＷｂ）
ｇｇｒ＝ＳＹ／（２＊ＳＧｒ）
ｇｇｂ＝ＳＹ／（２＊ＳＧｂ）
ｇｗｒ＝ＳＹ／（２＊ＳＷｒ）
（ｓｔｅｐ１２）
クリップ時の平均輝度レベルとしての
ＳＹ’＝（ＳＷｂ’＋ＳＧｒ’＋ＳＧｂ’＋ＳＷｒ’）／４
を求め、この平均輝度レベルに対する各色の積分値の比率を求める。
【００８０】
ｇｗｂ’＝ＳＹ’／（２＊ＳＷｂ’）
ｇｇｒ’＝ＳＹ’／（２＊ＳＧｒ’）
ｇｇｂ’＝ＳＹ’／（２＊ＳＧｂ’）
ｇｗｒ’＝ ＳＹ’／（２＊ＳＷｒ’）
（ｓｔｅｐ１３）
ステップ１１及び１２で得られた、各色の積分値の比率と、白判別範囲内の積分サンプル数ＳＮ１と色クリップによる積分サンプル数ＳＮ２より、ホワイトバランス調整データ（ｗｗｂ，ｗｇｒ，ｗｇｂ，ｗｗｒ）を作る。
【００８１】
例えば、

のような処理を施す。これらの値をホワイトバランス調整データとして記憶する。
【００８２】
上記処理で得られたホワイトバランス調整データを、撮像素子から得られた画素毎の信号値にかけることでホワイトバランスをとることができる。以上、本実施例はフィルタが４色の場合を考えたが、３色の場合でも同様の操作でホワイトバランス調整データを得ることができるのは明白である。
【００８３】
（実施例３）
図１４は本発明の実施例３のホワイトバランスの処理フローチャートの１部分であり、図２におけるステップ６に相当する部分である。ここは、ホワイトバランスグループを作成した後、グループに重み付けをする部分であるが、本実施例は、この重み付けに、撮影時の照度情報を用いることを特徴とする。この照度情報とは例えばＥＶ値でありフラッシュＯｎＯｆｆの情報である。
【００８４】
カメラ側から情報としてＥＶ値をもらい、ＥＶ値が大きい場合は外で撮影（太陽光）したものである場合が大きいので、図１５に示す（ａ）のように白座標範囲を限定する。また、逆にＥＶ値が小さいのは夕日、もしくは人工光と限定し、図１５（ｂ）のように白座標範囲を限定する。また、フラッシュがＯＮのときには図１５（ｃ）のように白座標範囲を限定する。ここで、サンプルポイントグループすべてに対し、以下のように重み付けを行なう。つまり、限定座標範囲にあるホワイトバランスグループの重みを増す。
【００８５】

このような重み付けを行なうことで、白の輝度の低い場合にも、より好ましいホワイトバランスを行なうことができ、また、限定座標範囲に入らない点が白である場合でも、重み付けによる白グループ選択を行っているため、ホワイトバランスがおおきくずれることはない。
【００８６】
また、本実施例における重み付けは実施例２におけるステップ７に用いても、また、実施例１及び実施例２の重み付けの手法と組み合わせて用いても、さしつかえない。
【００８７】
【発明の効果】
以上説明したように、本発明によれば、ホワイトバランスを良好に調整できる撮像装置を提供することができる。
すなわち、本発明では、全画面のうち任意の数に間引かれた参照ブロックに、画像のエッジか含まれるか否かによって参照ブロックが白色判定に適しているか判断しているため、例えば、少数画素のブロックからであっても、被写体の色温度を正確にかつ高速に求めることが出来る。
【図面の簡単な説明】
【図１】 第１の実施例のホワイトバランス処理のフローチャートである。
【図２】 第１の実施例のホワイトバランス処理のフローチャートである。
【図３】 第１の実施例のホワイトバランス処理のフローチャートである。
【図４】 第１の実施例のＷＢ検出回路を用いた電子カメラの信号処理ブロック図である。
【図５】 撮像素子の色フィルタ配列パターンを示した説明図である。
【図６】 ホワイトバランス処理に用いるホワイトバランス座標を示した説明図である。
【図７】 サンプルポイントグループの各パラメータを示した説明図である。
【図８】 第２の実施例のＷＢ検出回路を用いた電子カメラの信号処理ブロック図である。
【図９】 第２の実施例のホワイトバランス処理のフローチャートである。
【図１０】 第２の実施例のホワイトバランス処理のフローチャートである。
【図１１】 第２の実施例の撮像素子の読み出し手法を示した説明図である。
【図１２】 白判別曲線範囲幅の決定手法を示した説明図である。
【図１３】 第２の実施例における白判別範囲座標を示した説明図である。
【図１４】 第３の実施例のホワイトバランスの処理の一部分を示すフローチャートである。
【図１５】 第３の実施例の白座標範囲の決定の説明図である。
【図１６】 従来例のデジタル電子カメラのブロック図である。
【図１７】 従来例のブロック図である。
【図１８】 従来例のホワイトバランス制御の説明図である。[0001]
BACKGROUND OF THE INVENTION
The present invention belongs to the technical field of imaging devices that capture still images.
[0002]
[Prior art]
FIG. 16 is a block diagram of a conventional digital electronic camera.
[0003]
In FIG. 16, reference numeral 300 denotes a digital electronic camera, and 308 denotes a recording medium such as a memory card. In the digital electronic camera 300, reference numeral 301 denotes an imaging lens whose focal length and angle of view can be adjusted, 302 denotes a diaphragm / shutter having both an aperture function and a shutter function, and 304 denotes a mechanical system driving circuit for the imaging lens 301 and the diaphragm / shutter 302. . 101 is an image sensor that converts reflected light from an object into an electrical signal, 103 is a timing signal generation circuit (hereinafter referred to as TG) that generates a timing signal necessary for operating the image sensor, and 102 is a timing signal generation circuit. An image sensor driving circuit that amplifies the above signal to a level capable of driving the image signal, 104 is a preprocess means including a CDS circuit and an AGC circuit for removing output noise of the image sensor 101, 105 is an A / D converter, Is an imaging signal processing circuit having an imaging signal processing circuit for processing an A / D converted digital signal, 108 is a system control CPU, 116 is a display for assisting operation and an operation display unit indicating the state of the camera, 118 is This is a switch for the external photographer to control the start of camera shooting. The first stroke SW1 and the second stroke SW2 are two steps. Operation is allowed. Reference numeral 307 denotes a recording medium I / F for connecting the digital electronic camera 300 and the recording medium 308. Reference numeral 305 denotes a distance measuring circuit that measures the distance between the imaging device and the subject for focus adjustment of the optical system 301, and reference numeral 306 denotes a photometric circuit that measures the brightness of the subject.
[0004]
FIG. 17 is a block diagram showing the internal configuration of the 303 imaging signal processing circuit and its periphery. Reference numeral 101 denotes an image pickup device (CCD) having a complementary color filter. The picked-up signal is input to a 105 A / D converter via 104 preprocessing means, converted into a digital signal, and then input to a 303 image pickup signal processing circuit. The The input signal is temporarily stored in the 410 memory, or the input signal is directly input to the 401 enhancer / C_SEP circuit. A luminance signal and a chrominance signal are separated using a 401 enhancer / C_SEP circuit and a 402 delay unit, and the luminance signal is enhanced and compensated for a high frequency part. The color signals output from 401 are signals (Wr, Wb, Gr, Gb) obtained by adding CCD color filters (Ma, Gr, Cy, Ye), respectively, and the same color signals are converted into RGB signals in 403C_MTX. In 404, the luminance signal Y and the color signal are filtered. Reference numeral 405WB denotes a white balance circuit that controls the gains of the color signals RGB in accordance with 408AWB. Reference numeral 406 denotes a gamma circuit that performs gamma processing on Y and RGB, and 407C_YMTX denotes a matrix circuit that converts the gamma-processed RGB signal into color difference signals RY and BY. 408AWB is a control signal for white balance control by integrating RGB signals or 407C_YMTX outputs RY, BY signals and Y signals for a certain period and controlling the gains of the R and B signals at 405WB according to the integrated value. Is generated. Reference numeral 409 denotes a filter for performing filter processing on the color difference signal. The luminance signal Y and the color difference signals RY and BY are stored in 410 memories for one image, and then the data compression processing is performed in the 411 compression circuit. Reference numeral 412 denotes a pixel addition circuit that performs pixel addition in the vertical direction when the CCD is frame-read.
[0005]
FIG. 18A is a detailed drawing of 408AWB, which is a clip circuit that inputs a color difference signal (R−Y, B−Y) and restricts input of a large amplitude exceeding a predetermined value with respect to the amplitude of the signal. The color difference signal and the luminance signal that have passed through the clipping circuit are divided into a plurality of blocks, for example, one screen, integrated for each divided block, and white in coordinates formed by (RY) and (BY). A change range at the time of color temperature change is provided as a white discrimination range (as shown in FIG. 18B), and it is determined whether the integrated value for each block is within the white discrimination range on the same coordinate. The system control CPU 108 performs control for determining the gains of the R signal and the B signal using the integral value within the discrimination range, and adjusts the gains of the respective R / B with the control value corresponding to the gain.
[0006]
[Problems to be solved by the invention]
The white balance control according to the conventional example converges to a control state with the passage of time in order to adapt at the time of moving image shooting. However, in order to apply the white balance control based on the above-described conventional example in still image shooting, the image sensor is once exposed before image shooting (main exposure), and a color difference signal is generated from the exposed signal using a signal processing circuit. After the color temperature situation is detected from the position on the coordinates of (RY) and (BY) by the above-described conventional white balance detection and an adjustment value at the same color temperature is obtained, the adjustment value obtained previously by performing the main exposure. Adjust the gain using to adjust the white balance.
[0007]
In this way, it is necessary to detect the correct color temperature with a single white balance detection. However, as in the past, coordinates are created with (RY) and (BY), and a white discrimination range is set on the coordinates. In this method, white photography is performed when a certain color is photographed at a low luminance and at a certain color temperature (particularly, a color temperature within the white discrimination range and far from the intersection of the RY axis and the BY axis). In both cases, the white temperature falls within the white discrimination range, so that it is difficult to specify the color temperature and the accurate color temperature cannot be detected. For example, as shown in FIG. 18C, the relationship between RY and Y is a region surrounded by three points a, b, and o when the color temperature change is between α and β. Exists. On the other hand, it is assumed that a certain color (a color) exists in an area surrounded by three points c, d, and o. When white is discriminated at the RY level (e) as in the prior art, the area (F ) Is also included, which hinders color temperature detection.
[0008]
  The present invention has been made to solve the above-described problems, and is an imaging device capable of adjusting white balance satisfactorily.PlaceOfferChallenge to doIt is what.
[0009]
[Means for Solving the Problems]
  In order to solve the above problems, in the present invention, the imaging apparatus is as follows (1)., (2)Configure as follows.
  (1)In an imaging device having a white balance adjustment function,
  An image sensor having a plurality of color filters having different spectral characteristics;
  The output signal from the image sensor is divided into a plurality of blocks based on the unit arrangement in the arrangement of the plurality of color filters, the output signals of some of the blocks are thinned out, and the image by the output signal of each block after thinning out It is determined whether the output signal of the block can be used for the white balance adjustment based on the edge condition ofAppropriate judgment means,
WithImaging device.
  (2)In the imaging apparatus according to (1),
The situation of the edge of the image by the output signal of each block is whether or not the difference between the output signal values of the filters of the same color in each block is smaller than a predetermined value.Imaging equipmentPlace.
[0018]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described in detail by way of examples.
[0019]
【Example】
Embodiments of the present invention will be described below with reference to the drawings.
[0020]
Example 1
FIG. 4 is a block diagram showing the flow of signal processing of the electronic camera according to the first embodiment of the present invention. Since the image sensor in the present embodiment performs frame reading, the output from the image sensor is output as a filter attached to the image sensor. First, the black level is adjusted using the integrated value of each filter output in the optical black region. Next, white balance processing is performed so that the output gains of Ma, Gr, Cy, and Ye at the white point are the same.
[0021]
In order to create a luminance signal (Y), aperture correction is performed after a low-pass filter is applied to remove moire caused by the color filter. Here, a high-pass filter is applied horizontally and vertically, and the gain is adjusted. The peak is increased when the aperture signal has a small amplitude, and the peak is decreased when the aperture signal is large. To Peak processing is performed, horizontal and vertical are added, and further gain is applied to the luminance component (Yn).
[0022]
In order to generate the color difference signals (R−Y, B−Y), first, the signals of the four colors are synchronized by the synchronization circuit, and pixel interpolation is performed so that the four color signals are assigned to the entire area of the imaging surface. Next, the MGYC signal is converted into an RGB signal using a 4 × 3 matrix. At this time, the matrix is used such that the color temperature of the subject is determined from the white balance information and the color reproduction at the color temperature is the best. Next, the RGB signals are converted into RY and BY signals, a low-pass filter for moire reduction is applied, and saturation achromatic processing is performed with reference to the Y signals.
[0023]
The luminance signal (Y) and the color difference signals (R−Y, B−Y) produced in this way are converted into RGB signals, subjected to gamma correction processing, and then recorded.
[0024]
Next, white balance processing, which is the main point of the present invention, will be described in detail. When the CCD complementary color filters are arranged as shown in FIG. 5, the entire arrangement is formed by repeating this unit block with the 8-pixel arrangement shown in the figure as a unit block. Ma1, Ma2, Gr1, Gr2, Cy1, Cy2, Ye1, and Ye2 are set in accordance with the color filters of the eight pixels. The output of the same color filter is divided into two colors (Ma1 and Ma2, Gr1 and Gr2, Cy1 and Cy2, Ye1 and Ye2), and the output levels of the pixels of the same color are different because the colors of adjacent pixels are different. Because.
[0025]
Hereinafter, the white balance processing will be described with reference to the flowcharts of FIGS.
[0026]
(Step 1) Initial setting
1.1 Error absorption
A predetermined coefficient is applied to all the image signals output from the CCD image sensor. This corrects that the output values from the filters of the same color differ when the same color is photographed due to the arrangement of the color filters on the CCD image sensor. This will be described with reference to FIG. 5. For example, when a white plate is photographed, the signal values may differ greatly between Ma1 and Ma2 and between Gr1 and Gr2 depending on the image sensor. This is considered to be influenced by the Cy and Ye filters, and it is necessary to absorb by applying a coefficient that makes this value the same.
[0027]
Ma1 = Ma1 * Km1
Ma2 = Ma2 * Km2
Gr1 = Gr1 * Kg1
Gr2 = Gr2 * Kg2
Cy1 = Cy1 * Kc1
Cy2 = Cy2 * Kc2
Ye1 = Ye1 * Ky1
Ye2 = Ye2 * Ky2
(However, each coefficient K * is a value measured in advance for each CCD imager)
1.2 White discrimination range width setting
Take a picture of a white board in advance at various color temperatures.
(Ye-Cy) / Cy on the X axis (the influence of the change in color temperature is large)
(Ma-Gr) / Gr as Y axis
The plot is called a white discrimination curve, as shown in FIG. The value in the X-axis direction is sensitive to changes in color temperature. The color temperature decreases as going in the + direction. The Y axis direction is sensitive to green and red. Therefore, green and red can be corrected by changing the width dy of the Y axis. In this embodiment, dy is changed depending on the illuminance of the subject or the presence or absence of flicker. The light component of the fluorescent lamp has a green spectrum compared to sunlight. In other words, the subject color is more green than when shooting in sunlight. In order to correct this, green correction can be performed by widening the white discrimination region in the green direction of the Y axis (the value of dy in FIG. 6). Therefore, if the illuminance of the subject is dark, there is a high possibility of being under fluorescent light, and if there is flicker, it is under fluorescent light, so the value of dy is increased. 12A shows the white range width in the case of normal light photography, and FIG. 12B shows the white range width in the case of fluorescent light photography.
[0028]
Further, the color temperature of the subject can be predicted to some extent from the presence / absence of flash light and the illuminance information of the subject. Thus, more accurate white balance can be achieved by limiting the X-axis range. FIG. 12C is a diagram showing a white range width at the time of flash photography, and is limited to dx1 based on flash-on and illuminance information with respect to a normal X-axis range dx.
[0029]
(Step 2) Extraction of sample points
An 8-pixel unit as shown in FIG. 3 is called one sample point, and a new sampling point is selected.
[0030]
(Step 3) Appropriate judgment processing at sample points
3.1 Saturation discrimination
It is determined whether or not a saturated pixel is included in 8 sample points. If even one of the following expressions is not satisfied, it is determined that there is a saturated pixel, and this sample point is not used, and the process returns to step 2 Extract sampling points.
[0031]
Ma1 <BrightThresholdMagenta
Ma2 <BrightThresholdMagenta
Gr1 <BrightThresholdGreen
Gr2 <BrightThresholdGreen
Cy1 <BrightThresholdCyan
Cy2 <BrightThresholdCyan
Ye1 <BrightThresholdYellow
Ye2 <BrightThresholdYellow
3.2 Noise discrimination
If the S / N of the 8 sample points is poor, that is, if the following equation is not satisfied, it is determined that the pixel is a noise pixel, and this sample point is not used, and the process returns to Step 2.
[0032]
(Ma1 + Ma2 + Gr1 + Gr2 + Cy1 + Cy2 + Ye1 + Ye2) / 8> DarkTHreshold
3.3 Edge discrimination
If the following four formulas are satisfied in the 8 pixels of the sample point, the process proceeds to step 4. If any of the 8 points is not satisfied, it is determined that the sample point includes an edge. Return.
[0033]
EdgeThresholdMagenta> | Ma1-Ma2 |
EdgeThresholdGreen> | Gr1-Gr2 |
EdgeThresholdCyan> | Cy1-Cy2 |
EdgeThreshold Yellow> | Ye1-Ye2 |
(Step 4)
At the sample point, the value of the following equation is obtained.
[0034]
X1 = (Ye1-Cy1) / Cy1 (1)
Y1 = (Ma1-Gr1) / Gr1 (2)
X2 = (Ye2-Cy2) / Cy2 (3)
Y2 = (Ma2-Gr2) / Gr2 (4)
(Step 5)
When (Ye-Cy) / Cy is on the X axis and (Ma-Gr) / Gr is on the Y axis, and equations (1) to (4) are within a predetermined white area provided on the XY axis, that is, If the conditional expression of
a <X1 <b, c <Y1 <d and a <X2 <b, c <Y2 <d (5)
The sample point is regarded as valid as data for setting the WB, and the process proceeds to step 6, and if the expression (5) is not satisfied, the process proceeds to step 8.
[0035]
(Step 6)
6.1
First, at the same sample point, the average value of the XY axis values of the sample point in the WB coordinates and the luminance value are obtained using the following equations.
[0036]
AverageX = (X1 + X2) / 2
AverageY = (Y1 + Y2) / 2
AverageBrightness = (Ma1 + Ma2 + Gr1 + Gr2 + Cy1 + Cy2 + Ye1 + Ye2) / 8
6.2
When the same sample point is the first sample point regarded as the WB setting valid data, a sample point group having values as shown in FIG. 7 as parameters is created, and the values obtained in step 6.1 and Substitute the pixel value of the point.
[0037]
GpX = AverageX
GpY = AverageY
GpBrightness = AverageBrightness
GpMa1 = Ma1
GpMa2 = Ma2
GpGr1 = Gr1
GpGr2 = Gr2
GpCy1 = Cy1
GpCy2 = Cy2
GpYe1 = Ye1
GpYe2 = Ye2
GpNumber = 1
GpWeight = 1
6.3
Further, when the sample point is not the first sample point considered as the WB setting valid data, when the following conditional expression is satisfied using the values of GpX, GpY, and GpBrightness of the existing sample point group, The sample point is determined to be included in the sample point group, and is included in the sample point group.
[0038]

If the sample points cannot be included in all the sample point groups, a new sample point group based on the sample points is created. (Same processing as step 6.2)
(Step 7)
When the processing of step 6 is completed for all the sample points, the true white group is searched from one or more sample point groups created in step 6. I don't know if it's white. Therefore, assuming that the one with high luminance is white, the luminance information GpBrightness of the plurality of sample point groups is used to weight the one with high luminance. Weighting is performed by the following formula. Further, whether or not to perform this weighting process can be set in advance by the user.
[0039]

8.1
If the white point (X1, Y1) (X2, Y2) represented in the coordinates obtained in step 4 is not within the predetermined range and is determined by step 5 (5), the same coordinate point as shown in FIG. Is moved to a predetermined range frame, and Ma1 ′, Ma2 ′, Ye1 ′, and Ye2 ′ are newly obtained from coordinates (X ′, Y ′) on the range frame by using the following expression.
[0040]
Ma1 '= (1 + Y1') * Gr1
Ma2 '= (1 + Y2') * Gr2
Ye1 '= (1 + X1') * Cy1
Ye2 '= (1 + X2') * Cy2
8.2
However, the coordinate point is moved to a coordinate on a predetermined range frame closest to the coordinate point as shown in the figure. This coordinate movement processing is called color clip processing. Let SN2 be the total number of sample points clipped by this color, and let Ma1 ', Ma2', Gr1 ', Gr2', Cy1 ', Cy2', Ye1 ', Ye2' be the integrated values obtained by the color clip.
[0041]
(Step 9)
9.1
For all the sample point groups obtained in Steps 6 and 7, integral values (SMa1, SMa2, SGr1, SGr2, SCy1, SCy2, SYe1, SYe2) within the white discrimination range are obtained using the following formula. .
[0042]
SMa1 = SMa1 + GpMa1 * GpWeight
SMa2 = SMa2 + GpMa2 * GpWeight
SGr1 = SGr1 + GpGr1 * GpWeight
SGr2 = SGr2 + GpGr2 * GpWeight
SCy1 = SCy1 + GpCy1 * GpWeight
SCy2 = SCy2 + GpCy2 * GpWeight
SYe1 = SYe1 + GpYe1 * GpWeight
SYe2 = SYe2 + GpYe2 * GpWeight
9.2
At the same time, the number of sample points SN1 regarded as white is obtained.
[0043]
SN1 = SN1 + GpNumber
(Step 10)
If the number of samples (SN1 + SN2) is not zero or greater than a predetermined value, a white balance adjustment value of a predetermined color temperature (for example, 5000K) is used as white balance adjustment data.
[0044]
(Step 11)
As an average brightness level when shooting white,
SY = (SMa1 + SMa2 + SGr1 + SGr2 + SCy1 + SCy2 + SYe1 + SYe2) / 8
And the ratio of the integrated value of each color to the average luminance level is obtained.
[0045]

As the average brightness level when clipping
SY '= (SMa1' + SMa2 '+ SGr1' + SGr2 '+ SCy1' + SCy2 '+ SYe1' + SYe2 ') / 8
And the ratio of the integrated value of each color to the average luminance level is obtained.
[0046]

The white balance adjustment data (wmg1, wg1, wcy1, wye1, wmg2) is obtained from the ratio of the integral values of the respective colors obtained in steps 11 and 12, the integration sample number SN1 within the white discrimination range and the integration sample number SN2 by the color clip. , Wg2, wcy2, and wye2).
[0047]
For example,

Apply the following process. These values are stored as white balance adjustment data.
[0048]
The white balance can be obtained by applying the white balance adjustment data obtained by the above processing to the signal value for each pixel obtained from the image sensor.
[0049]
As described above, coordinates for white balance are created using the signal values from the image sensor, and the white points are weighted on the assumption that the luminance value is relatively higher than the sample points that have entered the white area at the coordinates. Since the integration processing is performed at the sample point after the image is processed, even if there is little white in the image, it is possible to avoid the white balance from being greatly affected by other colors due to weighting. It is.
[0050]
In addition, the image pickup device includes at least one means for blocking the output signal from the image pickup device for each filter array and a means for thinning a plurality of blocks arbitrarily or in a staggered manner. It is not necessary to perform calculation for these pixels, and the processing speed can be increased.
[0051]
Further, means for determining whether or not there is a saturated pixel in the block divided by the dividing means, means for determining whether or not there is a noise pixel, and whether or not an edge of the image is included in the block. Since the appropriate determination means including at least one of the determination means is provided, it can be determined whether or not the reference block is a block suitable for obtaining the color temperature of the subject.
[0052]
In addition, on the color filter array, light of a filter of another color adjacent to the signal value of a pixel of a certain color filter leaks, and as a result, the values of pixels of the same color in the same block of the same subject are different from each other. It is possible to avoid the problem that the color temperature of the subject due to the image cannot be determined by photographing a white board and applying a certain coefficient for each color filter so that the signal values of the same color pixels in the same block are the same. It becomes possible.
[0053]
Also, by changing the white discrimination range based on information such as the illuminance information of the subject, flicker information, and the presence / absence of flash light, the green component correction when the light source is a fluorescent lamp, white balance during flash, daytime synchronization It becomes possible to obtain a more accurate white balance during shooting.
[0054]
Also, instead of (R−Y) / Y, (B−Y) / Y, (Ma−Gr) / Gr or (Ma−Gr) / Ma and (Ye−Cy) / Cy or (Ye−Cy) / The color temperature can be detected directly from the readout signal of the image sensor having the color filter of (Ma, Gr, Cy, Ye) by making coordinates with Ye and detecting the color temperature. Therefore, the exposure and signal processing for this can be omitted, and the color temperature can be detected easily and accurately. Even when shooting a subject containing only a small amount of white, white coordinates can be determined by giving coordinates within the white determination range in the form of (Ma-Gr) / Gr = a, (Ye-Cy) / Cy = b. The image sensor output can be replaced by simple processing in the form of Ma ′ = (1 + a) * Gr, Ye ′ = (1 + b) * Cy within the range, and the white balance does not greatly deviate even under the shooting conditions. Balance adjustment is possible.
[0055]
As described above, although the case where the filter has four colors is considered in the present embodiment, it is obvious that the white balance adjustment data can be obtained by the same operation even in the case of three colors.
[0056]
(Example 2)
FIG. 8 is a diagram showing a signal processing flow of the electronic camera according to the second embodiment of the present invention. Since the image sensor in the present embodiment performs field readout, the output from the image sensor is read by adding two pixels in the vertical direction as shown in FIG. In this figure,
Wb = Ma + Cy
Gr = G + Ye
Gb = Cy + G
Wr = Ye + Ma
It is. If it is assumed that the color filter is changed from (Ma, G, Cy, Ye) to (Wb, Gr, Gb, Wr), the same processing as the frame reading is performed.
[0057]
First, the black level is adjusted using the integrated value of each filter output in the optical black region. Next, white balance processing is performed so that the output gains of Wb, Gr, Gb, and Wr at the white point are the same.
[0058]
In order to create the luminance signal (Y), aperture correction is performed after a horizontal low-pass filter is applied to remove moire caused by the color filter. Here, a high-pass filter is applied horizontally and vertically, and the gain is adjusted. The peak is increased when the aperture signal has a small amplitude, and the peak is decreased when the aperture signal is large. To Peak processing is performed, horizontal and vertical are added, and further gain is applied to the luminance component (Yn).
[0059]
In order to generate the color difference signals (R−Y, B−Y), first, the signals of the four colors are synchronized by the synchronization circuit, and pixel interpolation is performed so that the four color signals are assigned to the entire area of the imaging surface. Next, the WbGrGbWr signal is converted into an RGB signal using a 4 × 3 matrix. At this time, the matrix is used such that the color temperature of the subject is determined from the white balance information and the color reproduction at the color temperature is the best. Next, the RGB signals are converted into RY and BY signals, a low-pass filter for moire reduction is applied, and saturation achromatic processing is performed with reference to the Y signals.
[0060]
The luminance signal (Y) and the color difference signals (R−Y, B−Y) produced in this way are converted into RGB signals, subjected to gamma correction processing, and then recorded.
[0061]
Next, white balance processing, which is the main point of the present invention, will be described in detail. When the CCD complementary color filters are arranged as shown in FIG. 11A, the entire arrangement is formed by repeating this unit block with the 8-pixel arrangement shown in the figure as a unit block. Here, in order to perform field reading, a signal as shown in FIG. 11B is read in one field.
[0062]
Hereinafter, the white balance process will be described with reference to the flowcharts of FIGS.
[0063]
(Step 1) Setting the white discrimination range
Take a picture of a white board in advance at various color temperatures.
((Wr−Gb) − (Wb−Gr)) / (Wr + Gb) on the X axis
((Wr−Gb) + (Wb−Gr)) / (Wb + Gr) on the Y axis
A plot is shown in FIG. As in the first embodiment, the X-axis width is changed depending on the illuminance of the subject and the presence or absence of flicker, and the Y-axis width is changed depending on the presence or absence of the flash and the illuminance of the subject.
[0064]
(Step 2) Sample point extraction
A unit of four pixels (Wb, Gb, Gr, Wr) after addition as shown in FIG. 11 is called one sample point, and a new sampling point is selected.
[0065]
(Step3)
3.1 Saturation discrimination
It is determined whether or not a saturated pixel is included in the four sample points. If even one of the following expressions is not satisfied, it is determined that there is a saturated pixel, the present sample point is not used, and the process returns to step 2.
[0066]
Wb <BrightnessThreshold Wb
Gb <BrightnessThresholdGb
Gr <BrightnessThresholdGr
Wr <BrightnessThresholdThresholdWr
3.2 Noise discrimination
If four sample points have poor S / N, that is, if the following equation is not satisfied, it is determined that the pixel is a noise pixel, and this sample point is not used, and the process returns to step 2.
[0067]
(Wb + Gb + Gr + Wr) / 4> DarkThreshold
(Step 4)
At the sample point, the value of the following equation is obtained.
[0068]
X1 = ((Wr−Gb) − (Wb−Gr)) / (Wr + Gb) (1)
Y1 = ((Wr−Gb) + (Wb−Gr)) / (Wb + Gr) (2)
(Step 5)
Taking ((Wr−Gb) − (Wb−Gr)) / (Wr + Gb) as the X axis and ((Wr−Gb) + (Wb−Gr)) / (Wb + Gr) as the Y axis, equations (1) and (2) Is within a predetermined area provided on the XY axis, that is, when the following conditional expression is satisfied:
a <X1 <b, c <Y1 <d (3)
The sample point is regarded as valid as data for setting the WB, and the process proceeds to step 4, and if the expression (3) is not satisfied, the process proceeds to step 8.
[0069]
(Step 6)
6.1
First, at the same sample point, the average value of the XY axis values of the sample point in the WB coordinates and the luminance value are obtained using the following equations.
[0070]
AverageX = X1
AverageY = Y1
AverageBrightness = (Wb + Gr + Gb + Wr) / 2
6.2
When the same sample point is the first sample point regarded as the WB setting valid data, a sample point group having values as shown in FIG. 7 as parameters is created, and the values obtained in step 6.1 and Substitute the pixel value of the point.
[0071]
GpX = AverageX
GpY = AverageY
GpBrightness = AverageBrightness
GpWb = Wb
GpGr = Gr
GpGb = Gb
GpWr = Wr
GpNumber = 1
GpWeight = 1
6.3
Further, when the sample point is not the first sample point considered as the WB setting valid data, when the following conditional expression is satisfied using the values of GpX, GpY, and GpBrightness of the existing sample point group, The sample point is determined to be included in the sample point group, and is included in the sample point group.
[0072]

If the sample points cannot be included in all the sample point groups, a new sample point group based on the sample points is created. (Same processing as step 6.2)
(Step 7)
When the processing of step 6 is completed for all the sample points, the true white group is searched from one or more sample point groups created in step 6. I don't know if it's white. Therefore, assuming that the one with high luminance is white, the luminance information GpBrightness of the plurality of sample point groups is used to weight the one with high luminance. Weighting is performed by the following formula. Further, whether or not to perform this weighting process can be set in advance by the user.
[0073]

8.1
If the white point (X1, Y1) (X2, Y2) represented in the coordinates obtained in step 4 is not within the predetermined range and is determined by step 5 (3), the coordinate point is placed on the predetermined range frame. Move and recalculate WB ′ and Wr ′.
[0074]
8.2
Let SN2 be the total number of sample points clipped by this color, and let Wb ', Gr', Gb ', Wr' be the integral values obtained by the color clip.
[0075]
(Step 9)
9.1
For all the sample point groups obtained in Steps 6 and 7, integral values (SWb, SGr, SGb, SWr) within the white discrimination range are obtained using the following equation.
[0076]
SWb = SWb + GpWb * GpWeight
SGr = SGr + GpGr * GpWeight
SGb = SGb + GpGb * GpWeight
SWr = SWr + GpWr * GpWeight
9.2
At the same time, the number of sample points SN1 regarded as white is obtained.
[0077]
SN1 = SN1 + GpNumber
(Step 10)
If the number of samples (SN1 + SN2) is not zero or greater than a predetermined value, a white balance adjustment value of a predetermined color temperature (for example, 5000K) is used as white balance adjustment data.
[0078]
(Step 11)
As an average brightness level when shooting white,
SY = (SWb + SGr + SGb + SWr) / 4
And the ratio of the integrated value of each color to the average luminance level is obtained.
[0079]
gwb = SY / (2 * SWb)
ggr = SY / (2 * SGr)
ggb = SY / (2 * SGb)
gwr = SY / (2 * SWr)
(Step 12)
As the average brightness level when clipping
SY '= (SWb' + SGr '+ SGb' + SWr ') / 4
And the ratio of the integrated value of each color to the average luminance level is obtained.
[0080]
gwb '= SY' / (2 * SWb ')
ggr '= SY' / (2 * SGr ')
ggb '= SY' / (2 * SGb ')
gwr '= SY' / (2 * SWr ')
(Step 13)
White balance adjustment data (wwb, wgr, wgb, wwr) is obtained from the ratio of the integrated values of the respective colors obtained in steps 11 and 12, the integrated sample number SN1 within the white discrimination range, and the integrated sample number SN2 by the color clip. create.
[0081]
For example,

Apply the following process. These values are stored as white balance adjustment data.
[0082]
The white balance can be obtained by applying the white balance adjustment data obtained by the above processing to the signal value for each pixel obtained from the image sensor. As described above, although the case where the filter has four colors is considered in the present embodiment, it is obvious that the white balance adjustment data can be obtained by the same operation even in the case of three colors.
[0083]
(Example 3)
FIG. 14 is a part of a white balance processing flowchart according to the third embodiment of the present invention, and corresponds to step 6 in FIG. This is a part for weighting the group after the white balance group is created, but this embodiment is characterized in that illuminance information at the time of photographing is used for this weighting. The illuminance information is, for example, an EV value and information on the flash OnOff.
[0084]
When the EV value is obtained from the camera side and the EV value is large, the white coordinate range is limited as shown in (a) of FIG. 15 because it is often taken outside (sunlight). On the contrary, the EV value is limited to sunset or artificial light, and the white coordinate range is limited as shown in FIG. When the flash is on, the white coordinate range is limited as shown in FIG. Here, all sample point groups are weighted as follows. That is, the weight of the white balance group in the limited coordinate range is increased.
[0085]

By performing such weighting, a more preferable white balance can be achieved even when the brightness of white is low, and even when a point that does not fall within the limited coordinate range is white, white group selection by weighting can be performed. The white balance is not greatly changed because it is done.
[0086]
The weighting in this embodiment can be used for step 7 in the second embodiment or in combination with the weighting method in the first and second embodiments.
[0087]
【The invention's effect】
  As described above, according to the present invention, an imaging device capable of satisfactorily adjusting white balance.PlaceCan be provided.
  That is, in the present invention, since it is determined whether the reference block is suitable for the white determination based on whether or not the reference block thinned out to any number of the entire screen includes the edge of the image, for example, a small number Even from a block of pixels, the color temperature of the subject can be determined accurately and at high speed.
[Brief description of the drawings]
FIG. 1 is a flowchart of white balance processing according to a first embodiment.
FIG. 2 is a flowchart of white balance processing according to the first embodiment.
FIG. 3 is a flowchart of white balance processing according to the first embodiment;
FIG. 4 is a signal processing block diagram of an electronic camera using the WB detection circuit of the first embodiment.
FIG. 5 is an explanatory diagram showing a color filter array pattern of an image sensor.
FIG. 6 is an explanatory diagram showing white balance coordinates used for white balance processing.
FIG. 7 is an explanatory diagram showing parameters of a sample point group.
FIG. 8 is a signal processing block diagram of an electronic camera using a WB detection circuit according to a second embodiment.
FIG. 9 is a flowchart of white balance processing according to the second embodiment.
FIG. 10 is a flowchart of white balance processing according to the second embodiment.
FIG. 11 is an explanatory diagram illustrating a reading method of the image sensor according to the second embodiment.
FIG. 12 is an explanatory diagram showing a method for determining a white discrimination curve range width;
FIG. 13 is an explanatory diagram showing white discrimination range coordinates in the second embodiment.
FIG. 14 is a flowchart illustrating a part of white balance processing according to the third embodiment;
FIG. 15 is an explanatory diagram of determination of a white coordinate range according to the third embodiment.
FIG. 16 is a block diagram of a conventional digital electronic camera.
FIG. 17 is a block diagram of a conventional example.
FIG. 18 is an explanatory diagram of white balance control of a conventional example.

Claims (2)

In an imaging device having a white balance adjustment function,
An image sensor having a plurality of color filters having different spectral characteristics;
The output signal from the image sensor is divided into a plurality of blocks based on the unit arrangement in the arrangement of the plurality of color filters, the output signals of some of the blocks are thinned out, and the image by the output signal of each block after thinning out Appropriate determination means for determining whether or not the output signal of the block can be used for the white balance adjustment based on the edge state of
Imaging apparatus characterized by comprising a. The imaging device according to claim 1,
An image pickup apparatus characterized in that a state of an edge of an image by an output signal of each block is whether or not a difference between output signal values of filters of the same color in each block is smaller than a predetermined value .

Images