mirror of https://github.com/axmolengine/axmol.git
520 lines
18 KiB
C++
520 lines
18 KiB
C++
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// ----------------------------------------------------------------------------
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// This confidential and proprietary software may be used only as authorised
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// by a licensing agreement from Arm Limited.
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// (C) COPYRIGHT 2011-2019 Arm Limited, ALL RIGHTS RESERVED
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// The entire notice above must be reproduced on all authorised copies and
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// copies may only be made to the extent permitted by a licensing agreement
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// from Arm Limited.
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// ----------------------------------------------------------------------------
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/**
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* @brief Functions to calculate variance per-pixel-channel in a NxN footprint.
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*
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* We want N to be parametric. The routine below uses summed area tables in
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* order to execute in O(1) time per pixel, independent of big N is.
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*/
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#include "astc_codec_internals.h"
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#include "softfloat.h"
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#include <stdio.h>
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float4 *** input_averages;
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float *** input_alpha_averages;
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float4 *** input_variances;
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// routine to compute averages and variances for a pixel region.
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// The routine computes both in a single pass, using a summed-area table
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// to decouple the running time from the averaging/variance kernel size.
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static void compute_pixel_region_variance(const astc_codec_image * img, float rgb_power_to_use, float alpha_power_to_use, swizzlepattern swz, int use_z_axis,
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int source_xoffset,int source_yoffset, int source_zoffset, // position of upper-left pixel in data set
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int xsize, int ysize, int zsize, // the size of the region to actually compute averages and variances for.
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int avg_var_kernel_radius, int alpha_kernel_radius,
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int dest_xoffset, int dest_yoffset, int dest_zoffset)
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{
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int x, y, z;
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int kernel_radius = MAX(avg_var_kernel_radius, alpha_kernel_radius);
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int kerneldim = 2 * kernel_radius + 1;
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// allocate memory
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int xpadsize = xsize + kerneldim;
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int ypadsize = ysize + kerneldim;
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int zpadsize = zsize + (use_z_axis ? kerneldim : 1);
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double4 ***varbuf1 = new double4 **[zpadsize];
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double4 ***varbuf2 = new double4 **[zpadsize];
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varbuf1[0] = new double4 *[ypadsize * zpadsize];
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varbuf2[0] = new double4 *[ypadsize * zpadsize];
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varbuf1[0][0] = new double4[xpadsize * ypadsize * zpadsize];
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varbuf2[0][0] = new double4[xpadsize * ypadsize * zpadsize];
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for (z = 1; z < zpadsize; z++)
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{
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varbuf1[z] = varbuf1[0] + ypadsize * z;
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varbuf2[z] = varbuf2[0] + ypadsize * z;
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varbuf1[z][0] = varbuf1[0][0] + xpadsize * ypadsize * z;
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varbuf2[z][0] = varbuf2[0][0] + xpadsize * ypadsize * z;
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}
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for (z = 0; z < zpadsize; z++)
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{
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for (y = 1; y < ypadsize; y++)
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{
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varbuf1[z][y] = varbuf1[z][0] + xpadsize * y;
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varbuf2[z][y] = varbuf2[z][0] + xpadsize * y;
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}
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}
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int powers_are_1 = (rgb_power_to_use == 1.0f) && (alpha_power_to_use == 1.0f);
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// load x and x^2 values into the allocated buffers
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if (img->imagedata8)
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{
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uint8_t data[6];
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data[4] = 0;
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data[5] = 255;
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for (z = 0; z < zpadsize - 1; z++)
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{
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int z_src = z + source_zoffset - (use_z_axis ? kernel_radius : 0);
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for (y = 0; y < ypadsize - 1; y++)
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{
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int y_src = y + source_yoffset - kernel_radius;
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for (x = 0; x < xpadsize - 1; x++)
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{
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int x_src = x + source_xoffset - kernel_radius;
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data[0] = img->imagedata8[z_src][y_src][4 * x_src + 0];
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data[1] = img->imagedata8[z_src][y_src][4 * x_src + 1];
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data[2] = img->imagedata8[z_src][y_src][4 * x_src + 2];
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data[3] = img->imagedata8[z_src][y_src][4 * x_src + 3];
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uint8_t r = data[swz.r];
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uint8_t g = data[swz.g];
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uint8_t b = data[swz.b];
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uint8_t a = data[swz.a];
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double4 d = double4(r * (1.0 / 255.0),
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g * (1.0 / 255.0),
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b * (1.0 / 255.0),
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a * (1.0 / 255.0));
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if (perform_srgb_transform)
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{
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d.x = (d.x <= 0.04045) ? d.x * (1.0 / 12.92) : (d.x <= 1) ? pow((d.x + 0.055) * (1.0 / 1.055), 2.4) : d.x;
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d.y = (d.y <= 0.04045) ? d.y * (1.0 / 12.92) : (d.y <= 1) ? pow((d.y + 0.055) * (1.0 / 1.055), 2.4) : d.y;
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d.z = (d.z <= 0.04045) ? d.z * (1.0 / 12.92) : (d.z <= 1) ? pow((d.z + 0.055) * (1.0 / 1.055), 2.4) : d.z;
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}
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if (!powers_are_1)
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{
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d.x = pow(MAX(d.x, 1e-6), (double)rgb_power_to_use);
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d.y = pow(MAX(d.y, 1e-6), (double)rgb_power_to_use);
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d.z = pow(MAX(d.z, 1e-6), (double)rgb_power_to_use);
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d.w = pow(MAX(d.w, 1e-6), (double)alpha_power_to_use);
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}
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varbuf1[z][y][x] = d;
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varbuf2[z][y][x] = d * d;
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}
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}
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}
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}
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else
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{
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uint16_t data[6];
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data[4] = 0;
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data[5] = 0x3C00; // 1.0 encoded as FP16.
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for (z = 0; z < zpadsize - 1; z++)
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{
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int z_src = z + source_zoffset - (use_z_axis ? kernel_radius : 0);
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for (y = 0; y < ypadsize - 1; y++)
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{
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int y_src = y + source_yoffset - kernel_radius;
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for (x = 0; x < xpadsize - 1; x++)
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{
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int x_src = x + source_xoffset - kernel_radius;
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data[0] = img->imagedata16[z_src][y_src][4 * x_src];
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data[1] = img->imagedata16[z_src][y_src][4 * x_src + 1];
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data[2] = img->imagedata16[z_src][y_src][4 * x_src + 2];
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data[3] = img->imagedata16[z_src][y_src][4 * x_src + 3];
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uint16_t r = data[swz.r];
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uint16_t g = data[swz.g];
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uint16_t b = data[swz.b];
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uint16_t a = data[swz.a];
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double4 d = double4(sf16_to_float(r),
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sf16_to_float(g),
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sf16_to_float(b),
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sf16_to_float(a));
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if (perform_srgb_transform)
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{
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d.x = (d.x <= 0.04045) ? d.x * (1.0 / 12.92) : (d.x <= 1) ? pow((d.x + 0.055) * (1.0 / 1.055), 2.4) : d.x;
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d.y = (d.y <= 0.04045) ? d.y * (1.0 / 12.92) : (d.y <= 1) ? pow((d.y + 0.055) * (1.0 / 1.055), 2.4) : d.y;
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d.z = (d.z <= 0.04045) ? d.z * (1.0 / 12.92) : (d.z <= 1) ? pow((d.z + 0.055) * (1.0 / 1.055), 2.4) : d.z;
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}
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if (!powers_are_1)
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{
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d.x = pow(MAX(d.x, 1e-6), (double)rgb_power_to_use);
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d.y = pow(MAX(d.y, 1e-6), (double)rgb_power_to_use);
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d.z = pow(MAX(d.z, 1e-6), (double)rgb_power_to_use);
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d.w = pow(MAX(d.w, 1e-6), (double)alpha_power_to_use);
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}
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varbuf1[z][y][x] = d;
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varbuf2[z][y][x] = d * d;
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}
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}
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}
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}
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// pad out buffers with 0s
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for (z = 0; z < zpadsize; z++)
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{
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for (y = 0; y < ypadsize; y++)
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{
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varbuf1[z][y][xpadsize - 1] = double4(0.0, 0.0, 0.0, 0.0);
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varbuf2[z][y][xpadsize - 1] = double4(0.0, 0.0, 0.0, 0.0);
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}
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for (x = 0; x < xpadsize; x++)
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{
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varbuf1[z][ypadsize - 1][x] = double4(0.0, 0.0, 0.0, 0.0);
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varbuf2[z][ypadsize - 1][x] = double4(0.0, 0.0, 0.0, 0.0);
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}
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}
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if (use_z_axis)
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{
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for (y = 0; y < ypadsize; y++)
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{
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for (x = 0; x < xpadsize; x++)
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{
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varbuf1[zpadsize - 1][y][x] = double4(0.0, 0.0, 0.0, 0.0);
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varbuf2[zpadsize - 1][y][x] = double4(0.0, 0.0, 0.0, 0.0);
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}
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}
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}
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// generate summed-area tables for x and x2; this is done in-place
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for (z = 0; z < zpadsize; z++)
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{
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for (y = 0; y < ypadsize; y++)
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{
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double4 summa1 = double4(0.0, 0.0, 0.0, 0.0);
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double4 summa2 = double4(0.0, 0.0, 0.0, 0.0);
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for (x = 0; x < xpadsize; x++)
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{
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double4 val1 = varbuf1[z][y][x];
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double4 val2 = varbuf2[z][y][x];
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varbuf1[z][y][x] = summa1;
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varbuf2[z][y][x] = summa2;
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summa1 = summa1 + val1;
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summa2 = summa2 + val2;
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}
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}
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}
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for (z = 0; z < zpadsize; z++)
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{
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for (x = 0; x < xpadsize; x++)
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{
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double4 summa1 = double4(0.0, 0.0, 0.0, 0.0);
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double4 summa2 = double4(0.0, 0.0, 0.0, 0.0);
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for (y = 0; y < ypadsize; y++)
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{
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double4 val1 = varbuf1[z][y][x];
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double4 val2 = varbuf2[z][y][x];
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varbuf1[z][y][x] = summa1;
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varbuf2[z][y][x] = summa2;
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summa1 = summa1 + val1;
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summa2 = summa2 + val2;
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}
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}
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}
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if (use_z_axis)
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{
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for (y = 0; y < ypadsize; y++)
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{
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for (x = 0; x < xpadsize; x++)
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{
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double4 summa1 = double4(0.0, 0.0, 0.0, 0.0);
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double4 summa2 = double4(0.0, 0.0, 0.0, 0.0);
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for (z = 0; z < zpadsize; z++)
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{
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double4 val1 = varbuf1[z][y][x];
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double4 val2 = varbuf2[z][y][x];
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varbuf1[z][y][x] = summa1;
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varbuf2[z][y][x] = summa2;
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summa1 = summa1 + val1;
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summa2 = summa2 + val2;
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}
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}
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}
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}
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int avg_var_kerneldim = 2 * avg_var_kernel_radius + 1;
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int alpha_kerneldim = 2 * alpha_kernel_radius + 1;
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// compute a few constants used in the variance-calculation.
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double avg_var_samples;
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double alpha_rsamples;
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double mul1;
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if (use_z_axis)
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{
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avg_var_samples = avg_var_kerneldim * avg_var_kerneldim * avg_var_kerneldim;
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alpha_rsamples = 1.0 / (alpha_kerneldim * alpha_kerneldim * alpha_kerneldim);
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}
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else
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{
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avg_var_samples = avg_var_kerneldim * avg_var_kerneldim;
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alpha_rsamples = 1.0 / (alpha_kerneldim * alpha_kerneldim);
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}
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double avg_var_rsamples = 1.0 / avg_var_samples;
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if (avg_var_samples == 1)
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mul1 = 1.0;
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else
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mul1 = 1.0 / (avg_var_samples * (avg_var_samples - 1));
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double mul2 = avg_var_samples * mul1;
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// use the summed-area tables to compute variance for each sample-neighborhood
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if (use_z_axis)
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{
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for (z = 0; z < zsize; z++)
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{
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int z_src = z + kernel_radius;
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int z_dst = z + dest_zoffset;
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for (y = 0; y < ysize; y++)
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{
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int y_src = y + kernel_radius;
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int y_dst = y + dest_yoffset;
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for (x = 0; x < xsize; x++)
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{
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int x_src = x + kernel_radius;
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int x_dst = x + dest_xoffset;
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// summed-area table lookups for alpha average
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double vasum =
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(varbuf1[z_src + 1][y_src - alpha_kernel_radius][x_src - alpha_kernel_radius].w
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- varbuf1[z_src + 1][y_src - alpha_kernel_radius][x_src + alpha_kernel_radius + 1].w
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- varbuf1[z_src + 1][y_src + alpha_kernel_radius + 1][x_src - alpha_kernel_radius].w
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+ varbuf1[z_src + 1][y_src + alpha_kernel_radius + 1][x_src + alpha_kernel_radius + 1].w) -
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(varbuf1[z_src][y_src - alpha_kernel_radius][x_src - alpha_kernel_radius].w
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- varbuf1[z_src][y_src - alpha_kernel_radius][x_src + alpha_kernel_radius + 1].w
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- varbuf1[z_src][y_src + alpha_kernel_radius + 1][x_src - alpha_kernel_radius].w + varbuf1[z_src][y_src + alpha_kernel_radius + 1][x_src + alpha_kernel_radius + 1].w);
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input_alpha_averages[z_dst][y_dst][x_dst] = static_cast < float >(vasum * alpha_rsamples);
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|
|
||
|
|
|
||
|
|
// summed-area table lookups for RGBA average
|
||
|
|
double4 v0sum =
|
||
|
|
(varbuf1[z_src + 1][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf1[z_src + 1][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf1[z_src + 1][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius]
|
||
|
|
+ varbuf1[z_src + 1][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1]) -
|
||
|
|
(varbuf1[z_src][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf1[z_src][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius] + varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1]);
|
||
|
|
|
||
|
|
double4 avg = v0sum * avg_var_rsamples;
|
||
|
|
|
||
|
|
float4 favg = float4(static_cast < float >(avg.x),
|
||
|
|
static_cast < float >(avg.y),
|
||
|
|
static_cast < float >(avg.z),
|
||
|
|
static_cast < float >(avg.w));
|
||
|
|
input_averages[z_dst][y_dst][x_dst] = favg;
|
||
|
|
|
||
|
|
// summed-area table lookups for variance
|
||
|
|
double4 v1sum =
|
||
|
|
(varbuf1[z_src + 1][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf1[z_src + 1][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf1[z_src + 1][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius]
|
||
|
|
+ varbuf1[z_src + 1][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1]) -
|
||
|
|
(varbuf1[z_src][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf1[z_src][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius] + varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1]);
|
||
|
|
double4 v2sum =
|
||
|
|
(varbuf2[z_src + 1][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf2[z_src + 1][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf2[z_src + 1][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius]
|
||
|
|
+ varbuf2[z_src + 1][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1]) -
|
||
|
|
(varbuf2[z_src][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf2[z_src][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf2[z_src][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius] + varbuf2[z_src][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1]);
|
||
|
|
|
||
|
|
// the actual variance
|
||
|
|
double4 variance = mul2 * v2sum - mul1 * (v1sum * v1sum);
|
||
|
|
|
||
|
|
float4 fvar = float4(static_cast < float >(variance.x),
|
||
|
|
static_cast < float >(variance.y),
|
||
|
|
static_cast < float >(variance.z),
|
||
|
|
static_cast < float >(variance.w));
|
||
|
|
input_variances[z_dst][y_dst][x_dst] = fvar;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
for (z = 0; z < zsize; z++)
|
||
|
|
{
|
||
|
|
int z_src = z;
|
||
|
|
int z_dst = z + dest_zoffset;
|
||
|
|
for (y = 0; y < ysize; y++)
|
||
|
|
{
|
||
|
|
int y_src = y + kernel_radius;
|
||
|
|
int y_dst = y + dest_yoffset;
|
||
|
|
|
||
|
|
for (x = 0; x < xsize; x++)
|
||
|
|
{
|
||
|
|
int x_src = x + kernel_radius;
|
||
|
|
int x_dst = x + dest_xoffset;
|
||
|
|
|
||
|
|
// summed-area table lookups for alpha average
|
||
|
|
double vasum =
|
||
|
|
varbuf1[z_src][y_src - alpha_kernel_radius][x_src - alpha_kernel_radius].w
|
||
|
|
- varbuf1[z_src][y_src - alpha_kernel_radius][x_src + alpha_kernel_radius + 1].w
|
||
|
|
- varbuf1[z_src][y_src + alpha_kernel_radius + 1][x_src - alpha_kernel_radius].w + varbuf1[z_src][y_src + alpha_kernel_radius + 1][x_src + alpha_kernel_radius + 1].w;
|
||
|
|
input_alpha_averages[z_dst][y_dst][x_dst] = static_cast < float >(vasum * alpha_rsamples);
|
||
|
|
|
||
|
|
// summed-area table lookups for RGBA average
|
||
|
|
double4 v0sum =
|
||
|
|
varbuf1[z_src][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf1[z_src][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius] + varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1];
|
||
|
|
|
||
|
|
double4 avg = v0sum * avg_var_rsamples;
|
||
|
|
|
||
|
|
float4 favg = float4(static_cast < float >(avg.x),
|
||
|
|
static_cast < float >(avg.y),
|
||
|
|
static_cast < float >(avg.z),
|
||
|
|
static_cast < float >(avg.w));
|
||
|
|
input_averages[z_dst][y_dst][x_dst] = favg;
|
||
|
|
|
||
|
|
// summed-area table lookups for variance
|
||
|
|
double4 v1sum =
|
||
|
|
varbuf1[z_src][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf1[z_src][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius] + varbuf1[z_src][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1];
|
||
|
|
double4 v2sum =
|
||
|
|
varbuf2[z_src][y_src - avg_var_kernel_radius][x_src - avg_var_kernel_radius]
|
||
|
|
- varbuf2[z_src][y_src - avg_var_kernel_radius][x_src + avg_var_kernel_radius + 1]
|
||
|
|
- varbuf2[z_src][y_src + avg_var_kernel_radius + 1][x_src - avg_var_kernel_radius] + varbuf2[z_src][y_src + avg_var_kernel_radius + 1][x_src + avg_var_kernel_radius + 1];
|
||
|
|
|
||
|
|
// the actual variance
|
||
|
|
double4 variance = mul2 * v2sum - mul1 * (v1sum * v1sum);
|
||
|
|
|
||
|
|
float4 fvar = float4(static_cast < float >(variance.x),
|
||
|
|
static_cast < float >(variance.y),
|
||
|
|
static_cast < float >(variance.z),
|
||
|
|
static_cast < float >(variance.w));
|
||
|
|
input_variances[z_dst][y_dst][x_dst] = fvar;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
delete[] varbuf2[0][0];
|
||
|
|
delete[] varbuf1[0][0];
|
||
|
|
delete[] varbuf2[0];
|
||
|
|
delete[] varbuf1[0];
|
||
|
|
delete[] varbuf2;
|
||
|
|
delete[] varbuf1;
|
||
|
|
}
|
||
|
|
|
||
|
|
static void allocate_input_average_and_variance_buffers(int xsize, int ysize, int zsize)
|
||
|
|
{
|
||
|
|
int y, z;
|
||
|
|
if (input_averages)
|
||
|
|
{
|
||
|
|
delete[] input_averages[0][0];
|
||
|
|
delete[] input_averages[0];
|
||
|
|
delete[] input_averages;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (input_variances)
|
||
|
|
{
|
||
|
|
delete[] input_variances[0][0];
|
||
|
|
delete[] input_variances[0];
|
||
|
|
delete[] input_variances;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (input_alpha_averages)
|
||
|
|
{
|
||
|
|
delete[] input_alpha_averages[0][0];
|
||
|
|
delete[] input_alpha_averages[0];
|
||
|
|
delete[] input_alpha_averages;
|
||
|
|
}
|
||
|
|
|
||
|
|
input_averages = new float4 **[zsize];
|
||
|
|
input_variances = new float4 **[zsize];
|
||
|
|
input_alpha_averages = new float **[zsize];
|
||
|
|
|
||
|
|
input_averages[0] = new float4 *[ysize * zsize];
|
||
|
|
input_variances[0] = new float4 *[ysize * zsize];
|
||
|
|
input_alpha_averages[0] = new float *[ysize * zsize];
|
||
|
|
|
||
|
|
input_averages[0][0] = new float4[xsize * ysize * zsize];
|
||
|
|
input_variances[0][0] = new float4[xsize * ysize * zsize];
|
||
|
|
input_alpha_averages[0][0] = new float[xsize * ysize * zsize];
|
||
|
|
|
||
|
|
for (z = 1; z < zsize; z++)
|
||
|
|
{
|
||
|
|
input_averages[z] = input_averages[0] + z * ysize;
|
||
|
|
input_variances[z] = input_variances[0] + z * ysize;
|
||
|
|
input_alpha_averages[z] = input_alpha_averages[0] + z * ysize;
|
||
|
|
|
||
|
|
input_averages[z][0] = input_averages[0][0] + z * ysize * xsize;
|
||
|
|
input_variances[z][0] = input_variances[0][0] + z * ysize * xsize;
|
||
|
|
input_alpha_averages[z][0] = input_alpha_averages[0][0] + z * ysize * xsize;
|
||
|
|
}
|
||
|
|
|
||
|
|
for (z = 0; z < zsize; z++)
|
||
|
|
{
|
||
|
|
for (y = 1; y < ysize; y++)
|
||
|
|
{
|
||
|
|
input_averages[z][y] = input_averages[z][0] + y * xsize;
|
||
|
|
input_variances[z][y] = input_variances[z][0] + y * xsize;
|
||
|
|
input_alpha_averages[z][y] = input_alpha_averages[z][0] + y * xsize;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// compute averages and variances for the current input image.
|
||
|
|
void compute_averages_and_variances(const astc_codec_image * img, float rgb_power_to_use, float alpha_power_to_use, int avg_var_kernel_radius, int alpha_kernel_radius, swizzlepattern swz)
|
||
|
|
{
|
||
|
|
int xsize = img->xsize;
|
||
|
|
int ysize = img->ysize;
|
||
|
|
int zsize = img->zsize;
|
||
|
|
allocate_input_average_and_variance_buffers(xsize, ysize, zsize);
|
||
|
|
|
||
|
|
int x, y, z;
|
||
|
|
for (z = 0; z < zsize; z += 32)
|
||
|
|
{
|
||
|
|
int zblocksize = MIN(32, zsize - z);
|
||
|
|
for (y = 0; y < ysize; y += 32)
|
||
|
|
{
|
||
|
|
int yblocksize = MIN(32, ysize - y);
|
||
|
|
for (x = 0; x < xsize; x += 32)
|
||
|
|
{
|
||
|
|
int xblocksize = MIN(32, xsize - x);
|
||
|
|
compute_pixel_region_variance(img,
|
||
|
|
rgb_power_to_use,
|
||
|
|
alpha_power_to_use,
|
||
|
|
swz,
|
||
|
|
(zsize > 1),
|
||
|
|
x + img->padding,
|
||
|
|
y + img->padding, z + (zsize > 1 ? img->padding : 0), xblocksize, yblocksize, zblocksize, avg_var_kernel_radius, alpha_kernel_radius, x, y, z);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|