better vips_resize() for cubic/linear/nearest
vips_resize() used to do most of a downsize with vips_shrink() and the final 200 - 300% with vips_reduce(). This was correct for lanczos2/3, but not right for linear/cubic, which need more shrink and less reduce to avoid aliasing. This patch makes vips_resize() leave the final 100 - 200% to vips_reduce() for linear/cubic, and leave everything to reduce for nearest.
This commit is contained in:
John Cupitt
parent
a5bef08d4a
commit
f3326c8126
@ -24,6 +24,7 @@
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- added C++ arithmetic assignment overloads, += etc.
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- VImage::ifthenelse() with double args was missing =0 on options
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- better accuracy for reducev with smarter multiplication
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- better quality for vips_resize() with linear/cubic kernels
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18/5/16 started 8.3.2
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- more robust vips image reading
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20
TODO
20
TODO
@ -1,23 +1,3 @@
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- try:
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$ vips black x.v 10 10
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$ vips reducev x.v x2.v 2
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$ vips avg x2.v
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1.000000
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argh!
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reduceh seems OK
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$ vips reducev x.v x2.v 2 --vips-novector
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$ vips avg x2.v
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0.000000
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also OK ... just the vector path
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- add more reducev tests ... resize constant 255 and constant 0 image, with and
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without vector
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- add more webp tests to py suite
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- try moving some more of the CLI tests to py
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@ -559,11 +559,10 @@ vips_reduceh_init( VipsReduceh *reduceh )
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*
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* Optional arguments:
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*
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* @kernel: #VipsKernel to use to interpolate (default: lanczos3)
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* * @kernel: #VipsKernel to use to interpolate (default: lanczos3)
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*
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* Reduce @in horizontally by a float factor. The pixels in @out are
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* interpolated with a 1D mask. This operation will not work well for
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* a reduction of more than a factor of two.
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* interpolated with a 1D mask.
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*
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* This is a very low-level operation: see vips_resize() for a more
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* convenient way to resize images.
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@ -41,6 +41,8 @@
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*/
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/*
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#define DEBUG_PIXELS
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#define DEBUG_COMPILE
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#define DEBUG
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*/
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@ -163,9 +165,9 @@ vips_reducev_compile_section( VipsReducev *reducev, Pass *pass, gboolean first )
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VipsVector *v;
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int i;
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#ifdef DEBUG
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#ifdef DEBUG_COMPILE
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printf( "starting pass %d\n", pass->first );
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#endif /*DEBUG*/
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#endif /*DEBUG_COMPILE*/
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pass->vector = v = vips_vector_new( "reducev", 1 );
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@ -270,10 +272,10 @@ vips_reducev_compile_section( VipsReducev *reducev, Pass *pass, gboolean first )
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if( !vips_vector_compile( v ) )
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return( -1 );
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#ifdef DEBUG
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#ifdef DEBUG_COMPILE
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printf( "done coeffs %d to %d\n", pass->first, pass->last );
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vips_vector_print( v );
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#endif /*DEBUG*/
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#endif /*DEBUG_COMPILE*/
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return( 0 );
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}
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@ -623,10 +625,10 @@ vips_reducev_vector_gen( VipsRegion *out_region, void *vseq,
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VipsExecutor executor[MAX_PASS];
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VipsRect s;
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#ifdef DEBUG
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#ifdef DEBUG_PIXELS
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printf( "vips_reducev_vector_gen: generating %d x %d at %d x %d\n",
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r->width, r->height, r->left, r->top );
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#endif /*DEBUG*/
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#endif /*DEBUG_PIXELS*/
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s.left = r->left;
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s.top = r->top * reducev->yshrink;
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@ -635,10 +637,10 @@ vips_reducev_vector_gen( VipsRegion *out_region, void *vseq,
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if( vips_region_prepare( ir, &s ) )
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return( -1 );
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#ifdef DEBUG
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#ifdef DEBUG_PIXELS
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printf( "vips_reducev_vector_gen: preparing %d x %d at %d x %d\n",
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s.width, s.height, s.left, s.top );
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#endif /*DEBUG*/
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#endif /*DEBUG_PIXELS*/
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for( int i = 0; i < reducev->n_pass; i++ )
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vips_executor_set_program( &executor[i],
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@ -656,7 +658,7 @@ vips_reducev_vector_gen( VipsRegion *out_region, void *vseq,
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const int ty = (siy + 1) >> 1;
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const int *cyo = reducev->matrixo[ty];
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#ifdef DEBUG
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#ifdef DEBUG_PIXELS
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printf( "starting row %d\n", y + r->top );
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printf( "coefficients:\n" );
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for( int i = 0; i < reducev->n_point; i++ )
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@ -665,7 +667,7 @@ vips_reducev_vector_gen( VipsRegion *out_region, void *vseq,
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for( int i = 0; i < reducev->n_point; i++ )
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printf( "\t%d - %d\n", i,
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*VIPS_REGION_ADDR( ir, r->left, r->top + y + i ) );
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#endif /*DEBUG*/
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#endif /*DEBUG_PIXELS*/
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/* We run our n passes to generate this scanline.
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*/
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@ -687,10 +689,10 @@ vips_reducev_vector_gen( VipsRegion *out_region, void *vseq,
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VIPS_SWAP( signed short *, seq->t1, seq->t2 );
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}
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#ifdef DEBUG
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#ifdef DEBUG_PIXELS
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printf( "pixel result:\n" );
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printf( "\t%d\n", *q );
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#endif /*DEBUG*/
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#endif /*DEBUG_PIXELS*/
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}
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VIPS_GATE_STOP( "vips_reducev_vector_gen: work" );
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@ -964,11 +966,10 @@ vips_reducev_init( VipsReducev *reducev )
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*
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* Optional arguments:
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*
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* @kernel: #VipsKernel to use to interpolate (default: lanczos3)
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* * @kernel: #VipsKernel to use to interpolate (default: lanczos3)
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*
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* Reduce @in vertically by a float factor. The pixels in @out are
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* interpolated with a 1D mask. This operation will not work well for
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* a reduction of more than a factor of two.
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* interpolated with a 1D mask.
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*
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* This is a very low-level operation: see vips_resize() for a more
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* convenient way to resize images.
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@ -13,6 +13,9 @@
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* 1/5/16
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* - allow >1 on one axis, <1 on the other
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* - expose @kernel setting
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* 16/6/16
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* - better quality for linear/cubic kernels ... do more shrink and less
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* reduce
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*/
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/*
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@ -84,6 +87,43 @@ typedef VipsResampleClass VipsResizeClass;
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G_DEFINE_TYPE( VipsResize, vips_resize, VIPS_TYPE_RESAMPLE );
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/* How much of a scale should be by an integer shrink factor?
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*
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* This depends on the scale and the kernel we will use for residual resizing.
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* For upsizing and nearest-neighbour downsize, we want no shrinking.
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*
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* Linear and cubic are fixed-size kernels and for a 0 offset are point
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* samplers. We will get aliasing if we do more than a x2 shrink with them.
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*
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* Lanczos is adaptive: the size of the kernel changes with the shrink factor.
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* We will get the best quality (but be the slowest) if we let reduce do all
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* the work. Leave it the final 200 - 300% to do as a compromise for
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* efficiency.
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*
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* FIXME: this is rather ugly. Kernel should be a class and this info should be
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* stored in there.
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*/
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static int
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vips_resize_int_shrink( VipsResize *resize, double scale )
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{
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if( scale > 1.0 )
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return( 1 );
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switch( resize->kernel ) {
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case VIPS_KERNEL_NEAREST:
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return( 1 );
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case VIPS_KERNEL_LINEAR:
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case VIPS_KERNEL_CUBIC:
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default:
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return( VIPS_FLOOR( 1.0 / scale ) );
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case VIPS_KERNEL_LANCZOS2:
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case VIPS_KERNEL_LANCZOS3:
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return( VIPS_MAX( 1, VIPS_FLOOR( 1.0 / (resize->scale * 2) ) ) );
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}
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}
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static int
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vips_resize_build( VipsObject *object )
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{
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@ -114,25 +154,9 @@ vips_resize_build( VipsObject *object )
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else
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target_height = in->Ysize * resize->scale;
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/* If the factor is > 1.0, we need to zoom rather than shrink.
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* Just set the int part to 1 in this case.
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*/
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/* We want the int part of the shrink to leave a bit to do with
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* blur/reduce/sharpen, or we'll see strange changes in aliasing on int
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* shrink boundaries as we resize.
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*/
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if( resize->scale > 1.0 )
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int_hshrink = 1;
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else
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int_hshrink = VIPS_FLOOR( 1.0 / (resize->scale * 2) );
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if( vips_object_argument_isset( object, "vscale" ) ) {
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if( resize->vscale > 1.0 )
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int_vshrink = 1;
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else
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int_vshrink = VIPS_FLOOR( 1.0 / (resize->vscale * 2) );
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}
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int_hshrink = vips_resize_int_shrink( resize, resize->scale );
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if( vips_object_argument_isset( object, "vscale" ) )
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int_vshrink = vips_resize_int_shrink( resize, resize->vscale );
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else
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int_vshrink = int_hshrink;
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@ -334,21 +358,21 @@ vips_resize_init( VipsResize *resize )
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*
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* Optional arguments:
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*
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* * @vscale: vertical scale factor
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* * @vscale: %gdouble vertical scale factor
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* * @kernel: #VipsKernel to reduce with
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*
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* Resize an image. When upsizing (@scale > 1), the image is simply block
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* upsized. When downsizing, the
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* image is block-shrunk with vips_shrink(),
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* then the image is shrunk again to the
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* target size with vips_reduce(). The operation will leave at least the final
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* x2 to be done with vips_reduce().
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* target size with vips_reduce(). How much is done by vips_shrink() vs.
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* vips_reduce() varies with the @kernel setting.
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*
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* vips_resize() normally maintains the image apect ratio. If you set
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* @vscale, that factor is used for the vertical scale and @scale for the
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* horizontal.
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*
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* vips_resize() normally uses #VIPS_KERNEL_LANCZOS3 for thre final shrink, you
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* vips_resize() normally uses #VIPS_KERNEL_LANCZOS3 for the final shrink, you
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* can change this with @kernel.
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*
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* This operation does not change xres or yres. The image resolution needs to
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@ -435,10 +435,8 @@ vips_shrinkv_init( VipsShrinkv *shrink )
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* Shrink @in vertically by an integer factor. Each pixel in the output is
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* the average of the corresponding column of @yshrink pixels in the input.
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*
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* You will get aliasing for non-integer shrinks. In this case, shrink with
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* this function to the nearest integer size above the target shrink, then
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* downsample to the exact size with vips_affine() and your choice of
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* interpolator. See vips_resize() for a convenient way to do this.
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* This is a very low-level operation: see vips_resize() for a more
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* convenient way to resize images.
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*
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* This operation does not change xres or yres. The image resolution needs to
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* be updated by the application.
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