/*

 * Copyright (c) 2016, Alliance for Open Media. All rights reserved

 *

 * This source code is subject to the terms of the BSD 2 Clause License and

 * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License

 * was not distributed with this source code in the LICENSE file, you can

 * obtain it at www.aomedia.org/license/software. If the Alliance for Open

 * Media Patent License 1.0 was not distributed with this source code in the

 * PATENTS file, you can obtain it at www.aomedia.org/license/patent.

 */

#include <math.h>

#include <stdlib.h>

#include "config/aom_dsp_rtcd.h"

#include "config/av1_rtcd.h"

#include "av1/common/cdef.h"

/*

This is Cdef_Directions (section 7.15.3) with 2 padding entries at the

beginning and end of the table. The cdef direction range is [0, 7] and the

first index is offset +/-2. This removes the need to constrain the first

index to the same range using e.g., & 7.

*/

DECLARE_ALIGNED(16, const int, cdef_directions_padded[12][2]) = {

  /* Padding: cdef_directions[6] */

  { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE + 0 },

  /* Padding: cdef_directions[7] */

  { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE - 1 },

  /* Begin cdef_directions */

  { -1 * CDEF_BSTRIDE + 1, -2 * CDEF_BSTRIDE + 2 },

  { 0 * CDEF_BSTRIDE + 1, -1 * CDEF_BSTRIDE + 2 },

  { 0 * CDEF_BSTRIDE + 1, 0 * CDEF_BSTRIDE + 2 },

  { 0 * CDEF_BSTRIDE + 1, 1 * CDEF_BSTRIDE + 2 },

  { 1 * CDEF_BSTRIDE + 1, 2 * CDEF_BSTRIDE + 2 },

  { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE + 1 },

  { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE + 0 },

  { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE - 1 },

  /* End cdef_directions */

  /* Padding: cdef_directions[0] */

  { -1 * CDEF_BSTRIDE + 1, -2 * CDEF_BSTRIDE + 2 },

  /* Padding: cdef_directions[1] */

  { 0 * CDEF_BSTRIDE + 1, -1 * CDEF_BSTRIDE + 2 },

};

const int (*const cdef_directions)[2] = cdef_directions_padded + 2;

/* Detect direction. 0 means 45-degree up-right, 2 is horizontal, and so on.

   The search minimizes the weighted variance along all the lines in a

   particular direction, i.e. the squared error between the input and a

   "predicted" block where each pixel is replaced by the average along a line

   in a particular direction. Since each direction have the same sum(x^2) term,

   that term is never computed. See Section 2, step 2, of:

   http://jmvalin.ca/notes/intra_paint.pdf */

int cdef_find_dir_c(const uint16_t *img, int stride, int32_t *var,

                    int coeff_shift) {

  int i;

  int32_t cost[8] = { 0 };

  int partial[8][15] = { { 0 } };

  int32_t best_cost = 0;

  int best_dir = 0;

  /* Instead of dividing by n between 2 and 8, we multiply by 3*5*7*8/n.

     The output is then 840 times larger, but we don't care for finding

     the max. */

  static const int div_table[] = { 0, 840, 420, 280, 210, 168, 140, 120, 105 };

  for (i = 0; i < 8; i++) {

    int j;

    for (j = 0; j < 8; j++) {

      int x;

      /* We subtract 128 here to reduce the maximum range of the squared

         partial sums. */

      x = (img[i * stride + j] >> coeff_shift) - 128;

      partial[0][i + j] += x;

      partial[1][i + j / 2] += x;

      partial[2][i] += x;

      partial[3][3 + i - j / 2] += x;

      partial[4][7 + i - j] += x;

      partial[5][3 - i / 2 + j] += x;

      partial[6][j] += x;

      partial[7][i / 2 + j] += x;

    }

  }

  for (i = 0; i < 8; i++) {

    cost[2] += partial[2][i] * partial[2][i];

    cost[6] += partial[6][i] * partial[6][i];

  }

  cost[2] *= div_table[8];

  cost[6] *= div_table[8];

  for (i = 0; i < 7; i++) {

    cost[0] += (partial[0][i] * partial[0][i] +

                partial[0][14 - i] * partial[0][14 - i]) *

               div_table[i + 1];

    cost[4] += (partial[4][i] * partial[4][i] +

                partial[4][14 - i] * partial[4][14 - i]) *

               div_table[i + 1];

  }

  cost[0] += partial[0][7] * partial[0][7] * div_table[8];

  cost[4] += partial[4][7] * partial[4][7] * div_table[8];

  for (i = 1; i < 8; i += 2) {

    int j;

    for (j = 0; j < 4 + 1; j++) {

      cost[i] += partial[i][3 + j] * partial[i][3 + j];

    }

    cost[i] *= div_table[8];

    for (j = 0; j < 4 - 1; j++) {

      cost[i] += (partial[i][j] * partial[i][j] +

                  partial[i][10 - j] * partial[i][10 - j]) *

                 div_table[2 * j + 2];

    }

  }

  for (i = 0; i < 8; i++) {

    if (cost[i] > best_cost) {

      best_cost = cost[i];

      best_dir = i;

    }

  }

  /* Difference between the optimal variance and the variance along the

     orthogonal direction. Again, the sum(x^2) terms cancel out. */

  *var = best_cost - cost[(best_dir + 4) & 7];

  /* We'd normally divide by 840, but dividing by 1024 is close enough

     for what we're going to do with this. */

  *var >>= 10;

  return best_dir;

}

const int cdef_pri_taps[2][2] = { { 4, 2 }, { 3, 3 } };

const int cdef_sec_taps[2] = { 2, 1 };

/* Smooth in the direction detected. */

static void cdef_filter_block_internal(uint8_t *dst8, uint16_t *dst16,

                                       int dstride, const uint16_t *in,

                                       int pri_strength, int sec_strength,

                                       int dir, int pri_damping,

                                       int sec_damping, int bsize,

                                       int coeff_shift) {

  int i, j, k;

  const int s = CDEF_BSTRIDE;

  const int *pri_taps = cdef_pri_taps[(pri_strength >> coeff_shift) & 1];

  const int *sec_taps = cdef_sec_taps;

  for (i = 0; i < 4 << (bsize == BLOCK_8X8 || bsize == BLOCK_4X8); i++) {

    for (j = 0; j < 4 << (bsize == BLOCK_8X8 || bsize == BLOCK_8X4); j++) {

      int16_t sum = 0;

      int16_t y;

      int16_t x = in[i * s + j];

      int max = x;

      int min = x;

      for (k = 0; k < 2; k++) {

        int16_t p0 = in[i * s + j + cdef_directions[dir][k]];

        int16_t p1 = in[i * s + j - cdef_directions[dir][k]];

        sum += pri_taps[k] * constrain(p0 - x, pri_strength, pri_damping);

        sum += pri_taps[k] * constrain(p1 - x, pri_strength, pri_damping);

        if (p0 != CDEF_VERY_LARGE) max = AOMMAX(p0, max);

        if (p1 != CDEF_VERY_LARGE) max = AOMMAX(p1, max);

        min = AOMMIN(p0, min);

        min = AOMMIN(p1, min);

        int16_t s0 = in[i * s + j + cdef_directions[dir + 2][k]];

        int16_t s1 = in[i * s + j - cdef_directions[dir + 2][k]];

        int16_t s2 = in[i * s + j + cdef_directions[dir - 2][k]];

        int16_t s3 = in[i * s + j - cdef_directions[dir - 2][k]];

        if (s0 != CDEF_VERY_LARGE) max = AOMMAX(s0, max);

        if (s1 != CDEF_VERY_LARGE) max = AOMMAX(s1, max);

        if (s2 != CDEF_VERY_LARGE) max = AOMMAX(s2, max);

        if (s3 != CDEF_VERY_LARGE) max = AOMMAX(s3, max);

        min = AOMMIN(s0, min);

        min = AOMMIN(s1, min);

        min = AOMMIN(s2, min);

        min = AOMMIN(s3, min);

        sum += sec_taps[k] * constrain(s0 - x, sec_strength, sec_damping);

        sum += sec_taps[k] * constrain(s1 - x, sec_strength, sec_damping);

        sum += sec_taps[k] * constrain(s2 - x, sec_strength, sec_damping);

        sum += sec_taps[k] * constrain(s3 - x, sec_strength, sec_damping);

      }

      y = clamp((int16_t)x + ((8 + sum - (sum < 0)) >> 4), min, max);

      if (dst8)

        dst8[i * dstride + j] = (uint8_t)y;

      else

        dst16[i * dstride + j] = (uint16_t)y;

    }

  }

}

void cdef_filter_block_c(void *dst8, int dstride, const uint16_t *in,

                         int pri_strength, int sec_strength, int dir,

                         int pri_damping, int sec_damping, int bsize,

                         int coeff_shift) {

  cdef_filter_block_internal((uint8_t *)dst8, NULL, dstride, in, pri_strength,

                             sec_strength, dir, pri_damping, sec_damping, bsize,

                             coeff_shift);

}

void cdef_filter_block_highbd_c(void *dst16, int dstride, const uint16_t *in,

                                int pri_strength, int sec_strength, int dir,

                                int pri_damping, int sec_damping, int bsize,

                                int coeff_shift) {

  cdef_filter_block_internal(NULL, (uint16_t *)dst16, dstride, in, pri_strength,

                             sec_strength, dir, pri_damping, sec_damping, bsize,

                             coeff_shift);

}

/* Compute the primary filter strength for an 8x8 block based on the

   directional variance difference. A high variance difference means

   that we have a highly directional pattern (e.g. a high contrast

   edge), so we can apply more deringing. A low variance means that we

   either have a low contrast edge, or a non-directional texture, so

   we want to be careful not to blur. */

static INLINE int adjust_strength(int strength, int32_t var) {

  const int i = var >> 6 ? AOMMIN(get_msb(var >> 6), 12) : 0;

  /* We use the variance of 8x8 blocks to adjust the strength. */

  return var ? (strength * (4 + i) + 8) >> 4 : 0;

}

void av1_cdef_filter_fb(uint8_t *dst8, uint16_t *dst16, int dstride,

                        uint16_t *in, int xdec, int ydec,

                        int dir[CDEF_NBLOCKS][CDEF_NBLOCKS], int *dirinit,

                        int var[CDEF_NBLOCKS][CDEF_NBLOCKS], int pli,

                        cdef_list *dlist, int cdef_count, int level,

                        int sec_strength, int damping, int coeff_shift) {

  int bi;

  int bx;

  int by;

  const int pri_strength = level << coeff_shift;

  sec_strength <<= coeff_shift;

  damping += coeff_shift - (pli != AOM_PLANE_Y);

  const int bw_log2 = 3 - xdec;

  const int bh_log2 = 3 - ydec;

  if (dirinit && pri_strength == 0 && sec_strength == 0) {

    // If we're here, both primary and secondary strengths are 0, and

    // we still haven't written anything to y[] yet, so we just copy

    // the input to y[]. This is necessary only for av1_cdef_search()

    // and only av1_cdef_search() sets dirinit.

    for (bi = 0; bi < cdef_count; bi++) {

      by = dlist[bi].by;

      bx = dlist[bi].bx;

      // TODO(stemidts/jmvalin): SIMD optimisations

      for (int iy = 0; iy < 1 << bh_log2; iy++) {

        memcpy(&dst16[(bi << (bw_log2 + bh_log2)) + (iy << bw_log2)],

               &in[((by << bh_log2) + iy) * CDEF_BSTRIDE + (bx << bw_log2)],

               ((size_t)1 << bw_log2) * sizeof(*dst16));

      }

    }

    return;

  }

  if (pli == 0) {

    if (!dirinit || !*dirinit) {

      for (bi = 0; bi < cdef_count; bi++) {

        by = dlist[bi].by;

        bx = dlist[bi].bx;

        dir[by][bx] = cdef_find_dir(&in[8 * by * CDEF_BSTRIDE + 8 * bx],

                                    CDEF_BSTRIDE, &var[by][bx], coeff_shift);

      }

      if (dirinit) *dirinit = 1;

    }

  }

  if (pli == 1 && xdec != ydec) {

    for (bi = 0; bi < cdef_count; bi++) {

      static const int conv422[8] = { 7, 0, 2, 4, 5, 6, 6, 6 };

      static const int conv440[8] = { 1, 2, 2, 2, 3, 4, 6, 0 };

      by = dlist[bi].by;

      bx = dlist[bi].bx;

      dir[by][bx] = (xdec ? conv422 : conv440)[dir[by][bx]];

    }

  }

  const int bsize =

      ydec ? (xdec ? BLOCK_4X4 : BLOCK_8X4) : (xdec ? BLOCK_4X8 : BLOCK_8X8);

  const int t = pri_strength;

  const int s = sec_strength;

  for (bi = 0; bi < cdef_count; bi++) {

    by = dlist[bi].by;

    bx = dlist[bi].bx;

    if (dst16) {

      cdef_filter_block_highbd(

          &dst16[dirinit ? bi << (bw_log2 + bh_log2)

                         : (by << bh_log2) * dstride + (bx << bw_log2)],

          dirinit ? 1 << bw_log2 : dstride,

          &in[(by * CDEF_BSTRIDE << bh_log2) + (bx << bw_log2)],

          (pli ? t : adjust_strength(t, var[by][bx])), s, t ? dir[by][bx] : 0,

          damping, damping, bsize, coeff_shift);

    } else {

      cdef_filter_block(

          &dst8[(by << bh_log2) * dstride + (bx << bw_log2)], dstride,

          &in[(by * CDEF_BSTRIDE << bh_log2) + (bx << bw_log2)],

          (pli ? t : adjust_strength(t, var[by][bx])), s, t ? dir[by][bx] : 0,

          damping, damping, bsize, coeff_shift);

    }

  }

}