2 2. Fig.2. Schematic flow of proposed method. 2 DIC Technical Review No.2 / 26
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1 Realtime Color Appearance Processing for Images with High Dynamic Range ISHIHARA Daisuke, ISHII Toru, TSUMURA Norimichi, NAKAGUCHI Toshiya, SHISHIKURA Masami and MIYAKE Yoichi With the recently progress of 3-D Computer Graphics techniques, the use of virtual prototyping has increased in a product design process for automobile, consumer electronics, package, etc. A function of the virtual prototyping is to reproduce a virtual product image with real color and feel of a material (Shitsukan). When virtual product images are rendered with various lighting environments, an appearance model is necessary to predict how the human visual system (HVS) perceives the color and the Shitsukan of an object under different lighting conditions. CIECAM2 and icam are conventional appearance models. The CIECAM2 is a color appearance model and it does not support photographic data and high dynamic range (HDR) data to reproduce virtual product images in real scenes, e.g., under sunlight, indoor light, and shade. The icam is suggested as an improved model of the CIECAM2 to support photographic data and HDR data. However, this model cannot always accurately predict the HVS perception. We propose a color and Shitsukan reproduction technique with an appearance model for the HDR data by expanding the CIECAM2, and develop a realtime rendering application on a graphic hardware (GPU). As a result of subjective evaluation for still images and interactive images, our reproduction technique predicted the HVS perception more accurate than the icam. Fig. Shitsukan Representation System Ver.23. DIC Technical Review No.2 / 26
2 2 2. Fig.2. Schematic flow of proposed method. 2 DIC Technical Review No.2 / 26
3 報 文 Fig.3 Averaging area to calculate Yb and S. 2.2 光源情報による順応白色点の算出 CIECAM2では 入力値としてシーンの順応白色点の 三刺激値が必要である 本研究で対象とする質感表現 without color appearance model システムでは光源情報が既知であるため 各画素の光 proposed method Fig.4 Implementation result of realtime rendering. 源照度を求めることで順応白色点の三刺激値とする 2.3 フィルムカメラを想定した視野角の算出 CIECAM2では 視野角から決定される値Yb Sを 周囲の影響パラメータとして入力値に定めている 本 することで 画像に対する視野角の算出を行う フィ.9.8 ルムサイズをS film 焦点距離をF 画像の最大画素数 をP 画像の中心からの距離をD p i,j とすると 画 像の中心を注視点としたときの視野角θは式 3 に より算出される 3 手法では フィルムカメラによるシーンの撮影を想定 Fig.3は画像内の画素を注視点としたときのYb Sの算 出の様子である Ybは視野角2 の領域の平均輝度 Sは視野角 以上の領域の平均輝度を示している 式 3 で得られた視野角θを用いることで 各画 2 3 T 5 2 F Fig.5 Still image using proposed method for color appearance model. 素を注視点としたときのYb Sの視野角の領域を決定 し 領域内に含まれる画素のYの平均値からYb Sの 算出を行う 本研究ではYb Sのフィルタをそれぞれ 作成し 画像との畳み込み積分を行うことで 各画素 におけるYb Sの算出を行った 2.4 LAの算出 LAは シーンの順応輝度を表す値である 本研究で はシーン全体でLAを一定とし シーンの照度から輝度 を算出し その値の2%を順応輝度と想定することで L Aの算出を行う 照明を完全拡散照明とし 照度を E[lux] 輝度をL[cd/m2]とすると LAは式 4 により 算出される /4 /8 /6 /4 /8 /6 /4 /8 /6 /4 WhitePoint=XYZ /8 /6.5. D WhitePoint=YYY Fig.6 Still image using icam for color appearance model. DIC Technical Review No.2 / 26 3
4 報 文 4. 主観評価結果に対する考察 3 GPUによる提案手法の実装 本研究ではリアルタイムな色順応処理 動きを伴っ Fig.5 8から 静止画 GPUともに提案手法の方が た質感再現を実現するためGPUによる提案手法の実装 icamよりも全体的に評価が高いことから本手法の有効 を行った 本手法では各画素においてCIECAM2の入 性を確認することができる Fig.5を見ると Fの値により 力値を算出しているため 画素単位で処理を行うこ 評価が下がっているのがわかる これはYbの影響によ とが可能である また 処理過程はYb S算出以外で り光沢部の周辺が暗く再現される現象 halo が発生し 全て線形演算であるため GPUによる高速演算が可能 ているためだと考えられる YbはCIECAM2の処理で であり リアルタイムな色順応処理を実現した Fig.4 明度に影響を与えるパラメータで 値が高いほど明度は はGPUにより提案手法の実装を行った結果である 下がる Fが5 のとき Ybの領域は飲料缶の光沢とほ ぼ同じ大きさになり Ybの値が高くなることでhaloが強く 4 主観評価実験 表れたと考えられる Fig.7を見ると Fig.5に比べFによ 主観評価実験は HDR画像の静止画 GPUの2パター る評価値の低下は見られないことがわかる これは ンで行った 被験者人に提案手法 icamの処理画 GPUによりインタラクティブな操作が可能となり haloの 像をランダムに見せ5段階の系列範疇法により評価しても 影響だけでなくデザインの色味や 光沢部の再現を総合 らう 得られた評価結果から提案手法とiCAMの比較検 的に評価することで 評価値に対するhaloの影響の割合 証 任意パラメータの最適値を決定する 静止画は提案 が低下したためだと考えられる 手法35枚 icam36枚の計7枚 GPUは提案手法2枚 5 まとめ icam8枚の計39枚の評価画像を使用した 本研究では CIECAM2の入力値を拡張し GPUに よる提案手法の実装を行うことで HDR画像に対する インタラクティブな環境によるCIECAM2処理を実現.9.8 した GPUによる主観評価実験では インタラクティ ブな操作が可能になったことで評価基準に変化が見ら れた この結果は 画像評価において動き情報が重要 な役割を持つと考えられ 今後のGPU処理の重要性を 示しているといえる 本稿は 25年電子情報通信学会総合大会における同 T 8 5 F 名の発表 発表No.AS-7-9 を基に 本誌用に加筆し たものである Fig.7 Realtime rendering using proposed method for color appearance model. 参照文献 N. Moroney, M.D. Fairchild, R.W.G. Hunt, C.J Li, M.R. Luo, and T. Newman, The CIECAM2 color.9 appearance model, IS&T/SID th Color Imaging.8 Conference, Scottsdale, Fairchild, Johnson "The icam framework for image.5 appearance, image differences, and image quality".4 Journal of Electronic Imaging, in press Erik Reinhard, Michael Stark, Peter Shirley, James.2. Ferwerda, "Photographic Tone Reproduction for Digital /4 /8 /6.5 /4 Filter Size /8 /6 Images" SIGGRAPH 22. Fig.8 Realtime rendering using icam for color appearance model. 4 DIC Technical Review No.2 / 26
5 ISHIHARA Daisuke ISHII Toru TSUMURA Norimichi NAKAGUCHI Toshiya SHISHIKURA Masami MIYAKE Yoichi DIC Technical Review No.2 / 26 5
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す 局所領域 ωk において 線形変換に用いる係数 (ak 画素の係数 (ak bk ) を算出し 入力画像の信号成分を bk ) は次式のコスト関数 E を最小化するように最適化 有さない画素に対して 式 (2) より画素値を算出する される これにより 低解像度な画像から補間によるアップサ E(
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(2001) 49 2 333 343 Java Jasp 1 2 3 4 2001 4 13 2001 9 17 Java Jasp (JAva based Statistical Processor) Jasp Jasp. Java. 1. Jasp CPU 1 106 8569 4 6 7; fuji@ism.ac.jp 2 106 8569 4 6 7; nakanoj@ism.ac.jp
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