JP3989788B2 - Code amount control apparatus and program - Google Patents

Description

【００４８】
上式（１）中、ｚは、ビット切り捨て点（bit truncation point）；ｏｙ_i ^K[i,j]［ｊ］は、Ｋ［ｉ，ｊ］番目のビットプレーンで逆量子化されたコードブロックのｊ番目のサンプル値（係数値）；ｙ_i［ｊ］は、当該コードブロックのｊ番目のサンプル値（係数値）；Ｇ_b[i]は、サブバンドｂ［ｉ］に対応する合成フィルタ係数のノルムの二乗であって、当該サブバンドｂに依存する歪モデルの重み係数を示している。尚、説明の便宜上、上式（１）に示した記号の表記法は、前記参考文献Ａでのそれとは若干異なる。
【００４９】
レート・歪み最適化では、この歪測度Ｄ_i ^(z)のサブバンドｂ［ｉ］における総和量を最小にするような最適化処理が行われる。サブバンドｂの重み係数Ｇ_bは、画像の歪みを低減させるための重み付けを表している。
【００５０】
サブバンドｂの重み係数Ｇ_bは、次式（２）に従って算出される。
【００５１】
【数２】

【００５２】
ここで、上式（２）中、ｓ_b［ｎ］は、サブバンドｂの１次元合成フィルタ係数を示している。また、記号||x||は、ベクトルxに関するノルムを示す。
【００５３】
前記参考文献Ａに記載される数式（４．３９）と（４．４０）によれば、分解レベル１における低域成分Ｌ１の１次元合成フィルタ係数ｓ_L[1]［ｎ］と、同分解レベルにおける高域成分Ｈ１の１次元合成フィルタ係数ｓ_H[1]［ｎ］とは、次式（３）に従って算出される。
【００５４】
【数３】

【００５５】
ここで、上式（３）中、ｇ₀［ｎ］は、画像信号を帯域分割する順変換フィルタのローパス・フィルタ係数、ｇ₁［ｎ］は、そのハイパス・フィルタ係数をそれぞれ示している。
【００５６】
また、分解レベルｄ（ｄ＝１，２，…，Ｄ）における低域成分Ｌｄの１次元合成フィルタ係数ｓ_L[d]［ｎ］と、同分解レベルにおける高域成分Ｈｄの１次元合成フィルタ係数ｓ_H[d]［ｎ］とは、次式（４）に従って算出される。
【００５７】
【数４】

【００５８】
そして、分解レベルｄにおける低域成分Ｌｄの１次元合成フィルタ係数のノルムの二乗は、次式（５）に従って算出される。
【００５９】
【数５】

【００６０】
高域成分の１次元合成フィルタ係数のノルムの二乗も、上式（５）と同様にして算出することができる。
【００６１】
次に、分解レベルｄ（ｄ＝１，２，…，Ｄ；Ｄは整数）における帯域成分ＬＬＤ，ＨＬｄ，ＬＨｄ，ＨＨｄの２次元合成フィルタ係数は、上記１次元合成フィルタ係数の積で表現することができ、帯域成分ｂの２次元の重み係数Ｇ_bも、１次元の重み係数の積で表現することができる。具体的には、２次元合成フィルタ係数と２次元の重み係数とは、次式（６）に従って算出される。
【００６２】
【数６】

【００６３】
上式（６）中、添字ＬＬ［Ｄ］はサブバンドＬＬＤを示し，ＨＬ［ｄ］，ＬＨ［ｄ］およびＨＨ［ｄ］はそれぞれサブバンドＨＬｄ，ＬＨｄおよびＨＨｄを表している。
【００６４】
重み係数Ｇ_bの平方根がノルムである。以下の表１〜表４に、２次元の重み係数Ｇ_bに関する計算結果を示す。表１に、（９，７）フィルタ（９×７タップのフィルタ）の各帯域成分のノルムの二乗の数値を、表２には、表１に対応するノルムの数値をそれぞれ示す。また、表３に、（５，３）フィルタ（５×３タップのフィルタ）の各帯域成分のノルムの二乗の数値を、表４には、表３に対応するノルムの数値をそれぞれ示す。
【００６５】
【表１】

【００６６】
【表２】

【００６７】
【表３】

【００６８】
【表４】

【００６９】
更に、分解レベル１における低域成分ＬＬ１のノルムをαで表すとき、このノルムαを用いて、各帯域成分について図６に示すような値を設定する。図６に示す２次元画像２７は、オクターブ分割方式に従って帯域分割された２次元画像１２０を示す図である。分解レベルｎ（ｎ：１以上の整数）における帯域成分ＨＨｎの設定値は「２^n-3×α」、帯域成分ＨＬｎおよびＬＨｎの設定値は「２^n-2×α」、帯域成分ＬＬｎの設定値は「２^n-1×α」にそれぞれ設定される。従って、例えば、帯域成分ＬＨ１の設定値は「２^-1×α」に設定されている。
【００７０】
上記設定値と、表２と表４に示したノルムの数値とを比較すれば、両者は概ね近似する。例えば、表２の場合（α=1.96591）、図６に示す各帯域成分の「設定値（対応する帯域成分）」は、約０．４９（ＨＨ１）、約０．９８（ＨＬ１，ＬＨ１）、約１．９６（ＨＬ２，ＬＨ２，ＨＨ３）、約３．９３（ＨＬ３，ＬＨ３）、約７．８６（ＬＬ３）となり、これら設定値は、表２に示したノルムの数値と近似していることが分かる。
【００７１】
また、図６において、帯域成分ＬＬ１のノルムをα＝２に丸め込み、各帯域成分の設定値を１ビット左シフトした値、すなわち、全ての設定値に２¹を乗算した２の巾乗値の指数は、図３に示した優先度の値に一致することが分かる。よって、第１実施例のように各帯域成分に優先度を設定することは、近似的に、レート・歪み最適化で使用するフィルタのノルム（重み係数の平方根）を各帯域成分のサンプル値（変換係数値）に乗算することに等しい。従って、本実施例の優先度は画像の歪みを低減させ得るように設定されるものである。
【００７２】
優先度設定処理（第２実施例）．
次に、優先度設定方法の第２実施例について説明する。本実施例では、各帯域成分の上記重み係数Ｇ_bの平方根であるノルムを、最も高い分解レベルにおける最低域成分ＬＬのノルムで除算した値を２の巾乗値に丸め込み、その２の巾乗値の指数の絶対値を、優先度として設定する。具体的には、最も高い分解レベルｎの最低域成分ＬＬｎのノルムをαとし、その他の帯域成分のノルムをｘとし、２の巾乗に丸め込む変数ｙに関する関数をR［ｙ］とし、変数ｙの２の巾乗２^mの指数ｍを算出する関数をｍ＝Ｉ［２^m］とし、変数ｙに関する絶対値を｜ｙ｜とするとき、優先度ｐは、ｐ＝｜Ｉ［Ｒ［ｘ／α］］｜、に従って算出される。
【００７３】
以下の表５に、上記表２に示した（９，７）フィルタのノルムを用いて算出した優先度を示す。ここで、最も高い分解レベルは５であり、α＝３３．９２４９３、である。また、図７に、表５に示した優先度を記した２次元画像２８を示す帯域分割図を示す。尚、表中の「×」は、当該帯域成分の優先度は計算されていないことを意味する。
【００７４】
【表５】

【００７５】
また、以下の表６に、上記表４に示した（５，３）フィルタのノルムを用いて算出した優先度を示す。
【００７６】
【表６】

【００７７】
上記第１実施例では、各帯域成分の変換係数を優先度のビット数だけ左シフトさせて優先度を設定していたが、本第２実施例では、各帯域成分の変換係数を優先度のビット数だけ右シフトさせる処理が実行される。但し、変換係数のビット長を拡大させるように右ビットシフト処理が実行される。図８は、図７に示す優先度のビット数だけ右シフトされた帯域成分の変換係数２９，２９，…を示す模式図である。
【００７８】
優先度設定処理（第３実施例）．
次に、人間の視覚特性を考慮した第３実施例に係る優先度設定方法について説明する。数百万画素程度の高解像度の画像について上記第２実施例で示した優先度を適用した場合、復号画像の画質は客観評価では良いが、人間の視覚評価では必ずしも良いとは限らない。そこで、本実施例の優先度設定方法は、人間の視覚特性を考慮した重み付けをされた優先度を採用するものである。これにより、高い表示画質の圧縮画像を生成することが可能になる。
【００７９】
前記参考文献ＡのChapter 16には、ＣＳＦ（human visual system Contrast Sensitivity Function）に基づいた重み付けＭＳＥ（Weighted Mean Squared Error；WMSE）が記載されている。この記載によれば、人間の視覚評価を改善するために、上式（１）を次式（７）に修正するのが望ましい。
【００８０】
【数７】

【００８１】
ここで、上式（７）中、Ｗ_b[i] ^csfは、サブバンドｂ［ｉ］の"energy weighting factor"と呼ばれており、Ｗ_b[i] ^csfの推奨数値は、「ISO/IEC JTC 1/SC 29/WG1(ITU-T SG8) N2406, "JPEG 2000 Part 1 FDIS (includes COR 1, COR 2, and DCOR3)," 4 December 2001」の文献（以下、参考文献Ｂと呼ぶ。）に記載されている。図９〜図１１に、参考文献Ｂに記載される"energy weighting factor"の数値を示す。
【００８２】
図９〜図１１中の"level"および "Lev"は分解レベルを、"Comp"は輝度成分Ｙと色差成分Ｃｂ,Ｃｒをそれぞれ示しており、"Viewing distance（視距離）"が1000，1700，2000，3000，4000の例が示されている。また、"Viewing distance 1000", "Viewing distance 1700", "Viewing distance 2000", "Viewing distance 3000", "Viewing distance 4000"は、それぞれ、100dpi，170dpi，200dpi，300dpi，400dpiのディスプレイまたは印刷物を１０インチ離れて見たときの視距離を意味する。
【００８３】
図９〜図１１に示す数値を用いて、上式（７）の重み付け係数の平方根（Ｗ_b[i] ^csf・Ｇ_b[i]）^1/2を計算した。その計算結果を、以下の表７〜表１８に示す。表７〜表９は、図９に示す数値を用いて計算した（９，７）フィルタの白黒用数値、表１０〜表１２は、図１０と図１１に示す数値を用いて計算した（９，７）フィルタのカラー用数値を、表１３〜表１５は、図９に示す数値を用いて計算した（５，３）フィルタの白黒用数値を、表１６〜表１８は、図１０と図１１に示す数値を用いて計算した（５，３）フィルタのカラー用数値をそれぞれ示している。
【００８４】
【表７】

【００８５】
【表８】

【００８６】
【表９】

【００８７】
【表１０】

【００８８】
【表１１】

【００８９】
【表１２】

【００９０】
【表１３】

【００９１】
【表１４】

【００９２】
【表１５】

【００９３】
【表１６】

【００９４】
【表１７】

【００９５】
【表１８】

【００９６】
次に、上記表７〜表１８に示す数値を用いて、上記第２実施例で述べたのと同じ手順で各帯域成分の優先度を算出した。すなわち、最も高い分解レベルｎの最低域成分ＬＬｎの数値をαとし、その他の帯域成分の数値をｘとし、２の巾乗に丸め込む変数ｙに関する関数をR［ｙ］とし、変数ｙの２の巾乗２^mの指数ｍを算出する関数をｍ＝Ｉ［２^m］とし、変数ｙに関する絶対値を｜ｙ｜とするとき、優先度ｐは、ｐ＝｜Ｉ［Ｒ［ｘ／α］］｜、に従って算出される。
【００９７】
優先度の値を、以下の表１９〜表３０に示す。表１９，表２０，表２１，表２２，表２３，表２４，表２５，表２６，表２７，表２８，表２９および表３０の優先度は、それぞれ、上記した表７，表８，表９，表１０，表１１，表１２，表１３，表１４，表１５，表１６，表１７および表１８の数値を用いて算出されたものである。
【００９８】
【表１９】

【００９９】
【表２０】

【０１００】
【表２１】

【０１０１】
【表２２】

【０１０２】
【表２３】

【０１０３】
【表２４】

【０１０４】
【表２５】

【０１０５】
【表２６】

【０１０６】
【表２７】

【０１０７】
【表２８】

【０１０８】
【表２９】

【０１０９】
【表３０】

【０１１０】
本実施例では、上記第２実施例と同じように、以上の表１９〜表３０に示す優先度のビット数だけ右シフトさせることで、各帯域成分の変換係数に対して優先度が設定される。これにより、人間の視覚特性を考慮した優先度を設定できる。
【０１１１】
画質制御処理．
次に、図２に示した画質制御部１０の構成と処理内容について説明する。図１２は、この画質制御部１０の概略構成を示す機能ブロック図である。
【０１１２】
この画質制御部１０は、目標画質（高画質，標準画質，低画質など）に基づいて、複数の画質パラメータ群から当該目標画質に適した画質パラメータＱＰを選択して出力する画質パラメータ選択部３１と、符号化対象を決定する符号化対象判定部３０とを備えている。符号化対象判定部３０は、優先度テーブル６から取得した優先度データＰＳ１に従って、入力ビットストリームに含まれる圧縮画像データの各帯域成分に対して上述の優先度を設定する。また符号化対象判定部３０は、設定した優先度に従って、前記画質パラメータＱＰで指定される目標画質に合わせて符号化対象を決定し、走査領域情報ＳＡを生成出力する。
【０１１３】
以下、符号化対象判定部３０における符号化対象の決定方法について説明する。図１３は、優先度に応じてビットシフトされた変換係数３３，３３，…を例示する模式図である。各変換係数３３は優先度に応じてビットシフトされている。また、変換係数３３の各ビットに付した番号０，１，…，１０は、当該ビットが属するビットプレーンの番号を示している。ここで、ＬＳＢ番号＝０，ＭＳＢ番号＝１０、である。
【０１１４】
符号化対象判定部３０は、画質パラメータＱＰに従って符号化終了ライン３２を設定し、当該符号化終了ライン３２よりも上位ビットを符号化対象に決定し、そのライン３２よりも下位ビットを符号化対象から外すように走査領域情報ＳＡを生成する。これにより符号化対象を効率的に選別することが可能になる。この結果、走査領域情報ＳＡを受けた符号量制御部１１は、各コードブロックにおいて、符号化終了ライン３２よりも上位のビットプレーンのみを走査し、そのライン３２よりも下位のビットプレーンを切り捨てることになる。
【０１１５】
符号化対象判定部３０は、更に、画質パラメータＱＰに従って、符号化パス単位で符号化対象を決定することができる。画質パラメータＱＰは、符号化対象のビットプレーンの制限と、符号化対象の符号化パス（ＣＬパス，ＳＩＧパスおよびＭＲパス）の制限とを示すパラメータ群を含んでいる。以下の表３１に、２０４８×２５６０画素の解像度をもつ画像に適した画質パラメータＱＰを例示する。尚、最低域のサブバンドの解像度を１２８×１２８画素よりも小さくする必要があるため、５以上の分解レベルが必要である。
【０１１６】
【表３１】

【０１１７】
表３１において「ビットプレーン数」は、図１３に示した符号化終了ライン３２よりも下位ビットの切り捨て対象のビットプレーンの数を、「パス名」は、符号化対象の中の最終符号化パスを、「最大パス数」は、符号化対象の符号化パス数の上限をそれぞれ表している。
【０１１８】
図１３と表３１を適用した場合の処理例を以下に説明する。図１４に、帯域成分ＬＬ５の変換係数３３として"00011010111₂=215₁₀"を例示する（Y₂は２進値Yを、X₁₀は１０進値Xを表すものとする）。表３１に示す通り、帯域成分ＬＬ５における最終符号化パスはＣＬパス、最大パス数は１７に制限されている。
【０１１９】
図１４に示す変換係数の７番目ビットは、ＳＩＧパスまたはＣＬパスに属するようにコンテクスト判定がなされている。８番目〜１０番目の上位ビットは、０ビットのみで構成されるビットプレーンに属する場合はタグツリー（Tag tree）と称する方式で符号化されており、既に符号化パスが開始している場合はＳＩＧパスまたはＣＬパスで符号化されている。７番目ビットが符号化開始パス（ＣＬパス）に属する場合、６番目ビットを含む下位ビットは、ＭＲパスに属するようにコンテクスト判定される。一般に、符号化開始のビットプレーンよりも下位のビットプレーンは、符号化効率の観点から、ＳＩＧパス，ＭＲパスおよびＣＬパスの順番で符号化されている。よって、最大パス数は１７に制限されているため、７番目ビットのＣＬパスから１番目ビットのＳＩＧパス迄の計１７パスが符号化対象になる。但し、１番目ビットはＭＲパスに属するため符号化対象に入らない。従って、下位２ビットは切り捨てられ、切り捨て後の値は"00011010100₂=212₁₀"となる。この値がミッドポイントで逆量子化されれば、"00011010110₂=214₁₀"となる。
【０１２０】
次に、図１５に、帯域成分ＬＬ５の変換係数３３として"00000001111₂=15₁₀"を例示する。変換係数の３番目ビットは、ＳＩＧパスまたはＣＬパスに属する。４番目〜１０番目の上位ビットは、０ビットのみで構成されるビットプレーンに属する場合はタグツリー（Tag tree）で符号化されており、既に符号化パスが開始している場合はＳＩＧパスまたはＣＬパスで符号化されている。３番目ビットが符号化開始パス（ＣＬパス）に属する場合、２番目ビットを含む下位ビットはＭＲパスに属し、３番目ビットのＣＬパスから０番目ビットのＣＬパス迄の計１０パスが符号化対象になる。切り捨て後の値は"00000001111₂=15₁₀"となり、この値が逆量子化されれば、"00000001111₂=15₁₀"となる。
【０１２１】
次に、図１６に、帯域成分ＨＨ２の変換係数３３として"00001011111₂=95₁₀"を例示する。表３１に示す通り、帯域成分ＨＨ２における最終符号化パスはＳＩＧパス、最大パス数は１４に制限されている。また下位３ビットのビットプレーンは切り捨てられる。
【０１２２】
変換係数の６番目ビットは、ＳＩＧパスまたはＣＬパスに属する。７番目〜１０番目の上位ビットは、０ビットのみで構成されるビットプレーンに属する場合はタグツリー（Tag tree）で符号化されており、既に符号化パスが開始している場合はＳＩＧパスまたはＣＬパスで符号化されている。６番目ビットが符号化開始パス（ＣＬパス）に属する場合、５番目ビットを含む下位ビットはＭＲパスに属する。また、３番目ビットプレーンのＳＩＧパス迄しか符号化しないという制限のため、６番目ビットのＣＬパスから４番目ビットのＳＩＧパス迄の８パスが符号化対象になるが、３番目ビットはＭＲパスに属するため符号化対象に入らない。従って、切り捨て後の値は"00001010000₂=80₁₀"となり、この値がミッドポイントで逆量子化されれば、"00001011000₂=88₁₀"となる。
【０１２３】
尚、各ビットプレーンが、ＳＩＧパス，ＭＲパスおよびＣＬパスの順番で符号化されているのは、ＳＩＧパスの歪みに対する符号化効率が最も高いからである。図１７に、各符号化パスにおけるレート・歪み特性を示す。Ｒ−Ｄ曲線中、点Ｐ₁〜Ｐ₂の部分がＳＩＧパス，点Ｐ₂〜Ｐ₃の部分がＭＲパス、点Ｐ₃〜Ｐ₄の部分がＣＬパスを示している。各符号化パスにおけるレート（符号量）に対する歪みの比率ΔＤ_SIG／ΔＲ_SIG，ΔＤ_MR／ΔＲ_MR，ΔＤ_CL／ΔＲ_CLをみれば、ＳＩＧパスにおける曲線勾配が最も急であり、符号化効率が最も高いことが分かる。
【０１２４】
以上のように、本実施形態に係る画質制御処理では、優先度に応じてビットシフトした変換係数に対して、変換係数を符号化対象とするか否かが決定される。符号化対象のみが選択されるため、歪みの少ない高画質の圧縮画像を生成し得るように、符号量を効率良く制御することが可能である。
【０１２５】
符号量制御処理．
次に、図２に示した符号量制御部１１の処理内容について説明する。符号量制御部１１は、入力ビットストリームに含まれる圧縮符号化データの容量の小計を、帯域成分単位，ビットプレーン単位および符号化パス単位で算出する。
【０１２６】
前記符号量制御部１１は、以下に説明する走査順序で並べ替えて生成した符号列から、目標符号量に適合するように切り捨て点（truncation point）を算出する。次に、符号量制御部１１は、その符号列のうち切り捨て点よりも前の符号列を読出すように読出制御信号ＣＳ１をＭＭＵ３に出力する。
【０１２７】
図１８と図１９は、前記走査順序と切り捨て点の一例を説明するための図である。図１８と図１９には、図１３に示したのと同じ規則で、優先度に応じてビットシフトされた変換係数３３，３３，…が表示されている。
【０１２８】
図１８の矢印に示すように、変換係数３３，３３，…は、ビットプレーン単位または符号化パス単位で、優先度の高い順に（上位ビットから下位ビットに向けて）且つ同一の優先度においては高域側から低域側に向けた走査順序で並べ替えられる。一般に、下位のビットプレーンを符号化する程にＭＲパスの割合が増えて圧縮効率が下がる傾向にある。よって、圧縮効率を向上させるために出来るだけ多くのＳＩＧパスを符号化すべく、同一の優先度においては高域側から低域側に向けた走査順序を採用している。
【０１２９】
そして、符号量制御部１１は、実際の符号量（バイト数）が目標符号量（バイト数）以下になる条件を満たすように切り捨て点を決定し、当該切り捨て点以降の符号列に含まれる下位ビットプレーンを切り捨てる。これにより、圧縮符号化データの符号量制御を、各サブバンドに設定した優先度に従って効率的に行うことができる。ここで、図１９に示すように、目標符号量に合わせてサブバンドＨＬ３の２番目ビットプレーンが切り捨て点として決定された場合、矢印で示す部分のビットが切り捨てられることになる。
【０１３０】
図２０は、ビットプレーン単位で並べ替えられた符号列を示す図、図２１は、符号化パス単位で並べ替えられた符号列を示す図である。図２０では、各ビットプレーンに対して、サブバンドを示す符号ＬＬ５，ＨＬ５，…と、ビットプレーン番号１０，９，…とが付されている。サブバンドＨＬ３の２番目ビットプレーンに付されたライン４４以降のビットプレーンが切り捨てられる。
【０１３１】
また、図２１では、各符号化パスに対して、符号化パスの種類を示す符号ＣＬ，ＳＩＧ，ＭＲと、サブバンドを示す符号ＬＬ５，ＨＬ５，…と、ビットプレーン番号１０，９，…とが付されている。サブバンドＨＬ３の２番目ビットプレーンのＭＲパスに付されたライン４４以降のビットプレーンが切り捨てられる。
【０１３２】
以上のように本実施形態に係る符号量制御処理によれば、レート・歪み最適化処理のために各符号化パスにおける歪量を利用せずに済み、リアルタイム性が高く、オーバーヘッドが低い高効率の符号量制御を実現できる。
【０１３３】
レイヤー分割処理．
次に、図２に示したレイヤー分割制御部７の動作を以下に説明する。レイヤー分割制御部７は、優先度テーブル６から取得した優先度データＰＳ２を用いて、入力ビットストリームに含まれる圧縮符号化データを優先度に対応するビット数だけビットシフトした符号列に変換し、その符号列を複数のレイヤー（マルチ・レイヤー）に分割させる制御機能を有している。
【０１３４】
以下、レイヤー分割処理について説明する。ＭＭＵ３は、入力ビットストリームを大容量の記憶装置２に一時的に記憶させる。レイヤー分割制御部７は、ＭＭＵ３から圧縮符号化データのデータ構造情報ＤＳを取得する。次いで、レイヤー分割制御部７は、優先度テーブル６から優先度データＰＳ２を取得し、この優先度データＰＳ２に含まれる優先度に従って、圧縮符号化データの各帯域成分の変換係数を所定ビット数だけシフトさせる。これにより、各帯域成分の変換係数に対して優先度が設定される。優先度の設定方法としては、上記した第１実施例、第２実施例および第３実施例の方法を採用すればよい。
【０１３５】
図２２は、優先度に対応するビット数だけシフトされた変換係数４５，４５，…を例示する模式図である。各帯域成分ＬＬ５〜ＨＨ１の変換係数４５，４５，…は、優先度のビット数だけ右ビットシフト或いは左ビットシフトされている。また、各変換係数４４の各ビットに付した番号０，１，…，１０は、当該ビットが属するビットプレーンの番号を示している。ここで、ＬＳＢ番号＝０，ＭＳＢ番号＝１０、である。
【０１３６】
次に、レイヤー分割制御部７は、レイヤー分割情報に基づき、ビットシフトした符号化データを、ビットプレーン単位或いは符号化パス単位で複数のレイヤーにグループ分けするように分割位置を決定する。レイヤー分割情報としては、シングル・レイヤーとマルチ・レイヤーとの何れかを選択させる選択情報や、ビットプレーン単位または符号化パス単位でレイヤー分割位置を指定する情報などが含まれる。図２２の例では、圧縮符号化データを５枚のレイヤー０〜レイヤー４にビットプレーン単位で分割する分割位置が示されている。そして、レイヤー分割制御部７は、その分割位置に従ってレイヤー単位でデータを読出す旨の読出制御信号ＣＳ２をＭＭＵ３に供給する。ＭＭＵ３は、読出制御信号ＣＳ２に従って、記憶装置２に記憶されたデータＯＤを、上位レイヤーから下位レイヤーにかけて順番に読出して、多重化部５に出力する。
【０１３７】
以上のレイヤー分割処理では、優先度は、各帯域成分を当該優先度に対応するビット数だけビットシフトして設定される。このようにビットシフトした帯域成分を複数のレイヤーに分割することで、レートに対する歪みを低減し得るように、ビットプレーン単位或いは符号化パス単位で複数のレイヤーを効率的に生成することが可能である。従って、必ずしも、上述のレート・歪み最適化を用いてレイヤー分割処理を行う必要は無く、歪みを低減し得るようにリアルタイム性の高いレイヤー分割処理を行うことが可能になる。
【０１３８】
【発明の効果】
以上の如く、本発明の請求項１に係る符号量制御装置および請求項９に係るプログラムによれば、各帯域成分は優先度に対応するビット数だけシフトされ、シフトするビット数に応じて帯域成分の優先度が定まることから、圧縮画像の目標画質に合わせて符号化対象を効率的に指定し、少ない演算量で高速な符号量制御を行うことが可能になる。
【０１３９】
請求項２および請求項１０によれば、人間の視覚評価に適した、高い表示画質を実現するように符号量制御を行うことが可能となる。
【０１４０】
請求項３および請求項１１によれば、目標画質に合わせてビットプレーン単位で符号量を細かく且つ効率的に制御できる。
【０１４１】
請求項４および請求項１２によれば、目標画質に合わせて符号化パス単位で符号量を細かく且つ効率的に制御できる。
【０１４２】
請求項５，６および請求項１３，１４によれば、圧縮符号化データの符号量制御を、当該圧縮符号化データを復号化せずに、各帯域成分に設定した優先度に従って効率的に行うことが可能である。また、必ずしも、レート・歪み最適化を用いなくても、歪みを抑制し得るようにリアルタイム性の高い符号量制御を行うことが可能である。
【０１４３】
請求項７および請求項１５によれば、優先度に応じてビットシフトした帯域成分を複数のレイヤーに分割するため、レートに対する歪みを低減し得るように複数のレイヤーを効率的に生成することが可能である。
【０１４４】
請求項８および請求項１６によれば、人間の視覚評価に適した、高い表示画質を有する圧縮画像を生成することが可能となる。
【図面の簡単な説明】
【図１】本発明の実施形態に係る符号量制御装置の概略構成を示す機能ブロック図である。
【図２】図１に示した符号量制御装置におけるビット切り捨て制御部の概略構成を示す機能ブロック図である。
【図３】オクターブ分割方式に従って帯域分割した２次元画像を示す模式図である。
【図４】ビットシフトによる優先度設定処理を説明するための図である。
【図５】ビットシフトされた変換係数を例示する図である。
【図６】ウェーブレット変換によって帯域分割した２次元画像を示す模式図である。
【図７】ウェーブレット変換によって帯域分割した２次元画像を示す模式図である。
【図８】図７に示す優先度に応じて右ビットシフトされた帯域成分の変換係数を示す模式図である。
【図９】 Energy weighting factorの数値テーブルを示す図である。
【図１０】 Energy weighting factorの数値テーブルを示す図である。
【図１１】 Energy weighting factorの数値テーブルを示す図である。
【図１２】本実施形態に係る画質制御部の概略構成を示す機能ブロック図である。
【図１３】優先度に応じてビットシフトされた変換係数を例示する模式図である。
【図１４】帯域成分ＬＬ５の変換係数の処理例を説明するための図である。
【図１５】帯域成分ＬＬ５の変換係数の処理例を説明するための図である。
【図１６】帯域成分ＨＨ２の変換係数の符号化処理例を説明するための図である。
【図１７】レート・歪み特性の曲線を示す図である。
【図１８】走査順序の一例を説明するための図である。
【図１９】切り捨て点の一例を説明するための図である。
【図２０】ビットプレーン単位で並べ替えられた符号列を示す図である。
【図２１】符号化パス単位で並べ替えられた符号列を示す図である。
【図２２】複数のレイヤーに分割された符号化データを例示する模式図である。
【図２３】ＪＰＥＧ２０００方式による圧縮符号化装置の概略構成を示す機能ブロック図である。
【図２４】オクターブ分割方式に従って帯域分割された２次元画像を示す模式図である。
【図２５】複数のコードブロックに分解された２次元画像を示す模式図である。
【図２６】コードブロックを構成する複数枚のビットプレーンを示す模式図である。
【図２７】３種類の符号化パスを示す模式図である。
【符号の説明】
１ 符号量制御装置
２ 記憶装置
３ ＭＭＵ
４ ビット切り捨て制御部
５ 多重化部
６ 優先度テーブル
７ レイヤー分割制御部
１０ 画質制御部
１１ 符号量制御部[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a code amount control apparatus for controlling the code amount of a bit stream including a compressed image signal.
[0002]
[Prior art]
As a next-generation high-efficiency encoding system for image data, the ISO (International Organization for Standardization) and ITU-T (International Telecommunication Union Telecommunication Standardization Sector) have developed the JPEG 2000 (Joint Photographic Experts Group 2000) system. The JPEG2000 system has superior functions compared to the current mainstream JPEG (Joint Photographic Experts Group) system, adopts DWT (Discrete Wavelet Transform) as orthogonal transform, and uses bit for entropy coding. It is characterized in that a method called EBCOT (Embedded Block Coding with Optimized Truncation) with plain coding is adopted.
[0003]
Hereinafter, the JPEG2000 format compression encoding procedure will be outlined with reference to the compression encoding apparatus (encoder) 100 shown in FIG.
[0004]
The image signal input to the compression encoding apparatus 100 is subjected to DC level conversion as necessary by the DC level shift unit 102 and then output to the color space conversion unit 103. Next, the color space conversion unit 103 converts the color space of the signal input from the DC level shift unit 102. Next, the tiling unit 104 divides the image signal input from the color space conversion unit 103 into a plurality of area components called “tiles” having a rectangular shape, and outputs the result to the DWT unit 105. The DWT unit 105 performs integer type or real number type DWT on the image signal input from the tiling unit 104 in units of tiles, and outputs a conversion coefficient obtained as a result. In the DWT, a one-dimensional filter that divides a two-dimensional image signal into a high frequency component (high frequency component) and a low frequency component (low frequency component) is applied in the order of vertical and horizontal directions. The JPEG 2000 basic method employs an octave division method that recursively divides a band only in a band component that is divided in the vertical direction and the horizontal direction in the low frequency range. The number of times the band is recursively divided is called a decomposition level.
[0005]
FIG. 24 is a schematic diagram showing a two-dimensional image 120 that has been subjected to decomposition level 3 DWT according to the octave division method. At decomposition level 1, the two-dimensional image 120 is divided into four band components HH1, HL1, LH1, and LL1 (not shown) by sequentially applying the above-described one-dimensional filter in the vertical direction and the horizontal direction. The Here, “H” indicates a high frequency component, and “L” indicates a low frequency component. For example, HL1 is a band component composed of a high frequency component H in the horizontal direction and a low frequency component L in the vertical direction at the decomposition level 1. Generalizing the notation, “XYn” (X and Y are either H or L; n is an integer equal to or greater than 1) is defined as the horizontal band component X and the vertical band component Y at the decomposition level n. A band component consisting of
[0006]
Next, at the decomposition level 2, the low frequency component LL1 is band-divided into HH2, HL2, LH2, and LL2 (not shown). Further, at the decomposition level 3, the low frequency component LL2 is band-divided into HH3, HL3, LH3 and LL3. FIG. 24 shows the band components HH1 to LL3 generated as described above.
[0007]
Next, the quantization unit 106 has a function of performing scalar quantization on the transform coefficient output from the DWT unit 105 as necessary. The quantization unit 106 also has a function of performing bit shift processing that prioritizes the image quality of a designated region (ROI; Region Of Interest) by the ROI unit 107. Note that, when performing reversible (lossless) transformation, scalar quantization in the quantization unit 106 is not performed. In the JPEG2000 system, two types of quantization means are prepared: scalar quantization in the quantization unit 106 and post-quantization (truncation) described later.
[0008]
Next, the transform coefficient output from the quantization unit 106 is sequentially subjected to block-based entropy coding by the coefficient bit modeling unit 108 and the arithmetic coding unit 109 in accordance with the above-described EBCOT, and the code amount control unit 110. The rate is controlled by. Specifically, the coefficient bit modeling unit 108 divides the band component of the input transform coefficient into regions called “code blocks” of about 32 × 32 or 64 × 64, and further, each code block is divided into each bit. Decompose into a plurality of bit planes composed of a two-dimensional array.
[0009]
FIG. 25 is a schematic diagram illustrating a two-dimensional image 120 that has been decomposed into a plurality of code blocks 121, 121, 121,... FIG. 26 shows n bit planes 122 constituting the code block 121.₀~ 122_n-1It is a schematic diagram which shows (n: natural number). As shown in FIG. 26, when the binary value 123 of the conversion coefficient at one point in the code block 121 is “011... 0”, the bits constituting the binary value 123 are respectively bit planes 122._n-1122_n-2122_n-3, ..., 122₀It is disassembled to belong to. Bit plane 122 in the figure_n-1Represents the most significant bit plane consisting only of the most significant bit (MSB) of the transform coefficient, and represents the bit plane 122.₀Represents the least significant bit plane consisting only of the least significant bit (LSB).
[0010]
  Further, the coefficient bit modeling unit 108 includes each bit plane 122._kThe context of each bit in (k = 0 to n−1) is determined, and as shown in FIG. 27, according to the significance (determination result) of each bit, the bit plane 122 is determined._kWith three types of encoding passes:SIG pass ( SIGnificance propagation pass ), MR path ( Magnitude Refinement pass ), CL path ( CLeanup pass )Disassembled into The context determination algorithm for each coding pass is defined by EBCOT. According to it, “significant” means a state in which the coefficient of interest is known to be non-zero in the encoding process so far, and “not significant” means that the coefficient value is zero. , Or a state that may be zero.
[0011]
The coefficient bit modeling unit 108 performs an SIG path (significant coefficient coding pass with significant coefficients around), an MR path (significant coefficient coding path), and a CL path (SIG path, MR path not corresponding to the rest). Bit plane encoding is performed in three types of encoding passes). Bit plane encoding is performed by scanning the bits of each bit plane in units of 4 bits from the most significant bit plane to the least significant bit plane and determining whether or not a significant coefficient exists. The number of bit planes composed only of insignificant coefficients (0 bits) is recorded in the packet header, and actual encoding is started from the bit plane in which significant coefficients first appear. The encoding start bit plane is encoded only by the CL pass, and the bit planes lower than the bit plane are sequentially encoded by the above three types of encoding passes.
[0012]
Next, the arithmetic coding unit 109 performs arithmetic coding in units of coding passes on the coefficient sequence from the coefficient bit modeling unit 108 based on the context determination result using the MQ coder. There is also a mode in which the arithmetic encoding unit 109 performs a bypass process in which a part of the coefficient sequence input from the coefficient bit modeling unit 108 is not arithmetically encoded.
[0013]
Next, the code amount control unit 110 controls the final code amount by performing post-quantization that truncates the lower bit planes of the code string output by the arithmetic encoding unit 109. Then, the bit stream generation unit 111 generates a bit stream in which the code string output from the code amount control unit 110 and additional information (header information, layer configuration, scalability, quantization table, etc.) are multiplexed, and is used as a compressed image. Output.
[0014]
[Problems to be solved by the invention]
In the compression encoding apparatus 100 described above, the final code amount and the like are controlled so as to optimize the distortion amount with respect to the encoding rate using rate / distortion optimization (R-D optimization). The rate / distortion optimization is performed using a distortion amount in each coding pass calculated in the arithmetic coding stage. The algorithm for rate / distortion optimization is disclosed in the document "David S. Taubman and Michael W. Marcellin," JPEG2000 IMAGE COMPRESSION FUNDAMENTALS, STANDARDS AND PRACTICE, "Kluwer Academic Publishers" (hereinafter referred to as Reference A). Is done.
[0015]
On the other hand, in a digital device such as a digital camera, the image quality, image size, code amount, scalability (hierarchy), and the like of compressed image data may be changed. In such a case, the code amount and scalability of the compressed image are changed using a transcoder. In the JPEG2000 system, the scalability and code amount can be changed without decoding the compressed image signal. However, in the conventional JPEG baseline method, after the compressed image signal is once decoded, the scalability and code amount are changed. Since the change and compression encoding must be executed, the amount of calculation is large and the real-time property is low.
[0016]
Therefore, by using a JPEG2000 transcoder, it is possible to change the scalability, the code amount, and the like of the compressed encoded data in the bitstream generated by the compression encoding apparatus 100 with a small amount of calculation. However, the JPEG2000 transcoder cannot know the amount of distortion calculated by the compression encoding apparatus 100, and therefore cannot easily control the bitstream code amount using rate / distortion optimization. There is. Even if a transcoder that performs code amount control using rate / distortion optimization is feasible, the amount of calculation of the code amount control processing becomes enormous, and the real-time property is lowered.
[0017]
In view of the above problems and the like, the present invention has a problem that the code amount control of a bitstream including compressed encoded data can be executed with a small amount of computation and high speed so that distortion with respect to the rate can be suppressed. The point is to provide a code amount control device.
[0018]
[Means for Solving the Problems]
  In order to solve the above-mentioned problem, the invention according to claim 1 calculates a transform coefficient of a plurality of band components by recursively dividing the image signal into a high-frequency component and a low-frequency component by wavelet transform. A code amount control apparatus for controlling a code amount of compressed image data compressed by entropy coding of a coefficient, wherein each band component of the compressed image dataOf which the norm of the two-dimensional synthesis filter coefficient of the predetermined band component is a reference, andDepending on the number of times the band was recursively split,Set priorityPer priorityThe band component is bit-shifted by the number of bits corresponding to, and an image quality control unit that selects an encoding target in accordance with the target image quality from the band-shifted band component is provided.
[0019]
  The invention according to claim 2The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform ControlA code amount control device comprising:For each band component of the compressed image data, the band component is bit-shifted by the number of bits corresponding to the priority set according to the number of times the band is recursively divided into the low-frequency component, and the bit An image quality control unit that selects an encoding target in accordance with a target image quality from the shifted band component,The image quality control unit has a function of using the priority weighted in consideration of human visual characteristics.
[0020]
The invention according to claim 3 is the code amount control apparatus according to claim 1 or 2, wherein the image quality control unit has a function of determining the encoding target in units of the bit planes.
[0021]
The invention according to a fourth aspect is the code amount control apparatus according to any one of the first to third aspects, wherein the image quality control unit has a function of determining the encoding target in units of the encoding pass. It is what you have.
[0022]
  Next, the invention according to claim 5 calculates a transform coefficient of a plurality of band components by recursively dividing the image signal into a high frequency component and a low frequency component by wavelet transform, and the transform coefficients are entropy coded. A code amount control apparatus for controlling the code amount of compressed image data compressed by compression, wherein each band component of the compressed image dataOf which the norm of the two-dimensional synthesis filter coefficient of the predetermined band component is a reference, andDepending on the number of times the band was recursively split,Set priorityPer priorityThe band component is bit-shifted by the number of bits corresponding to, and the truncation point that matches the target code amount is calculated from the code string generated by rearranging the encoded data of the band-shifted band component in a predetermined scanning order. And a code amount control unit that controls to output the code string before the cut-off point.
[0023]
The invention according to claim 6 is the code amount control apparatus according to claim 5, wherein the code amount control unit outputs the encoded data in the order of the highest priority and in the same priority. The code string is generated by rearranging in the scanning order from the side toward the low frequency side.
[0024]
The invention according to claim 7 is the code amount control apparatus according to any one of claims 1 to 6, wherein the low-frequency component is recursively applied to each band component of the compressed image data. A layer division control unit that performs bit shift of the band component by the number of bits corresponding to the priority set according to the number of times of band division, and controls the band shifted bit component to be divided into a plurality of layers, Is further provided.
[0025]
The invention according to claim 8 is the code amount control apparatus according to claim 7, wherein the layer division control unit has a function of using the priority weighted in consideration of human visual characteristics. It is.
[0026]
  Next, the invention according to claim 9 calculates a transform coefficient of a plurality of band components by recursively dividing the image signal into a high frequency component and a low frequency component by wavelet transform, and the transform coefficients are entropy coded. A program for controlling the amount of code of compressed image data compressed by compression, wherein each band component of the compressed image dataOf which the norm of the two-dimensional synthesis filter coefficient of the predetermined band component is a reference, andDepending on the number of times the band was recursively split,Set priorityPer priorityThe band component is bit-shifted by the number of bits corresponding to, and the microprocessor is caused to function as an image quality control unit that selects an encoding target in accordance with the target image quality from the band-shifted band component.
[0027]
  The invention according to claim 10 is:The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform To controlThe program ofFor each band component of the compressed image data, the band component is bit-shifted by the number of bits corresponding to the priority set according to the number of times the band is recursively divided into the low-frequency component, and the bit The microprocessor functions as an image quality control unit that selects an encoding target in accordance with the target image quality from the shifted band component,The image quality control unit causes the microprocessor to function so as to use the priority weighted in consideration of human visual characteristics.
[0028]
The invention according to claim 11 is the program according to claim 9 or 10, wherein the image quality control unit causes the microprocessor to function so as to determine the encoding target in units of the bit planes.
[0029]
A twelfth aspect of the invention is the program according to any one of the ninth to eleventh aspects, in which the image quality control unit determines the encoding target in units of the encoding pass. Is to function.
[0030]
  Next, an invention according to claim 13 is that the image signal is recursively divided into a high-frequency component and a low-frequency component by wavelet transform to calculate transform coefficients of a plurality of band components, and the transform coefficients are entropy-coded. A program for controlling the amount of code of compressed image data compressed by compression, wherein each band component of the compressed image dataOf which the norm of the two-dimensional synthesis filter coefficient of the predetermined band component is a reference, andDepending on the number of times the band was recursively split,Set priorityPer priorityThe band component is bit-shifted by the number of bits corresponding to, and the truncation point that matches the target code amount is calculated from the code string generated by rearranging the encoded data of the band-shifted band component in a predetermined scanning order. In addition, a microprocessor is made to function as a code amount control unit that controls to output the code string before the cut-off point.
[0031]
The invention according to claim 14 is the program according to claim 13, wherein the code amount control unit sets the encoded data in a descending order from the highest priority and from the high frequency side in the same priority. The microprocessor is caused to function so as to generate the code string by rearranging in the scanning order toward the region side.
[0032]
The invention according to claim 15 is the program according to any one of claims 9 to 14, wherein the respective band components of the compressed image data are recursively band-divided into the low-frequency components. As the layer division control unit that performs bit shift of the band component by the number of bits corresponding to the priority set according to the number of times, and controls the bit shift to divide the band component into a plurality of layers, It makes the processor function.
[0033]
The invention according to claim 16 is the program according to claim 15, wherein the layer division control unit functions the microprocessor to use the priority weighted in consideration of human visual characteristics. It is something to be made.
[0034]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described.
[0035]
Configuration of code amount control device.
FIG. 1 is a functional block diagram showing a schematic configuration of a code amount control apparatus according to an embodiment of the present invention. The code amount control device (transcoder) 1 includes a large-capacity storage device 2, an MMU (memory management unit) 3 that controls reading and writing of data with respect to the storage device 2, a bit truncation control unit 4, a multiplexing unit And a priority table 6 and a layer division control unit 7.
[0036]
Note that all or part of the processing units 4, 5, 6 and 7 constituting the code amount control apparatus 1 may be configured by hardware or a program for causing the microprocessor to function. .
[0037]
The MMU 3 of the code amount control device 1 temporarily stores an input bitstream including compressed encoded data compressed and encoded by the JPEG2000 system in the storage device 2, and then according to control signals CS1 and CS2 for controlling the code amount. Data OD is read from the storage device 2 and output to the multiplexing unit 5. The multiplexing unit 5 multiplexes the data OD and outputs it as an output bit stream.
[0038]
FIG. 2 is a functional block diagram showing a schematic configuration of the bit truncation control unit 4 in the code amount control device 1 shown in FIG. The bit truncation control unit 4 includes an image quality control unit 10 that selects an encoding target according to the target image quality, and a code amount control unit 11 that controls the code amount according to the target code amount (final code amount). . Further, the code amount control unit 11 calculates a truncation point that matches the target code amount from the encoding target selected by the image quality control unit 10 based on the data structure information DS of the input bitstream supplied from the MMU 3. The read control signal CS1 for reading the code string before the cut-off point is generated and supplied to the MMU 3.
[0039]
1 generates a read control signal CS2 for generating an output bitstream divided into a plurality of layers, based on the data structure information DS of the input bitstream supplied from the MMU 3. And output to the MMU 3.
[0040]
The priority table 6 indicates the priority set according to the number of times the band components of the compression-coded data included in the input bitstream are recursively band-divided into low-frequency components according to the JPEG2000 system. The priority data PS1 and PS2 are stored and supplied to the bit truncation control unit 4 and the layer division control unit 7.
[0041]
The configuration and operation of the code amount control apparatus 1 having the above configuration will be described in detail below.
[0042]
Priority setting process (first embodiment).
A first embodiment of the priority setting method recorded in the priority table 6 will be described. In the present invention, the priority is determined for each band component (subband) according to the number of times the band is recursively divided into low frequency components. In this embodiment, the priority of the band component HHn at the decomposition level n (n: an integer of 1 or more) is “n−1”, the priority of the band components HLn and LHn is “(n−1) +1”, and the band component. The priority of LLn is determined as “(n−1) +2”. For example, the priority of the band component HH1 shown in FIG. 24 is set to “0”, and the priority of the band component LL3 is set to “4”. FIG. 3 is a schematic diagram showing a two-dimensional image 25 obtained by band division according to the octave division method. Each band component has a priority “0”, “1”, “2”, “3”, or “4”.
[0043]
The priority table 6 records priority information corresponding to each of the band components HHn, HLn, LHn, and LLn. The image quality control unit 10, the code amount control unit 11, and the layer division control unit 7 In accordance with the priority data PS1 and PS2 acquired from the priority table 6, priority is set for each band component. Specifically, the transform coefficient entropy-encoded in each band component (hereinafter simply referred to as “transform coefficient”) is shifted by the number of bits corresponding to the priority to give priority to each transform coefficient. The degree is set. In this bit shift process, it is not always necessary to actually perform a bit shift operation on each transform coefficient, and the position of each bit of the transform coefficient may be virtually shifted. In this case, the position of the bit plane to which each bit of the transform coefficient belongs does not change.
[0044]
FIG. 4 is a diagram for explaining priority setting processing by bit shift. In the example shown in FIG. 3, since the priority of the band component LL3 is “4”, the corresponding transform coefficient 26 is shifted left by 4 bits. Further, the conversion coefficients 26 and 26 of the band components HL3 and LH3 set with the priority “3” are shifted left by 3 bits, and the conversion coefficients 26 of the band components HH3, HL2 and LH2 set with the priority “2” are set. , 26, and 26 are shifted left by 2 bits, and the transform coefficients 26, 26, and 26 of the band components HH2, HL1, and LH1 set with the priority "1" are shifted left by 1 bit. At this time, as shown in FIG. 5, the conversion coefficient of the two-dimensional image 25A before the bit shift is changed to the conversion coefficient indicated by the two-dimensional image 25B by the left bit shift process. For example, the transform coefficient value (= 4) of the band component LL3 is 4 × 2 by 4-bit left shift.^Four= 64.
[0045]
Next, the reason (theoretical background) for setting the priority as described above will be described below.
[0046]
In the above-described conventional rate / distortion optimization (R-D optimization) method, an optimization process using a distortion measure has been performed. According to the above reference A by David S. Taubman et al._i ^(z)Is calculated according to the following equation (1).
[0047]
[Expression 1]

[0048]
In the above formula (1), z is a bit truncation point; oy_i ^{K [i, j]}[J] is the jth sample value (coefficient value) of the code block dequantized by the K [i, j] th bitplane; y_i[J] is the j-th sample value (coefficient value) of the code block; G_{b [i]}Is the square of the norm of the synthesis filter coefficient corresponding to the subband b [i], and indicates the weighting coefficient of the distortion model depending on the subband b. For convenience of explanation, the notation of the symbol shown in the above formula (1) is slightly different from that in the reference A.
[0049]
For rate / distortion optimization, this distortion measure D_i ^(z)Optimization processing is performed so as to minimize the total amount in the subband b [i]. Weighting factor G for subband b_bRepresents weighting for reducing image distortion.
[0050]
Weighting factor G for subband b_bIs calculated according to the following equation (2).
[0051]
[Expression 2]

[0052]
Here, in the above equation (2), s_b[N] indicates a one-dimensional synthesis filter coefficient of subband b. The symbol || x || indicates a norm related to the vector x.
[0053]
According to the equations (4.39) and (4.40) described in the reference A, the one-dimensional synthesis filter coefficient s of the low-frequency component L1 at the decomposition level 1_{L [1]}[N] and the one-dimensional synthesis filter coefficient s of the high-frequency component H1 at the same decomposition level_{H [1]}[N] is calculated according to the following equation (3).
[0054]
[Equation 3]

[0055]
Here, in the above formula (3), g₀[N] is a low-pass filter coefficient of a forward transform filter for dividing an image signal into bands, g₁[N] indicates the high-pass filter coefficient, respectively.
[0056]
Further, the one-dimensional synthesis filter coefficient s of the low frequency component Ld at the decomposition level d (d = 1, 2,..., D)._{L [d]}[N] and the one-dimensional synthesis filter coefficient s of the high-frequency component Hd at the same decomposition level_{H [d]}[N] is calculated according to the following equation (4).
[0057]
[Expression 4]

[0058]
Then, the square of the norm of the one-dimensional synthesis filter coefficient of the low frequency component Ld at the decomposition level d is calculated according to the following equation (5).
[0059]
[Equation 5]

[0060]
The square of the norm of the one-dimensional synthesis filter coefficient of the high-frequency component can be calculated in the same manner as the above equation (5).
[0061]
Next, the two-dimensional synthesis filter coefficients of the band components LLD, HLd, LHd, and HHd at the decomposition level d (d = 1, 2,..., D; D is an integer) are expressed by the product of the one-dimensional synthesis filter coefficients. The two-dimensional weighting factor G of the band component b_bCan also be expressed as a product of one-dimensional weighting factors. Specifically, the two-dimensional synthesis filter coefficient and the two-dimensional weighting coefficient are calculated according to the following equation (6).
[0062]
[Formula 6]

[0063]
In the above formula (6), the subscript LL [D] indicates the subband LLD, and HL [d], LH [d], and HH [d] indicate the subbands HLd, LHd, and HHd, respectively.
[0064]
Weight coefficient G_bIs the norm. Tables 1 to 4 below show the two-dimensional weighting factor G_bThe calculation result about is shown. Table 1 shows the numerical value of the norm of each band component of the (9, 7) filter (9 × 7 tap filter), and Table 2 shows the numerical value of the norm corresponding to Table 1. Table 3 shows the norm square value of each band component of the (5, 3) filter (5 × 3 tap filter), and Table 4 shows the norm value corresponding to Table 3.
[0065]
[Table 1]

[0066]
[Table 2]

[0067]
[Table 3]

[0068]
[Table 4]

[0069]
Furthermore, when the norm of the low-frequency component LL1 at the decomposition level 1 is represented by α, a value as shown in FIG. 6 is set for each band component using this norm α. A two-dimensional image 27 shown in FIG. 6 is a diagram showing a two-dimensional image 120 that is band-divided according to the octave division method. The set value of the band component HHn at the decomposition level n (n is an integer of 1 or more) is “2^n-3× α ”, the set values of the band components HLn and LHn are“ 2 ”^n-2× α ”, the set value of the band component LLn is“ 2 ”^n-1Xα ”. Therefore, for example, the set value of the band component LH1 is “2”.^-1× α ”.
[0070]
If the set value is compared with the norm values shown in Tables 2 and 4, they are approximately approximate. For example, in the case of Table 2 (α = 1.96591), the “set value (corresponding band component)” of each band component shown in FIG. 6 is about 0.49 (HH1), about 0.98 (HL1, LH1), It is about 1.96 (HL2, LH2, HH3), about 3.93 (HL3, LH3), and about 7.86 (LL3), and these set values are close to the norm values shown in Table 2. I understand.
[0071]
In FIG. 6, the norm of the band component LL1 is rounded to α = 2, and the set value of each band component is shifted to the left by 1 bit, that is, all set values are 2¹It can be seen that the exponent of the power value of 2 multiplied by 2 matches the priority value shown in FIG. Therefore, setting the priority to each band component as in the first embodiment approximately means that the norm (square root of the weighting factor) of the filter used in the rate / distortion optimization is the sample value of each band component ( Equivalent to multiplying (conversion coefficient value). Accordingly, the priority of the present embodiment is set so as to reduce image distortion.
[0072]
Priority setting process (second embodiment).
Next, a second embodiment of the priority setting method will be described. In the present embodiment, the weight coefficient G of each band component_bA value obtained by dividing the norm, which is the square root of, by the norm of the lowest frequency component LL at the highest decomposition level is rounded to a power value of 2, and the absolute value of the exponent of the power value of 2 is set as the priority. Specifically, the norm of the lowest band component LLn of the highest decomposition level n is α, the norm of the other band component is x, a function related to a variable y rounded to the power of 2 is R [y], and the variable y 2 power of 2^mA function for calculating an index m of m = I [2^m] And the absolute value for the variable y is | y |, the priority p is calculated according to p = | I [R [x / α]] |.
[0073]
Table 5 below shows the priority calculated using the norm of the (9, 7) filter shown in Table 2 above. Here, the highest decomposition level is 5, and α = 33.4923. FIG. 7 shows a band division diagram showing the two-dimensional image 28 in which the priorities shown in Table 5 are shown. In the table, “x” means that the priority of the band component is not calculated.
[0074]
[Table 5]

[0075]
Table 6 below shows the priority calculated using the norm of the (5, 3) filter shown in Table 4 above.
[0076]
[Table 6]

[0077]
In the first embodiment, the priority is set by shifting the conversion coefficient of each band component to the left by the number of priority bits, but in the second embodiment, the conversion coefficient of each band component is set to the priority. A process of shifting right by the number of bits is executed. However, the right bit shift process is executed so as to increase the bit length of the transform coefficient. FIG. 8 is a schematic diagram showing band component conversion coefficients 29, 29,... Shifted to the right by the number of priority bits shown in FIG.
[0078]
Priority setting process (third embodiment).
Next, a priority setting method according to the third embodiment in consideration of human visual characteristics will be described. When the priority shown in the second embodiment is applied to a high-resolution image of about several million pixels, the image quality of the decoded image is good for objective evaluation, but not necessarily good for human visual evaluation. Therefore, the priority setting method of this embodiment employs a weighted priority in consideration of human visual characteristics. This makes it possible to generate a compressed image with high display quality.
[0079]
Chapter 16 of the reference A describes a weighted mean squared error (WMSE) based on CSF (human visual system contrast sensitivity function). According to this description, in order to improve human visual evaluation, it is desirable to modify the above equation (1) into the following equation (7).
[0080]
[Expression 7]

[0081]
Here, in the above formula (7), W_{b [i]} ^csfIs called the “energy weighting factor” of subband b [i] and W_{b [i]} ^csfThe recommended value for is the ISO / IEC JTC 1 / SC 29 / WG1 (ITU-T SG8) N2406, "JPEG 2000 Part 1 FDIS (includes COR 1, COR 2, and DCOR3)," 4 December 2001 document ( Hereinafter referred to as Reference Document B). 9 to 11 show numerical values of “energy weighting factor” described in Reference Document B. FIG.
[0082]
9 to 11, “level” and “Lev” indicate the decomposition level, “Comp” indicates the luminance component Y and the color difference components Cb and Cr, respectively, and “Viewing distance” is 1000 and 1700. , 2000, 3000, 4000 examples are shown. "Viewing distance 1000", "Viewing distance 1700", "Viewing distance 2000", "Viewing distance 3000", and "Viewing distance 4000" are 10 displays or printed materials of 100 dpi, 170 dpi, 200 dpi, 300 dpi, and 400 dpi, respectively. The viewing distance when viewed from an inch away.
[0083]
Using the numerical values shown in FIGS. 9 to 11, the square root (W_{b [i]} ^csf・ G_{b [i]})^1/2Was calculated. The calculation results are shown in Tables 7 to 18 below. Tables 7 to 9 are calculated using the numerical values shown in FIG. 9 (9, 7), and black and white values for the filter. Tables 10 to 12 are calculated using the numerical values shown in FIGS. 10 and 11 (9 7) Filter color values, Tables 13 to 15 calculated using the values shown in FIG. 9, (5, 3) Filter black and white values, Tables 16 to 18 are shown in FIG. The numerical values for the color of the (5, 3) filter calculated using the numerical values shown in FIG.
[0084]
[Table 7]

[0085]
[Table 8]

[0086]
[Table 9]

[0087]
[Table 10]

[0088]
[Table 11]

[0089]
[Table 12]

[0090]
[Table 13]

[0091]
[Table 14]

[0092]
[Table 15]

[0093]
[Table 16]

[0094]
[Table 17]

[0095]
[Table 18]

[0096]
Next, using the numerical values shown in Tables 7 to 18, the priority of each band component was calculated in the same procedure as described in the second embodiment. That is, the numerical value of the lowest band component LLn of the highest decomposition level n is α, the numerical values of the other band components are x, the function relating to the variable y rounded to the power of 2 is R [y], and the variable y of 2 Width power 2^mA function for calculating an index m of m = I [2^m] And the absolute value for the variable y is | y |, the priority p is calculated according to p = | I [R [x / α]] |.
[0097]
The priority values are shown in Table 19 to Table 30 below. The priorities of Table 19, Table 20, Table 21, Table 22, Table 23, Table 24, Table 25, Table 26, Table 27, Table 28, Table 29, and Table 30 are shown in Tables 7, 8, and 8, respectively. Table 9, Table 10, Table 11, Table 12, Table 13, Table 14, Table 15, Table 16, Table 17, and Table 18 are used for calculation.
[0098]
[Table 19]

[0099]
[Table 20]

[0100]
[Table 21]

[0101]
[Table 22]

[0102]
[Table 23]

[0103]
[Table 24]

[0104]
[Table 25]

[0105]
[Table 26]

[0106]
[Table 27]

[0107]
[Table 28]

[0108]
[Table 29]

[0109]
[Table 30]

[0110]
In the present embodiment, as in the second embodiment, the priority is set for the conversion coefficient of each band component by shifting right by the number of bits of the priority shown in Tables 19 to 30 above. The Thereby, the priority which considered the human visual characteristic can be set.
[0111]
Image quality control processing.
Next, the configuration and processing contents of the image quality control unit 10 shown in FIG. 2 will be described. FIG. 12 is a functional block diagram showing a schematic configuration of the image quality control unit 10.
[0112]
The image quality control unit 10 selects and outputs an image quality parameter QP suitable for the target image quality from a plurality of image quality parameter groups based on the target image quality (high image quality, standard image quality, low image quality, etc.). And an encoding target determination unit 30 that determines an encoding target. The encoding target determination unit 30 sets the above-described priority for each band component of the compressed image data included in the input bitstream according to the priority data PS1 acquired from the priority table 6. The encoding target determination unit 30 determines the encoding target in accordance with the target image quality specified by the image quality parameter QP according to the set priority, and generates and outputs the scanning area information SA.
[0113]
Hereinafter, a method for determining an encoding target in the encoding target determination unit 30 will be described. FIG. 13 is a schematic diagram illustrating conversion coefficients 33, 33,... Bit-shifted according to priority. Each conversion coefficient 33 is bit-shifted according to the priority. The numbers 0, 1,..., 10 attached to the respective bits of the conversion coefficient 33 indicate the numbers of bit planes to which the bits belong. Here, LSB number = 0 and MSB number = 10.
[0114]
The encoding target determination unit 30 sets the encoding end line 32 according to the image quality parameter QP, determines the higher bits than the encoding end line 32 as the encoding target, and sets the lower bits than the line 32 as the encoding target. The scanning area information SA is generated so as to be excluded from the above. This makes it possible to efficiently select the encoding target. As a result, the code amount control unit 11 that has received the scanning area information SA scans only the bit plane higher than the encoding end line 32 in each code block, and truncates the bit plane lower than the line 32. become.
[0115]
The encoding target determination unit 30 can further determine the encoding target in units of encoding passes according to the image quality parameter QP. The image quality parameter QP includes a parameter group indicating a restriction on a bit plane to be encoded and a restriction on a coding path (CL path, SIG path, and MR path) to be encoded. Table 31 below illustrates image quality parameters QP suitable for an image having a resolution of 2048 × 2560 pixels. Since the resolution of the lowest subband needs to be smaller than 128 × 128 pixels, a resolution level of 5 or higher is required.
[0116]
[Table 31]

[0117]
In Table 31, “Number of bit planes” indicates the number of bit planes subject to truncation of lower bits than the encoding end line 32 shown in FIG. 13, and “Path name” indicates the last encoding pass in the encoding target. The “maximum number of passes” represents the upper limit of the number of encoding passes to be encoded.
[0118]
An example of processing when FIG. 13 and Table 31 are applied will be described below. FIG. 14 shows “00011010111” as the conversion coefficient 33 of the band component LL5.₂= 215_TenExemplify (Y₂Is the binary value Y, X_TenRepresents the decimal value X). As shown in Table 31, the final coding pass in the band component LL5 is limited to the CL pass, and the maximum number of passes is limited to 17.
[0119]
The context determination is performed so that the seventh bit of the transform coefficient shown in FIG. 14 belongs to the SIG path or the CL path. If the 8th to 10th upper bits belong to a bit plane composed of only 0 bits, they are encoded by a method called a tag tree, and the encoding pass has already started. It is encoded by SIG pass or CL pass. When the seventh bit belongs to the encoding start pass (CL pass), the lower-order bits including the sixth bit are context-determined so as to belong to the MR pass. In general, bit planes lower than the encoding start bit plane are encoded in the order of the SIG pass, MR pass, and CL pass from the viewpoint of encoding efficiency. Therefore, since the maximum number of passes is limited to 17, a total of 17 passes from the 7th bit CL pass to the 1st bit SIG pass are to be encoded. However, since the first bit belongs to the MR path, it does not enter the encoding target. Therefore, the lower 2 bits are truncated, and the value after truncation is "00011010100₂= 212_Ten"If this value is dequantized at midpoint," 00011010110₂= 214_Ten"Become.
[0120]
Next, FIG. 15 shows “00000001111” as the conversion coefficient 33 of the band component LL5.₂= 15_TenThe third bit of the transform coefficient belongs to the SIG path or the CL path. If the fourth to tenth upper bits belong to a bit plane consisting of only 0 bits, a tag tree (Tag tree) If the third bit belongs to the coding start pass (CL pass), the second bit is set to the SIG pass or the CL pass. The lower bits included belong to the MR pass, and a total of 10 passes from the CL pass of the 3rd bit to the CL pass of the 0th bit are to be encoded. The value after truncation is “00000001111”.₂= 15_Ten"If this value is dequantized," 00000001111₂= 15_Ten"Become.
[0121]
Next, FIG. 16 shows “00001011111” as the conversion coefficient 33 of the band component HH2.₂= 95_Ten“As an example, as shown in Table 31, the final coding pass in the band component HH2 is limited to the SIG pass, and the maximum number of passes is 14. The bit planes of the lower 3 bits are discarded.
[0122]
The sixth bit of the transform coefficient belongs to the SIG path or CL path. The seventh to the tenth upper bits are encoded with a tag tree if they belong to a bit plane consisting of only 0 bits, and if the encoding pass has already started, the SIG pass or Encoded with CL path. When the sixth bit belongs to the encoding start pass (CL pass), the lower bits including the fifth bit belong to the MR pass. Also, because of the limitation that encoding is performed only up to the SIG pass of the third bit plane, 8 passes from the CL pass of the 6th bit to the SIG pass of the 4th bit are encoded, but the 3rd bit is the MR pass. Because it belongs to, it does not enter the encoding target. Therefore, the value after truncation is "00001010000₂= 80_Ten"If this value is dequantized at midpoint," 00001011000₂= 88_Ten"Become.
[0123]
Each bit plane is encoded in the order of the SIG pass, MR pass, and CL pass because the encoding efficiency with respect to the distortion of the SIG pass is the highest. FIG. 17 shows rate / distortion characteristics in each coding pass. Point P in the RD curve₁~ P₂Is the SIG path, point P₂~ P_ThreeIs the MR path, point P_Three~ P_FourIndicates the CL path. Ratio of distortion ΔD to rate (code amount) in each coding pass_SIG/ ΔR_SIG, ΔD_MR/ ΔR_MR, ΔD_CL/ ΔR_CLAs can be seen, the curve slope in the SIG path is the steepest and the coding efficiency is the highest.
[0124]
As described above, in the image quality control processing according to the present embodiment, it is determined whether or not the transform coefficient is to be encoded with respect to the transform coefficient bit-shifted according to the priority. Since only the encoding target is selected, it is possible to efficiently control the code amount so that a high-quality compressed image with little distortion can be generated.
[0125]
Code amount control processing.
Next, processing contents of the code amount control unit 11 shown in FIG. 2 will be described. The code amount control unit 11 calculates a subtotal of the capacity of the compressed encoded data included in the input bitstream in band component units, bit plane units, and encoding pass units.
[0126]
The code amount control unit 11 calculates a truncation point so as to match the target code amount from a code string generated by rearrangement in the scanning order described below. Next, the code amount control unit 11 outputs the read control signal CS1 to the MMU 3 so as to read the code string before the cut-off point in the code string.
[0127]
18 and 19 are diagrams for explaining an example of the scanning order and the cut-off points. 18 and 19 show transform coefficients 33, 33,... Bit-shifted according to priority according to the same rules as shown in FIG.
[0128]
As shown by the arrows in FIG. 18, the transform coefficients 33, 33,... Are in bit-plane units or coding pass units in the order of priority (from the upper bit to the lower bit) and at the same priority. Rearranged in the scanning order from the high frequency side to the low frequency side. In general, as the lower bit plane is encoded, the MR path ratio increases and the compression efficiency tends to decrease. Therefore, in order to encode as many SIG passes as possible in order to improve the compression efficiency, the scanning order from the high frequency side to the low frequency side is adopted at the same priority.
[0129]
Then, the code amount control unit 11 determines a truncation point so that the actual code amount (number of bytes) is less than or equal to the target code amount (number of bytes), and the lower order included in the code string after the truncation point. Truncate the bit plane. Thereby, the code amount control of the compression encoded data can be efficiently performed according to the priority set for each subband. Here, as shown in FIG. 19, when the second bit plane of the subband HL3 is determined as the truncation point in accordance with the target code amount, the bit indicated by the arrow is truncated.
[0130]
20 is a diagram illustrating a code string rearranged in units of bit planes, and FIG. 21 is a diagram illustrating a code string rearranged in units of coding passes. In FIG. 20, codes LL5, HL5,... Indicating subbands and bit plane numbers 10, 9,. The bit plane after the line 44 attached to the second bit plane of the subband HL3 is discarded.
[0131]
21, for each coding pass, codes CL, SIG, MR indicating the type of coding pass, codes LL5, HL5,... Indicating subbands, bit plane numbers 10, 9,. Is attached. The bit planes after the line 44 attached to the MR path of the second bit plane of the subband HL3 are discarded.
[0132]
As described above, according to the code amount control process according to the present embodiment, it is not necessary to use the distortion amount in each encoding pass for the rate / distortion optimization process, and the real time performance is high and the overhead is low. Can be realized.
[0133]
Layer division processing.
Next, the operation of the layer division control unit 7 shown in FIG. 2 will be described below. The layer division control unit 7 uses the priority data PS2 acquired from the priority table 6 to convert the compressed encoded data included in the input bitstream into a code string that is bit-shifted by the number of bits corresponding to the priority, It has a control function for dividing the code string into a plurality of layers (multi-layer).
[0134]
  Hereinafter, the layer division process will be described. The MMU 3 temporarily stores the input bit stream in the large-capacity storage device 2. The layer division control unit 7MMU3To obtain the data structure information DS of the compressed encoded data. Next, the layer division control unit 7 acquires the priority data PS2 from the priority table 6, and in accordance with the priority included in the priority data PS2, the conversion coefficient of each band component of the compressed encoded data is a predetermined number of bits. Shift. Thereby, a priority is set with respect to the conversion coefficient of each band component. As a priority setting method, the methods of the first, second, and third embodiments described above may be employed.
[0135]
  FIG. 22 shows the transform coefficient shifted by the number of bits corresponding to the priority.45, 45FIG. Conversion coefficient of each band component LL5 to HH145, 45,... Are right bit shifted or left bit shifted by the number of priority bits. Further, numbers 0, 1,..., 10 attached to the respective bits of each conversion coefficient 44 indicate the numbers of bit planes to which the bits belong. Here, LSB number = 0 and MSB number = 10.
[0136]
Next, the layer division control unit 7 determines a division position based on the layer division information so that the bit-shifted encoded data is grouped into a plurality of layers in bit plane units or encoding pass units. The layer division information includes selection information for selecting either a single layer or a multi-layer, information for specifying a layer division position in bit plane units or encoding pass units, and the like. In the example of FIG. 22, a division position where the compression encoded data is divided into five layers 0 to 4 in units of bit planes is shown. Then, the layer division control unit 7 supplies the MMU 3 with a read control signal CS2 for reading data in units of layers according to the division position. The MMU 3 reads the data OD stored in the storage device 2 in order from the upper layer to the lower layer in accordance with the read control signal CS2, and outputs the data OD to the multiplexing unit 5.
[0137]
In the layer division processing described above, the priority is set by shifting each band component by the number of bits corresponding to the priority. By dividing the bit-shifted band component into a plurality of layers in this way, it is possible to efficiently generate a plurality of layers in bit plane units or coding pass units so that distortion with respect to the rate can be reduced. is there. Therefore, it is not always necessary to perform the layer division processing using the above-described rate / distortion optimization, and it is possible to perform the layer division processing with high real-time property so that the distortion can be reduced.
[0138]
【The invention's effect】
As described above, according to the code amount control apparatus according to the first aspect of the present invention and the program according to the ninth aspect, each band component is shifted by the number of bits corresponding to the priority, and the band according to the number of bits to be shifted. Since the priority of the components is determined, it is possible to efficiently specify the encoding target in accordance with the target image quality of the compressed image and perform high-speed code amount control with a small amount of calculation.
[0139]
According to the second and tenth aspects, it is possible to perform the code amount control so as to realize a high display image quality suitable for human visual evaluation.
[0140]
According to the third and eleventh aspects, the code amount can be finely and efficiently controlled in bit plane units according to the target image quality.
[0141]
According to the fourth and twelfth aspects, the code amount can be finely and efficiently controlled for each coding pass in accordance with the target image quality.
[0142]
According to the fifth, sixth, and thirteenth and fourteenth aspects, the code amount control of the compression encoded data is efficiently performed according to the priority set for each band component without decoding the compression encoded data. It is possible. In addition, it is possible to perform code amount control with high real-time characteristics so that distortion can be suppressed without necessarily using rate / distortion optimization.
[0143]
According to the seventh and fifteenth aspects, since the band component bit-shifted according to the priority is divided into a plurality of layers, the plurality of layers can be efficiently generated so as to reduce distortion with respect to the rate. Is possible.
[0144]
According to the eighth and sixteenth aspects, it is possible to generate a compressed image having high display image quality suitable for human visual evaluation.
[Brief description of the drawings]
FIG. 1 is a functional block diagram showing a schematic configuration of a code amount control apparatus according to an embodiment of the present invention.
FIG. 2 is a functional block diagram showing a schematic configuration of a bit truncation control unit in the code amount control apparatus shown in FIG. 1;
FIG. 3 is a schematic diagram illustrating a two-dimensional image obtained by band division according to an octave division method.
FIG. 4 is a diagram for explaining priority setting processing by bit shift.
FIG. 5 is a diagram illustrating bit-shifted transform coefficients.
FIG. 6 is a schematic diagram showing a two-dimensional image obtained by band division by wavelet transform.
FIG. 7 is a schematic diagram showing a two-dimensional image obtained by band division by wavelet transform.
8 is a schematic diagram showing band component conversion coefficients that are right-bit shifted in accordance with the priorities shown in FIG.
FIG. 9 is a diagram illustrating a numerical table of energy weighting factors.
FIG. 10 is a diagram showing a numerical table of energy weighting factors.
FIG. 11 is a diagram showing a numerical table of energy weighting factors.
FIG. 12 is a functional block diagram illustrating a schematic configuration of an image quality control unit according to the present embodiment.
FIG. 13 is a schematic view illustrating conversion coefficients bit-shifted according to priority.
FIG. 14 is a diagram for explaining a processing example of a transform coefficient of band component LL5.
FIG. 15 is a diagram for explaining a processing example of a transform coefficient of band component LL5.
FIG. 16 is a diagram for explaining an example of encoding processing of transform coefficients of band component HH2.
FIG. 17 is a diagram showing a curve of rate / distortion characteristics.
FIG. 18 is a diagram for explaining an example of a scanning order.
FIG. 19 is a diagram for explaining an example of truncation points;
FIG. 20 is a diagram illustrating code strings rearranged in units of bit planes.
FIG. 21 is a diagram illustrating code strings that are rearranged in units of coding passes.
FIG. 22 is a schematic diagram illustrating encoded data divided into a plurality of layers.
FIG. 23 is a functional block diagram showing a schematic configuration of a compression encoding apparatus according to the JPEG2000 system.
FIG. 24 is a schematic diagram showing a two-dimensional image band-divided according to an octave division method.
FIG. 25 is a schematic diagram showing a two-dimensional image decomposed into a plurality of code blocks.
FIG. 26 is a schematic diagram showing a plurality of bit planes constituting a code block.
FIG. 27 is a schematic diagram showing three types of encoding passes.
[Explanation of symbols]
1 Code amount control device
2 storage devices
3 MMU
4-bit truncation control unit
5 Multiplexer
6 Priority table
7 Layer division controller
10 Image quality control unit
11 Code amount control unit

Claims (16)

The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform A code amount control device for controlling
Among the respective band components of the compressed image data, based on the norm of the two-dimensional synthesis filter coefficients in a predetermined band component, and, recursively according to the number of times which is band-divided, per set priority, the An image quality control unit that bit-shifts the band component by the number of bits corresponding to the priority, and selects an encoding target in accordance with the target image quality from the band-shifted band component,
A code amount control apparatus comprising: The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform A code amount control device for controlling
For each band component of the compressed image data, the band component is bit-shifted by the number of bits corresponding to the priority set according to the number of times the band is recursively divided into the low-frequency component, and the bit An image quality control unit that selects an encoding target in accordance with a target image quality from the shifted band component,
With
The code quality control device, wherein the image quality control unit has a function of using the priority weighted in consideration of human visual characteristics.   The code amount control apparatus according to claim 1 or 2, wherein the image quality control unit has a function of determining the encoding target in units of the bit planes. The code amount control apparatus according to any one of claims 1 to 3,
The image quality control unit is a code amount control device having a function of determining the encoding target in units of the encoding pass. The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform A code amount control device for controlling
Among the respective band components of the compressed image data, based on the norm of the two-dimensional synthesis filter coefficients in a predetermined band component, and, recursively according to the number of times which is band-divided, per set priority, the The band component is bit-shifted by the number of bits corresponding to the priority, and a truncation point that matches the target code amount is generated from a code string generated by rearranging the bit-shifted encoded data of the band component in a predetermined scanning order. And a code amount control unit for controlling to output the code string before the truncation point,
A code amount control apparatus comprising: The code amount control device according to claim 5,
The code amount control unit rearranges the encoded data in the order of higher priority and in the same priority, in the scanning order from the high frequency side to the low frequency side to generate the code string. Code amount control device. The code amount control device according to any one of claims 1 to 6,
For each band component of the compressed image data, the band component is bit-shifted by the number of bits corresponding to the priority set according to the number of times the band is recursively divided into the low-frequency component, and the bit A layer division control unit for controlling the shifted band component to be divided into a plurality of layers;
A code amount control device further comprising: The code amount control device according to claim 7,
The layer division control unit has a function of using the priority weighted in consideration of human visual characteristics. The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform A program for controlling
Among the respective band components of the compressed image data, based on the norm of the two-dimensional synthesis filter coefficients in a predetermined band component, and, recursively according to the number which has been band-split, per set priority, the As an image quality control unit that bit-shifts the band component by the number of bits corresponding to the priority, and selects an encoding target in accordance with the target image quality from the band-shifted band component,
A program characterized by causing a microprocessor to function. The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform A program for controlling
For each band component of the compressed image data, the band component is bit-shifted by the number of bits corresponding to the priority set according to the number of times the band is recursively divided into the low-frequency component, and the bit As an image quality control unit that selects an encoding target in accordance with the target image quality from the shifted band component,
Make the microprocessor work,
The image quality control unit, a program in which said to function the microprocessor to use the priority that has been weighted in consideration of human visual characteristics.   The program according to claim 9 or 10, wherein the image quality control unit causes the microprocessor to function so as to determine the encoding target in units of the bit planes.   The program according to claim 9, wherein the image quality control unit causes the microprocessor to function so as to determine the encoding target in units of the encoding pass. The amount of code of compressed image data that is compressed by entropy encoding the transform coefficient by calculating the transform coefficient of multiple band components by recursively dividing the image signal into high and low frequency components by wavelet transform A program for controlling
Among the respective band components of the compressed image data, based on the norm of the two-dimensional synthesis filter coefficients in a predetermined band component, and, recursively according to the number of times which is band-divided, per set priority, the The band component is bit-shifted by the number of bits corresponding to the priority, and a truncation point that matches the target code amount is generated from a code string generated by rearranging the bit-shifted encoded data of the band component in a predetermined scanning order. As a code amount control unit that controls to output the code string before the truncation point,
A program characterized by causing a microprocessor to function. 14. The program according to claim 13, wherein
The code amount control unit rearranges the encoded data in the order of higher priority and in the same priority, in the scanning order from the high frequency side to the low frequency side to generate the code string. A program for causing the microprocessor to function. The program according to any one of claims 9 to 14,
For each band component of the compressed image data, the band component is bit-shifted by the number of bits corresponding to the priority set according to the number of times the band is recursively divided into the low-frequency component, and the bit As a layer division control unit for controlling the shifted band component to be divided into a plurality of layers,
A program for causing the microprocessor to function.   16. The program according to claim 15, wherein the layer division control unit causes the microprocessor to function so as to use the priority weighted in consideration of human visual characteristics.

Images