Revision 8840ce92 doc/swscale.txt

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doc/swscale.txt
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                         output
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Swscale has 2 scaler pathes, each side must be capable to handle
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Swscale has 2 scaler paths, each side must be capable to handle
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slices, that is consecutive non overlapping rectangles of dimension
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(0,slice_top) - (picture_width, slice_bottom)
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    When the input to the main path is not planar 8bit per component yuv or
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    8bit gray then it is converted to planar 8bit YUV, 2 sets of converters
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    exist for this currently one performing horizontal downscaling by 2
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    before the convertion and the other leaving the full chroma resolution
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    before the conversion and the other leaving the full chroma resolution
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    but being slightly slower. The scaler will try to preserve full chroma
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    here when the output uses it, its possible to force full chroma with
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    SWS_FULL_CHR_H_INP though even for cases where the scaler thinks its
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Horizontal scaler
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    There are several horizontal scalers, a special case worth mentioning is
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    the fast bilinear scaler that is made of runtime generated mmx2 code
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    the fast bilinear scaler that is made of runtime generated MMX2 code
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    using specially tuned pshufw instructions.
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    The remaining scalers are specially tuned for various filter lengths
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    they scale 8bit unsigned planar data to 16bit signed planar data.
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    Future >8bit per component inputs will need to add a new scaler here
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    that preserves the input precission.
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    that preserves the input precision.
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Vertical scaler and output converter
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    There is a large number of combined vertical scalers+output converters
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--------------------
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There are several different scalers (bilinear, bicubic, lanczos, area, sinc, ...)
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Their coefficients are calculated in initFilter().
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Horinzontal filter coeffs have a 1.0 point at 1<<14, vertical ones at 1<<12.
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The 1.0 points have been choosen to maximize precission while leaving a
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Horizontal filter coeffs have a 1.0 point at 1<<14, vertical ones at 1<<12.
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The 1.0 points have been chosen to maximize precision while leaving a
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little headroom for convolutional filters like sharpening filters and
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minimizing SIMD instructions needed to apply them.
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It would be trivial to use a different 1.0 point if some specific scaler

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