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libkdcraw/dcrawsettingswidget.cpp:258
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libkdcraw/dcrawsettingswidget.cpp:259
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libkdcraw/dcrawsettingswidget.cpp:262
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libkdcraw/dcrawsettingswidget.cpp:263
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libkdcraw/dcrawsettingswidget.cpp:264
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libkdcraw/dcrawsettingswidget.cpp:265
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libkdcraw/dcrawsettingswidget.cpp:266
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libkdcraw/dcrawsettingswidget.cpp:267
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libkdcraw/dcrawsettingswidget.cpp:268
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20.
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<title>Quality (interpolation)</title><para>Select here the demosaicing method to use when decoding RAW images. A demosaicing algorithm is a digital image process used to interpolate a complete image from the partial raw data received from the color-filtered image sensor, internal to many digital cameras, in form of a matrix of colored pixels. Also known as CFA interpolation or color reconstruction, another common spelling is demosaicing. The following methods are available for demosaicing RAW images:</para><para><list><item><emphasis strong='true'>Bilinear</emphasis>: use high-speed but low-quality bilinear interpolation (default - for slow computers). In this method, the red value of a non-red pixel is computed as the average of the adjacent red pixels, and similarly for blue and green.</item><item><emphasis strong='true'>VNG</emphasis>: use Variable Number of Gradients interpolation. This method computes gradients near the pixel of interest and uses the lower gradients (representing smoother and more similar parts of the image) to make an estimate.</item><item><emphasis strong='true'>PPG</emphasis>: use Patterned-Pixel-Grouping interpolation. Pixel Grouping uses assumptions about natural scenery in making estimates. It has fewer color artifacts on natural images than the Variable Number of Gradients method.</item><item><emphasis strong='true'>AHD</emphasis>: use Adaptive Homogeneity-Directed interpolation. This method selects the direction of interpolation so as to maximize a homogeneity metric, thus typically minimizing color artifacts.</item><item><emphasis strong='true'>DCB</emphasis>: DCB interpolation from linuxphoto.org project.</item><item><emphasis strong='true'>AHD v2</emphasis>: modified AHD interpolation using Variance of Color Differences method.</item><item><emphasis strong='true'>AFD</emphasis>: Adaptive Filtered Demosaicing interpolation through 5 pass median filter from PerfectRaw project.</item><item><emphasis strong='true'>VCD</emphasis>: Variance of Color Differences interpolation.</item><item><emphasis strong='true'>VCD & AHD</emphasis>: Mixed demosaicing between VCD and AHD.</item><item><emphasis strong='true'>LMMSE</emphasis>: color demosaicing via directional linear minimum mean-square error estimation interpolation from PerfectRaw.</item><item><emphasis strong='true'>AMaZE</emphasis>: Aliasing Minimization interpolation and Zipper Elimination to apply color aberration removal from RawTherapee project.</item></list></para>
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<p><b>品質（內插）</b></p><p>在此選擇反馬賽克原始影像解壓內插法。反馬賽克演算法是一種數位影像處理法，用於內插一完整的影像，從內部的色彩過濾影像感知器接收到的部份的原始資料，到許多數位相機的顏色像素矩陣。又稱為 CFA 內插法，或色彩重建。以下方法可將原始影像做反馬賽克處理：</p><p><b>雙線性</b>：使用高速但低品質的雙線性內插（預設值，給慢速電腦使用）。在此方法中，非紅像素的紅值會被計算為相鄰紅像素的平均值，藍跟綠值也是比照辦理。</p><p><b>VNG</b>：使用 VNG（Variable Number of Gradients）內插法。此方法會計算像素週邊的漸層，使用較低的漸層來估計。</p><p><b>PPG</b>：使用 PPG（Patterned Pixel Grouping）內插法。此法使用一般的自然景色做估計。對自然影像來說，使用此法比用 VNG 更能呈現自然的樣式。 </p><p><b>AHD</b>：使用 AHD（Adaptive Homogeneity-Directed）內插法。此法選擇內插的方向，以便將同質矩陣最大化，通常可以將人造色彩降到最低。 </p><p><b>DCB</b>: linuxphoto.org 專案裡的 DCB 內插法。</p><p><b>AHD v2</b>: AHD 內插法的變更版，使用 Variance of Color Differences 內插法。</p><p><b>AFD</b>: Adaptive Filtered Demosaicing 內插法，從 PerfectRaw 專案而來，經過五道中途過濾手續。</p><p><b>VCD</b>: Variance of Color Differences 內插法。</p><p><b>VCD & AHD</b>: VCD 與 AHD 混合版。</p><p><b>LMMSE</b>: 透過「方向性最小平均平方誤差估計內插法」（directional linear minimum mean-square error estimation interpolation）做顏色反馬賽克。從 PerfectRaw 專案而來。</p><p><b>AMaZE</b>: Aliasing Minimization interpolation and Zipper Elimination，從 RawTherapee 專案而來，用於移除反常的顏色。</p>
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libkdcraw/dcrawsettingswidget.cpp:271
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