faster, more accurate bilinear/bicubic
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John Cupitt
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32f481d524
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7fd672f595
@ -9,6 +9,8 @@
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- all "colour" in messages changed to "color", have a proper en_GB
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translation file
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- vipsthumbnail delete profile failed if there was a profile
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- interpolate cli unref was broken
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- more accurate, slightly faster bilinear and bicubic (thanks Nicolas)
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21/3/10 started 7.21.3
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- added progress feedback to threadpool
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98
TODO
98
TODO
@ -1,103 +1,5 @@
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mask selection seems reasonable:
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vips_interpolate_bicubic_interpolate: 2 2
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left=1, top=1, width=4, height=4
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maskx=0, masky=0
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vips_interpolate_bicubic_interpolate: 2.1 2
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left=1, top=1, width=4, height=4
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maskx=3, masky=0
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vips_interpolate_bicubic_interpolate: 2.2 2
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left=1, top=1, width=4, height=4
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maskx=6, masky=0
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vips_interpolate_bicubic_interpolate: 2.3 2
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left=1, top=1, width=4, height=4
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maskx=9, masky=0
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vips_interpolate_bicubic_interpolate: 2.4 2
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left=1, top=1, width=4, height=4
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maskx=12, masky=0
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vips_interpolate_bicubic_interpolate: 2.5 2
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left=1, top=1, width=4, height=4
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maskx=16, masky=0
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vips_interpolate_bicubic_interpolate: 2.6 2
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left=1, top=1, width=4, height=4
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maskx=19, masky=0
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vips_interpolate_bicubic_interpolate: 2.7 2
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left=1, top=1, width=4, height=4
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maskx=22, masky=0
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vips_interpolate_bicubic_interpolate: 2.8 2
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left=1, top=1, width=4, height=4
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maskx=25, masky=0
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vips_interpolate_bicubic_interpolate: 2.9 2
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left=1, top=1, width=4, height=4
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maskx=28, masky=0
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vips_interpolate_bicubic_interpolate: 3 2
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left=2, top=1, width=4, height=4
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maskx=0, masky=0
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so for (eg.) 2.4 we pick mask 12, which is (12 / 32), or 0.375
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however, mask13 would be closer: 13 / 32) = 0.4076
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calculation is
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2.4 * 32 == 76.8
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FLOOR(76.8) == 76
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76 & 31 == 12
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vips_interpolate_bicubic_class_init:
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mask = 0, calculate_coefficients_catmull: 0
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mask = 1, calculate_coefficients_catmull: 0.03125
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mask = 2, calculate_coefficients_catmull: 0.0625
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mask = 3, calculate_coefficients_catmull: 0.09375
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mask = 4, calculate_coefficients_catmull: 0.125
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mask = 5, calculate_coefficients_catmull: 0.15625
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mask = 6, calculate_coefficients_catmull: 0.1875
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mask = 7, calculate_coefficients_catmull: 0.21875
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mask = 8, calculate_coefficients_catmull: 0.25
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mask = 9, calculate_coefficients_catmull: 0.28125
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mask = 10, calculate_coefficients_catmull: 0.3125
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mask = 11, calculate_coefficients_catmull: 0.34375
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mask = 12, calculate_coefficients_catmull: 0.375
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mask = 13, calculate_coefficients_catmull: 0.40625
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mask = 14, calculate_coefficients_catmull: 0.4375
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mask = 15, calculate_coefficients_catmull: 0.46875
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mask = 16, calculate_coefficients_catmull: 0.5
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mask = 17, calculate_coefficients_catmull: 0.53125
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mask = 18, calculate_coefficients_catmull: 0.5625
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mask = 19, calculate_coefficients_catmull: 0.59375
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mask = 20, calculate_coefficients_catmull: 0.625
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mask = 21, calculate_coefficients_catmull: 0.65625
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mask = 22, calculate_coefficients_catmull: 0.6875
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mask = 23, calculate_coefficients_catmull: 0.71875
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mask = 24, calculate_coefficients_catmull: 0.75
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mask = 25, calculate_coefficients_catmull: 0.78125
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mask = 26, calculate_coefficients_catmull: 0.8125
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mask = 27, calculate_coefficients_catmull: 0.84375
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mask = 28, calculate_coefficients_catmull: 0.875
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mask = 29, calculate_coefficients_catmull: 0.90625
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mask = 30, calculate_coefficients_catmull: 0.9375
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mask = 31, calculate_coefficients_catmull: 0.96875
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mask = 32, calculate_coefficients_catmull: 1
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- tools subdirs are now pretty stupid :-( just have a single dir
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- int bicubic needs more precision? try a 10x upscale and compare to the
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double path
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yes, looks like a rounding problem?
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upscale 10x, you get a small offset if you compare the double and int paths
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and slight banding
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- test
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python setup.py build_ext
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@ -96,7 +96,7 @@ int vips_interpolate_get_window_offset( VipsInterpolate *interpolate );
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/* How many bits of precision we keep for transformations, ie. how many
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* pre-computed matricies we have.
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*/
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#define VIPS_TRANSFORM_SHIFT (2)
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#define VIPS_TRANSFORM_SHIFT (6)
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#define VIPS_TRANSFORM_SCALE (1 << VIPS_TRANSFORM_SHIFT)
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/* How many bits of precision we keep for interpolation, ie. where the decimal
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@ -894,11 +894,19 @@ input_interpolate_init( im_object *obj, char *str )
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return( 0 );
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}
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static int
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input_interpolate_dest( im_object obj )
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{
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g_object_unref( (GObject *) obj );
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return( 0 );
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}
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im_type_desc im__input_interpolate = {
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IM_TYPE_INTERPOLATE,
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0, /* No storage required */
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IM_TYPE_ARG, /* It requires a command-line arg */
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(im_init_obj_fn) input_interpolate_init,/* Init function */
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(im_dest_obj_fn) g_object_unref /* Destroy function */
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input_interpolate_init, /* Init function */
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input_interpolate_dest /* Destroy function */
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};
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@ -302,23 +302,24 @@ static void
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vips_interpolate_bicubic_interpolate( VipsInterpolate *interpolate,
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PEL *out, REGION *in, double x, double y )
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{
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/* Scaled int.
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/* Find the mask index. We round-to-nearest, so we need to generate
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* indexes in 0 to VIPS_TRANSFORM_SCALE, 2^n + 1 values. We multiply
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* by 2 more than we need to, add one, mask, then shift down again to
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* get the extra range.
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*/
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const double sx = x * VIPS_TRANSFORM_SCALE;
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const double sy = y * VIPS_TRANSFORM_SCALE;
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const int sx = x * VIPS_TRANSFORM_SCALE * 2;
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const int sy = y * VIPS_TRANSFORM_SCALE * 2;
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/* We know sx/sy are always positive, so we can just (int) them.
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*/
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const int sxi = (int) sx;
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const int syi = (int) sy;
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const int six = sx & (VIPS_TRANSFORM_SCALE * 2 - 1);
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const int siy = sy & (VIPS_TRANSFORM_SCALE * 2 - 1);
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/* Get index into interpolation table and unscaled integer
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* position.
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const int tx = (six + 1) >> 1;
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const int ty = (siy + 1) >> 1;
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/* We know x/y are always positive, so we can just (int) them.
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*/
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const int tx = sxi & (VIPS_TRANSFORM_SCALE - 1);
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const int ty = syi & (VIPS_TRANSFORM_SCALE - 1);
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const int ix = sxi >> VIPS_TRANSFORM_SHIFT;
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const int iy = syi >> VIPS_TRANSFORM_SHIFT;
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const int ix = (int) x;
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const int iy = (int) y;
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/* Look up the tables we need.
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*/
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@ -325,15 +325,16 @@ static float vips_bilinear_matrixd
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* p3 p4
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*/
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/* Interpolate a section ... int8/16 types.
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/* Interpolate a section ... int8/16 types, lookup tables for interpolation
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* factors, fixed-point arithmetic.
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*/
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#define BILINEAR_INT( TYPE ) { \
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TYPE *tq = (TYPE *) out; \
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\
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const int c1 = vips_bilinear_matrixi[xi][yi][0]; \
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const int c2 = vips_bilinear_matrixi[xi][yi][1]; \
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const int c3 = vips_bilinear_matrixi[xi][yi][2]; \
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const int c4 = vips_bilinear_matrixi[xi][yi][3]; \
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const int c1 = vips_bilinear_matrixi[tx][ty][0]; \
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const int c2 = vips_bilinear_matrixi[tx][ty][1]; \
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const int c3 = vips_bilinear_matrixi[tx][ty][2]; \
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const int c4 = vips_bilinear_matrixi[tx][ty][3]; \
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\
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const TYPE *tp1 = (TYPE *) p1; \
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const TYPE *tp2 = (TYPE *) p2; \
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@ -345,15 +346,16 @@ static float vips_bilinear_matrixd
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c3 * tp3[z] + c4 * tp4[z]) >> VIPS_INTERPOLATE_SHIFT; \
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}
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/* Interpolate a pel ... int32 and float types.
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/* Interpolate a pel ... int32 and float types, lookup tables, float
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* arithmetic.
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*/
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#define BILINEAR_FLOAT( TYPE ) { \
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TYPE *tq = (TYPE *) out; \
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\
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const double c1 = vips_bilinear_matrixd[xi][yi][0]; \
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const double c2 = vips_bilinear_matrixd[xi][yi][1]; \
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const double c3 = vips_bilinear_matrixd[xi][yi][2]; \
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const double c4 = vips_bilinear_matrixd[xi][yi][3]; \
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const double c1 = vips_bilinear_matrixd[tx][ty][0]; \
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const double c2 = vips_bilinear_matrixd[tx][ty][1]; \
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const double c3 = vips_bilinear_matrixd[tx][ty][2]; \
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const double c4 = vips_bilinear_matrixd[tx][ty][3]; \
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\
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const TYPE *tp1 = (TYPE *) p1; \
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const TYPE *tp2 = (TYPE *) p2; \
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@ -393,25 +395,26 @@ vips_interpolate_bilinear_interpolate( VipsInterpolate *interpolate,
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const int ls = IM_REGION_LSKIP( in );
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const int b = in->im->Bands;
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/* Now go to scaled int.
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/* Find the mask index. We round-to-nearest, so we need to generate
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* indexes in 0 to VIPS_TRANSFORM_SCALE, 2^n + 1 values. We multiply
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* by 2 more than we need to, add one, mask, then shift down again to
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* get the extra range.
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*/
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const double sx = x * VIPS_TRANSFORM_SCALE;
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const double sy = y * VIPS_TRANSFORM_SCALE;
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const int sx = x * VIPS_TRANSFORM_SCALE * 2;
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const int sy = y * VIPS_TRANSFORM_SCALE * 2;
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/* We know sx/sy are always positive so we can just (int) them.
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const int six = sx & (VIPS_TRANSFORM_SCALE * 2 - 1);
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const int siy = sy & (VIPS_TRANSFORM_SCALE * 2 - 1);
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const int tx = (six + 1) >> 1;
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const int ty = (siy + 1) >> 1;
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/* We know x/y are always positive, so we can just (int) them.
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*/
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const int sxi = (int) sx;
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const int syi = (int) sy;
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const int ix = (int) x;
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const int iy = (int) y;
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/* Get index into interpolation table and unscaled integer
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* position.
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*/
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const int xi = sxi & (VIPS_TRANSFORM_SCALE - 1);
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const int yi = syi & (VIPS_TRANSFORM_SCALE - 1);
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const int x_int = sxi >> VIPS_TRANSFORM_SHIFT;
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const int y_int = syi >> VIPS_TRANSFORM_SHIFT;
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const PEL *p1 = (PEL *) IM_REGION_ADDR( in, x_int, y_int );
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const PEL *p1 = (PEL *) IM_REGION_ADDR( in, ix, iy );
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const PEL *p2 = p1 + ps;
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const PEL *p3 = p1 + ls;
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const PEL *p4 = p3 + ps;
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