diff --git a/av1/encoder/pickrst.c b/av1/encoder/pickrst.c
new file mode 100644
index 0000000..b6ee6f0
--- /dev/null
+++ b/av1/encoder/pickrst.c
@@ -0,0 +1,808 @@
+/*
+ *  Copyright (c) 2010 The WebM project authors. All Rights Reserved.
+ *
+ *  Use of this source code is governed by a BSD-style license
+ *  that can be found in the LICENSE file in the root of the source
+ *  tree. An additional intellectual property rights grant can be found
+ *  in the file PATENTS.  All contributing project authors may
+ *  be found in the AUTHORS file in the root of the source tree.
+ */
+
+#include <assert.h>
+#include <float.h>
+#include <limits.h>
+#include <math.h>
+
+#include "./vpx_scale_rtcd.h"
+
+#include "aom_dsp/psnr.h"
+#include "aom_dsp/vpx_dsp_common.h"
+#include "aom_mem/vpx_mem.h"
+#include "aom_ports/mem.h"
+
+#include "av1/common/onyxc_int.h"
+#include "av1/common/quant_common.h"
+
+#include "av1/encoder/encoder.h"
+#include "av1/encoder/picklpf.h"
+#include "av1/encoder/pickrst.h"
+#include "av1/encoder/quantize.h"
+
+static int64_t try_restoration_frame(const YV12_BUFFER_CONFIG *sd,
+                                     VP10_COMP *const cpi, RestorationInfo *rsi,
+                                     int partial_frame) {
+  VP10_COMMON *const cm = &cpi->common;
+  int64_t filt_err;
+  vp10_loop_restoration_frame(cm->frame_to_show, cm, rsi, 1, partial_frame);
+#if CONFIG_VP9_HIGHBITDEPTH
+  if (cm->use_highbitdepth) {
+    filt_err = vpx_highbd_get_y_sse(sd, cm->frame_to_show);
+  } else {
+    filt_err = vpx_get_y_sse(sd, cm->frame_to_show);
+  }
+#else
+  filt_err = vpx_get_y_sse(sd, cm->frame_to_show);
+#endif  // CONFIG_VP9_HIGHBITDEPTH
+
+  // Re-instate the unfiltered frame
+  vpx_yv12_copy_y(&cpi->last_frame_db, cm->frame_to_show);
+  return filt_err;
+}
+
+static int search_bilateral_level(const YV12_BUFFER_CONFIG *sd, VP10_COMP *cpi,
+                                  int filter_level, int partial_frame,
+                                  int *bilateral_level, double *best_cost_ret) {
+  VP10_COMMON *const cm = &cpi->common;
+  int i, j, tile_idx;
+  int64_t err;
+  int bits;
+  double cost, best_cost, cost_norestore, cost_bilateral;
+  const int bilateral_level_bits = vp10_bilateral_level_bits(&cpi->common);
+  const int bilateral_levels = 1 << bilateral_level_bits;
+  MACROBLOCK *x = &cpi->td.mb;
+  RestorationInfo rsi;
+  const int ntiles =
+      vp10_get_restoration_ntiles(BILATERAL_TILESIZE, cm->width, cm->height);
+
+  //  Make a copy of the unfiltered / processed recon buffer
+  vpx_yv12_copy_y(cm->frame_to_show, &cpi->last_frame_uf);
+  vp10_loop_filter_frame(cm->frame_to_show, cm, &cpi->td.mb.e_mbd, filter_level,
+                         1, partial_frame);
+  vpx_yv12_copy_y(cm->frame_to_show, &cpi->last_frame_db);
+
+  // RD cost associated with no restoration
+  rsi.restoration_type = RESTORE_NONE;
+  err = try_restoration_frame(sd, cpi, &rsi, partial_frame);
+  bits = 0;
+  cost_norestore = RDCOST_DBL(x->rdmult, x->rddiv,
+                              (bits << (VP10_PROB_COST_SHIFT - 4)), err);
+  best_cost = cost_norestore;
+
+  // RD cost associated with bilateral filtering
+  rsi.restoration_type = RESTORE_BILATERAL;
+  rsi.bilateral_level =
+      (int *)vpx_malloc(sizeof(*rsi.bilateral_level) * ntiles);
+  assert(rsi.bilateral_level != NULL);
+
+  for (j = 0; j < ntiles; ++j) bilateral_level[j] = -1;
+
+  // Find best filter for each tile
+  for (tile_idx = 0; tile_idx < ntiles; ++tile_idx) {
+    for (j = 0; j < ntiles; ++j) rsi.bilateral_level[j] = -1;
+    best_cost = cost_norestore;
+    for (i = 0; i < bilateral_levels; ++i) {
+      rsi.bilateral_level[tile_idx] = i;
+      err = try_restoration_frame(sd, cpi, &rsi, partial_frame);
+      bits = bilateral_level_bits + 1;
+      // Normally the rate is rate in bits * 256 and dist is sum sq err * 64
+      // when RDCOST is used.  However below we just scale both in the correct
+      // ratios appropriately but not exactly by these values.
+      cost = RDCOST_DBL(x->rdmult, x->rddiv,
+                        (bits << (VP10_PROB_COST_SHIFT - 4)), err);
+      if (cost < best_cost) {
+        bilateral_level[tile_idx] = i;
+        best_cost = cost;
+      }
+    }
+  }
+  // Find cost for combined configuration
+  bits = 0;
+  for (j = 0; j < ntiles; ++j) {
+    rsi.bilateral_level[j] = bilateral_level[j];
+    if (rsi.bilateral_level[j] >= 0) {
+      bits += (bilateral_level_bits + 1);
+    } else {
+      bits += 1;
+    }
+  }
+  err = try_restoration_frame(sd, cpi, &rsi, partial_frame);
+  cost_bilateral = RDCOST_DBL(x->rdmult, x->rddiv,
+                              (bits << (VP10_PROB_COST_SHIFT - 4)), err);
+
+  vpx_free(rsi.bilateral_level);
+
+  vpx_yv12_copy_y(&cpi->last_frame_uf, cm->frame_to_show);
+  if (cost_bilateral < cost_norestore) {
+    if (best_cost_ret) *best_cost_ret = cost_bilateral;
+    return 1;
+  } else {
+    if (best_cost_ret) *best_cost_ret = cost_norestore;
+    return 0;
+  }
+}
+
+static int search_filter_bilateral_level(const YV12_BUFFER_CONFIG *sd,
+                                         VP10_COMP *cpi, int partial_frame,
+                                         int *filter_best, int *bilateral_level,
+                                         double *best_cost_ret) {
+  const VP10_COMMON *const cm = &cpi->common;
+  const struct loopfilter *const lf = &cm->lf;
+  const int min_filter_level = 0;
+  const int max_filter_level = vp10_get_max_filter_level(cpi);
+  int filt_direction = 0;
+  int filt_best;
+  double best_err;
+  int i, j;
+  int *tmp_level;
+  int bilateral_success[MAX_LOOP_FILTER + 1];
+
+  const int ntiles =
+      vp10_get_restoration_ntiles(BILATERAL_TILESIZE, cm->width, cm->height);
+
+  // Start the search at the previous frame filter level unless it is now out of
+  // range.
+  int filt_mid = clamp(lf->filter_level, min_filter_level, max_filter_level);
+  int filter_step = filt_mid < 16 ? 4 : filt_mid / 4;
+  double ss_err[MAX_LOOP_FILTER + 1];
+  // Set each entry to -1
+  for (i = 0; i <= MAX_LOOP_FILTER; ++i) ss_err[i] = -1.0;
+
+  tmp_level = (int *)vpx_malloc(sizeof(*tmp_level) * ntiles);
+
+  bilateral_success[filt_mid] = search_bilateral_level(
+      sd, cpi, filt_mid, partial_frame, tmp_level, &best_err);
+  filt_best = filt_mid;
+  ss_err[filt_mid] = best_err;
+  for (j = 0; j < ntiles; ++j) {
+    bilateral_level[j] = tmp_level[j];
+  }
+
+  while (filter_step > 0) {
+    const int filt_high = VPXMIN(filt_mid + filter_step, max_filter_level);
+    const int filt_low = VPXMAX(filt_mid - filter_step, min_filter_level);
+
+    // Bias against raising loop filter in favor of lowering it.
+    double bias = (best_err / (1 << (15 - (filt_mid / 8)))) * filter_step;
+
+    if ((cpi->oxcf.pass == 2) && (cpi->twopass.section_intra_rating < 20))
+      bias = (bias * cpi->twopass.section_intra_rating) / 20;
+
+    // yx, bias less for large block size
+    if (cm->tx_mode != ONLY_4X4) bias /= 2;
+
+    if (filt_direction <= 0 && filt_low != filt_mid) {
+      // Get Low filter error score
+      if (ss_err[filt_low] < 0) {
+        bilateral_success[filt_low] = search_bilateral_level(
+            sd, cpi, filt_low, partial_frame, tmp_level, &ss_err[filt_low]);
+      }
+      // If value is close to the best so far then bias towards a lower loop
+      // filter value.
+      if (ss_err[filt_low] < (best_err + bias)) {
+        // Was it actually better than the previous best?
+        if (ss_err[filt_low] < best_err) {
+          best_err = ss_err[filt_low];
+        }
+        filt_best = filt_low;
+        for (j = 0; j < ntiles; ++j) {
+          bilateral_level[j] = tmp_level[j];
+        }
+      }
+    }
+
+    // Now look at filt_high
+    if (filt_direction >= 0 && filt_high != filt_mid) {
+      if (ss_err[filt_high] < 0) {
+        bilateral_success[filt_high] = search_bilateral_level(
+            sd, cpi, filt_high, partial_frame, tmp_level, &ss_err[filt_high]);
+      }
+      // If value is significantly better than previous best, bias added against
+      // raising filter value
+      if (ss_err[filt_high] < (best_err - bias)) {
+        best_err = ss_err[filt_high];
+        filt_best = filt_high;
+        for (j = 0; j < ntiles; ++j) {
+          bilateral_level[j] = tmp_level[j];
+        }
+      }
+    }
+
+    // Half the step distance if the best filter value was the same as last time
+    if (filt_best == filt_mid) {
+      filter_step /= 2;
+      filt_direction = 0;
+    } else {
+      filt_direction = (filt_best < filt_mid) ? -1 : 1;
+      filt_mid = filt_best;
+    }
+  }
+
+  vpx_free(tmp_level);
+
+  // Update best error
+  best_err = ss_err[filt_best];
+
+  if (best_cost_ret) *best_cost_ret = best_err;
+  if (filter_best) *filter_best = filt_best;
+
+  return bilateral_success[filt_best];
+}
+
+static double find_average(uint8_t *src, int h_start, int h_end, int v_start,
+                           int v_end, int stride) {
+  uint64_t sum = 0;
+  double avg = 0;
+  int i, j;
+  for (i = v_start; i < v_end; i++)
+    for (j = h_start; j < h_end; j++) sum += src[i * stride + j];
+  avg = (double)sum / ((v_end - v_start) * (h_end - h_start));
+  return avg;
+}
+
+static void compute_stats(uint8_t *dgd, uint8_t *src, int h_start, int h_end,
+                          int v_start, int v_end, int dgd_stride,
+                          int src_stride, double *M, double *H) {
+  int i, j, k, l;
+  double Y[RESTORATION_WIN2];
+  const double avg =
+      find_average(dgd, h_start, h_end, v_start, v_end, dgd_stride);
+
+  memset(M, 0, sizeof(*M) * RESTORATION_WIN2);
+  memset(H, 0, sizeof(*H) * RESTORATION_WIN2 * RESTORATION_WIN2);
+  for (i = v_start; i < v_end; i++) {
+    for (j = h_start; j < h_end; j++) {
+      const double X = (double)src[i * src_stride + j] - avg;
+      int idx = 0;
+      for (k = -RESTORATION_HALFWIN; k <= RESTORATION_HALFWIN; k++) {
+        for (l = -RESTORATION_HALFWIN; l <= RESTORATION_HALFWIN; l++) {
+          Y[idx] = (double)dgd[(i + l) * dgd_stride + (j + k)] - avg;
+          idx++;
+        }
+      }
+      for (k = 0; k < RESTORATION_WIN2; ++k) {
+        M[k] += Y[k] * X;
+        H[k * RESTORATION_WIN2 + k] += Y[k] * Y[k];
+        for (l = k + 1; l < RESTORATION_WIN2; ++l) {
+          double value = Y[k] * Y[l];
+          H[k * RESTORATION_WIN2 + l] += value;
+          H[l * RESTORATION_WIN2 + k] += value;
+        }
+      }
+    }
+  }
+}
+
+#if CONFIG_VP9_HIGHBITDEPTH
+static double find_average_highbd(uint16_t *src, int h_start, int h_end,
+                                  int v_start, int v_end, int stride) {
+  uint64_t sum = 0;
+  double avg = 0;
+  int i, j;
+  for (i = v_start; i < v_end; i++)
+    for (j = h_start; j < h_end; j++) sum += src[i * stride + j];
+  avg = (double)sum / ((v_end - v_start) * (h_end - h_start));
+  return avg;
+}
+
+static void compute_stats_highbd(uint8_t *dgd8, uint8_t *src8, int h_start,
+                                 int h_end, int v_start, int v_end,
+                                 int dgd_stride, int src_stride, double *M,
+                                 double *H) {
+  int i, j, k, l;
+  double Y[RESTORATION_WIN2];
+  uint16_t *src = CONVERT_TO_SHORTPTR(src8);
+  uint16_t *dgd = CONVERT_TO_SHORTPTR(dgd8);
+  const double avg =
+      find_average_highbd(dgd, h_start, h_end, v_start, v_end, dgd_stride);
+
+  memset(M, 0, sizeof(*M) * RESTORATION_WIN2);
+  memset(H, 0, sizeof(*H) * RESTORATION_WIN2 * RESTORATION_WIN2);
+  for (i = v_start; i < v_end; i++) {
+    for (j = h_start; j < h_end; j++) {
+      const double X = (double)src[i * src_stride + j] - avg;
+      int idx = 0;
+      for (k = -RESTORATION_HALFWIN; k <= RESTORATION_HALFWIN; k++) {
+        for (l = -RESTORATION_HALFWIN; l <= RESTORATION_HALFWIN; l++) {
+          Y[idx] = (double)dgd[(i + l) * dgd_stride + (j + k)] - avg;
+          idx++;
+        }
+      }
+      for (k = 0; k < RESTORATION_WIN2; ++k) {
+        M[k] += Y[k] * X;
+        H[k * RESTORATION_WIN2 + k] += Y[k] * Y[k];
+        for (l = k + 1; l < RESTORATION_WIN2; ++l) {
+          double value = Y[k] * Y[l];
+          H[k * RESTORATION_WIN2 + l] += value;
+          H[l * RESTORATION_WIN2 + k] += value;
+        }
+      }
+    }
+  }
+}
+#endif  // CONFIG_VP9_HIGHBITDEPTH
+
+// Solves Ax = b, where x and b are column vectors
+static int linsolve(int n, double *A, int stride, double *b, double *x) {
+  int i, j, k;
+  double c;
+  // Partial pivoting
+  for (i = n - 1; i > 0; i--) {
+    if (A[(i - 1) * stride] < A[i * stride]) {
+      for (j = 0; j < n; j++) {
+        c = A[i * stride + j];
+        A[i * stride + j] = A[(i - 1) * stride + j];
+        A[(i - 1) * stride + j] = c;
+      }
+      c = b[i];
+      b[i] = b[i - 1];
+      b[i - 1] = c;
+    }
+  }
+  // Forward elimination
+  for (k = 0; k < n - 1; k++) {
+    for (i = k; i < n - 1; i++) {
+      c = A[(i + 1) * stride + k] / A[k * stride + k];
+      for (j = 0; j < n; j++) A[(i + 1) * stride + j] -= c * A[k * stride + j];
+      b[i + 1] -= c * b[k];
+    }
+  }
+  // Backward substitution
+  for (i = n - 1; i >= 0; i--) {
+    if (fabs(A[i * stride + i]) < 1e-10) return 0;
+    c = 0;
+    for (j = i + 1; j <= n - 1; j++) c += A[i * stride + j] * x[j];
+    x[i] = (b[i] - c) / A[i * stride + i];
+  }
+  return 1;
+}
+
+static INLINE int wrap_index(int i) {
+  return (i >= RESTORATION_HALFWIN1 ? RESTORATION_WIN - 1 - i : i);
+}
+
+// Fix vector b, update vector a
+static void update_a_sep_sym(double **Mc, double **Hc, double *a, double *b) {
+  int i, j;
+  double S[RESTORATION_WIN];
+  double A[RESTORATION_WIN], B[RESTORATION_WIN2];
+  int w, w2;
+  memset(A, 0, sizeof(A));
+  memset(B, 0, sizeof(B));
+  for (i = 0; i < RESTORATION_WIN; i++) {
+    int j;
+    for (j = 0; j < RESTORATION_WIN; ++j) {
+      const int jj = wrap_index(j);
+      A[jj] += Mc[i][j] * b[i];
+    }
+  }
+  for (i = 0; i < RESTORATION_WIN; i++) {
+    for (j = 0; j < RESTORATION_WIN; j++) {
+      int k, l;
+      for (k = 0; k < RESTORATION_WIN; ++k)
+        for (l = 0; l < RESTORATION_WIN; ++l) {
+          const int kk = wrap_index(k);
+          const int ll = wrap_index(l);
+          B[ll * RESTORATION_HALFWIN1 + kk] +=
+              Hc[j * RESTORATION_WIN + i][k * RESTORATION_WIN2 + l] * b[i] *
+              b[j];
+        }
+    }
+  }
+  // Normalization enforcement in the system of equations itself
+  w = RESTORATION_WIN;
+  w2 = (w >> 1) + 1;
+  for (i = 0; i < w2 - 1; ++i)
+    A[i] -=
+        A[w2 - 1] * 2 + B[i * w2 + w2 - 1] - 2 * B[(w2 - 1) * w2 + (w2 - 1)];
+  for (i = 0; i < w2 - 1; ++i)
+    for (j = 0; j < w2 - 1; ++j)
+      B[i * w2 + j] -= 2 * (B[i * w2 + (w2 - 1)] + B[(w2 - 1) * w2 + j] -
+                            2 * B[(w2 - 1) * w2 + (w2 - 1)]);
+  if (linsolve(w2 - 1, B, w2, A, S)) {
+    S[w2 - 1] = 1.0;
+    for (i = w2; i < w; ++i) {
+      S[i] = S[w - 1 - i];
+      S[w2 - 1] -= 2 * S[i];
+    }
+    memcpy(a, S, w * sizeof(*a));
+  }
+}
+
+// Fix vector a, update vector b
+static void update_b_sep_sym(double **Mc, double **Hc, double *a, double *b) {
+  int i, j;
+  double S[RESTORATION_WIN];
+  double A[RESTORATION_WIN], B[RESTORATION_WIN2];
+  int w, w2;
+  memset(A, 0, sizeof(A));
+  memset(B, 0, sizeof(B));
+  for (i = 0; i < RESTORATION_WIN; i++) {
+    int j;
+    const int ii = wrap_index(i);
+    for (j = 0; j < RESTORATION_WIN; j++) A[ii] += Mc[i][j] * a[j];
+  }
+
+  for (i = 0; i < RESTORATION_WIN; i++) {
+    for (j = 0; j < RESTORATION_WIN; j++) {
+      const int ii = wrap_index(i);
+      const int jj = wrap_index(j);
+      int k, l;
+      for (k = 0; k < RESTORATION_WIN; ++k)
+        for (l = 0; l < RESTORATION_WIN; ++l)
+          B[jj * RESTORATION_HALFWIN1 + ii] +=
+              Hc[i * RESTORATION_WIN + j][k * RESTORATION_WIN2 + l] * a[k] *
+              a[l];
+    }
+  }
+  // Normalization enforcement in the system of equations itself
+  w = RESTORATION_WIN;
+  w2 = RESTORATION_HALFWIN1;
+  for (i = 0; i < w2 - 1; ++i)
+    A[i] -=
+        A[w2 - 1] * 2 + B[i * w2 + w2 - 1] - 2 * B[(w2 - 1) * w2 + (w2 - 1)];
+  for (i = 0; i < w2 - 1; ++i)
+    for (j = 0; j < w2 - 1; ++j)
+      B[i * w2 + j] -= 2 * (B[i * w2 + (w2 - 1)] + B[(w2 - 1) * w2 + j] -
+                            2 * B[(w2 - 1) * w2 + (w2 - 1)]);
+  if (linsolve(w2 - 1, B, w2, A, S)) {
+    S[w2 - 1] = 1.0;
+    for (i = w2; i < w; ++i) {
+      S[i] = S[w - 1 - i];
+      S[w2 - 1] -= 2 * S[i];
+    }
+    memcpy(b, S, w * sizeof(*b));
+  }
+}
+
+static int wiener_decompose_sep_sym(double *M, double *H, double *a,
+                                    double *b) {
+  static const double init_filt[RESTORATION_WIN] = {
+    0.035623, -0.127154, 0.211436, 0.760190, 0.211436, -0.127154, 0.035623,
+  };
+  int i, j, iter;
+  double *Hc[RESTORATION_WIN2];
+  double *Mc[RESTORATION_WIN];
+  for (i = 0; i < RESTORATION_WIN; i++) {
+    Mc[i] = M + i * RESTORATION_WIN;
+    for (j = 0; j < RESTORATION_WIN; j++) {
+      Hc[i * RESTORATION_WIN + j] =
+          H + i * RESTORATION_WIN * RESTORATION_WIN2 + j * RESTORATION_WIN;
+    }
+  }
+  memcpy(a, init_filt, sizeof(*a) * RESTORATION_WIN);
+  memcpy(b, init_filt, sizeof(*b) * RESTORATION_WIN);
+
+  iter = 1;
+  while (iter < 10) {
+    update_a_sep_sym(Mc, Hc, a, b);
+    update_b_sep_sym(Mc, Hc, a, b);
+    iter++;
+  }
+  return 1;
+}
+
+// Computes the function x'*A*x - x'*b for the learned filters, and compares
+// against identity filters; Final score is defined as the difference between
+// the function values
+static double compute_score(double *M, double *H, int *vfilt, int *hfilt) {
+  double ab[RESTORATION_WIN * RESTORATION_WIN];
+  int i, k, l;
+  double P = 0, Q = 0;
+  double iP = 0, iQ = 0;
+  double Score, iScore;
+  int w;
+  double a[RESTORATION_WIN], b[RESTORATION_WIN];
+  w = RESTORATION_WIN;
+  a[RESTORATION_HALFWIN] = b[RESTORATION_HALFWIN] = 1.0;
+  for (i = 0; i < RESTORATION_HALFWIN; ++i) {
+    a[i] = a[RESTORATION_WIN - i - 1] =
+        (double)vfilt[i] / RESTORATION_FILT_STEP;
+    b[i] = b[RESTORATION_WIN - i - 1] =
+        (double)hfilt[i] / RESTORATION_FILT_STEP;
+    a[RESTORATION_HALFWIN] -= 2 * a[i];
+    b[RESTORATION_HALFWIN] -= 2 * b[i];
+  }
+  for (k = 0; k < w; ++k) {
+    for (l = 0; l < w; ++l) {
+      ab[k * w + l] = a[l] * b[k];
+    }
+  }
+  for (k = 0; k < w * w; ++k) {
+    P += ab[k] * M[k];
+    for (l = 0; l < w * w; ++l) Q += ab[k] * H[k * w * w + l] * ab[l];
+  }
+  Score = Q - 2 * P;
+
+  iP = M[(w * w) >> 1];
+  iQ = H[((w * w) >> 1) * w * w + ((w * w) >> 1)];
+  iScore = iQ - 2 * iP;
+
+  return Score - iScore;
+}
+
+#define CLIP(x, lo, hi) ((x) < (lo) ? (lo) : (x) > (hi) ? (hi) : (x))
+#define RINT(x) ((x) < 0 ? (int)((x)-0.5) : (int)((x) + 0.5))
+
+static void quantize_sym_filter(double *f, int *fi) {
+  int i;
+  for (i = 0; i < RESTORATION_HALFWIN; ++i) {
+    fi[i] = RINT(f[i] * RESTORATION_FILT_STEP);
+  }
+  // Specialize for 7-tap filter
+  fi[0] = CLIP(fi[0], WIENER_FILT_TAP0_MINV, WIENER_FILT_TAP0_MAXV);
+  fi[1] = CLIP(fi[1], WIENER_FILT_TAP1_MINV, WIENER_FILT_TAP1_MAXV);
+  fi[2] = CLIP(fi[2], WIENER_FILT_TAP2_MINV, WIENER_FILT_TAP2_MAXV);
+}
+
+static int search_wiener_filter(const YV12_BUFFER_CONFIG *src, VP10_COMP *cpi,
+                                int filter_level, int partial_frame,
+                                int (*vfilter)[RESTORATION_HALFWIN],
+                                int (*hfilter)[RESTORATION_HALFWIN],
+                                int *process_tile, double *best_cost_ret) {
+  VP10_COMMON *const cm = &cpi->common;
+  RestorationInfo rsi;
+  int64_t err;
+  int bits;
+  double cost_wiener, cost_norestore;
+  MACROBLOCK *x = &cpi->td.mb;
+  double M[RESTORATION_WIN2];
+  double H[RESTORATION_WIN2 * RESTORATION_WIN2];
+  double vfilterd[RESTORATION_WIN], hfilterd[RESTORATION_WIN];
+  const YV12_BUFFER_CONFIG *dgd = cm->frame_to_show;
+  const int width = cm->width;
+  const int height = cm->height;
+  const int src_stride = src->y_stride;
+  const int dgd_stride = dgd->y_stride;
+  double score;
+  int tile_idx, htile_idx, vtile_idx, tile_width, tile_height, nhtiles, nvtiles;
+  int h_start, h_end, v_start, v_end;
+  int i, j;
+
+  const int tilesize = WIENER_TILESIZE;
+  const int ntiles = vp10_get_restoration_ntiles(tilesize, width, height);
+
+  assert(width == dgd->y_crop_width);
+  assert(height == dgd->y_crop_height);
+  assert(width == src->y_crop_width);
+  assert(height == src->y_crop_height);
+
+  vp10_get_restoration_tile_size(tilesize, width, height, &tile_width,
+                                 &tile_height, &nhtiles, &nvtiles);
+
+  //  Make a copy of the unfiltered / processed recon buffer
+  vpx_yv12_copy_y(cm->frame_to_show, &cpi->last_frame_uf);
+  vp10_loop_filter_frame(cm->frame_to_show, cm, &cpi->td.mb.e_mbd, filter_level,
+                         1, partial_frame);
+  vpx_yv12_copy_y(cm->frame_to_show, &cpi->last_frame_db);
+
+  rsi.restoration_type = RESTORE_NONE;
+  err = try_restoration_frame(src, cpi, &rsi, partial_frame);
+  bits = 0;
+  cost_norestore = RDCOST_DBL(x->rdmult, x->rddiv,
+                              (bits << (VP10_PROB_COST_SHIFT - 4)), err);
+
+  rsi.restoration_type = RESTORE_WIENER;
+  rsi.vfilter =
+      (int(*)[RESTORATION_HALFWIN])vpx_malloc(sizeof(*rsi.vfilter) * ntiles);
+  assert(rsi.vfilter != NULL);
+  rsi.hfilter =
+      (int(*)[RESTORATION_HALFWIN])vpx_malloc(sizeof(*rsi.hfilter) * ntiles);
+  assert(rsi.hfilter != NULL);
+  rsi.wiener_level = (int *)vpx_malloc(sizeof(*rsi.wiener_level) * ntiles);
+  assert(rsi.wiener_level != NULL);
+
+  // Compute best Wiener filters for each tile
+  for (tile_idx = 0; tile_idx < ntiles; ++tile_idx) {
+    htile_idx = tile_idx % nhtiles;
+    vtile_idx = tile_idx / nhtiles;
+    h_start =
+        htile_idx * tile_width + ((htile_idx > 0) ? 0 : RESTORATION_HALFWIN);
+    h_end = (htile_idx < nhtiles - 1) ? ((htile_idx + 1) * tile_width)
+                                      : (width - RESTORATION_HALFWIN);
+    v_start =
+        vtile_idx * tile_height + ((vtile_idx > 0) ? 0 : RESTORATION_HALFWIN);
+    v_end = (vtile_idx < nvtiles - 1) ? ((vtile_idx + 1) * tile_height)
+                                      : (height - RESTORATION_HALFWIN);
+
+#if CONFIG_VP9_HIGHBITDEPTH
+    if (cm->use_highbitdepth)
+      compute_stats_highbd(dgd->y_buffer, src->y_buffer, h_start, h_end,
+                           v_start, v_end, dgd_stride, src_stride, M, H);
+    else
+#endif  // CONFIG_VP9_HIGHBITDEPTH
+      compute_stats(dgd->y_buffer, src->y_buffer, h_start, h_end, v_start,
+                    v_end, dgd_stride, src_stride, M, H);
+
+    if (!wiener_decompose_sep_sym(M, H, vfilterd, hfilterd)) {
+      for (i = 0; i < RESTORATION_HALFWIN; ++i)
+        rsi.vfilter[tile_idx][i] = rsi.hfilter[tile_idx][i] = 0;
+      process_tile[tile_idx] = 0;
+      continue;
+    }
+    quantize_sym_filter(vfilterd, rsi.vfilter[tile_idx]);
+    quantize_sym_filter(hfilterd, rsi.hfilter[tile_idx]);
+    process_tile[tile_idx] = 1;
+
+    // Filter score computes the value of the function x'*A*x - x'*b for the
+    // learned filter and compares it against identity filer. If there is no
+    // reduction in the function, the filter is reverted back to identity
+    score = compute_score(M, H, rsi.vfilter[tile_idx], rsi.hfilter[tile_idx]);
+    if (score > 0.0) {
+      for (i = 0; i < RESTORATION_HALFWIN; ++i)
+        rsi.vfilter[tile_idx][i] = rsi.hfilter[tile_idx][i] = 0;
+      process_tile[tile_idx] = 0;
+      continue;
+    }
+
+    for (j = 0; j < ntiles; ++j) rsi.wiener_level[j] = 0;
+    rsi.wiener_level[tile_idx] = 1;
+
+    err = try_restoration_frame(src, cpi, &rsi, partial_frame);
+    bits = 1 + WIENER_FILT_BITS;
+    cost_wiener = RDCOST_DBL(x->rdmult, x->rddiv,
+                             (bits << (VP10_PROB_COST_SHIFT - 4)), err);
+    if (cost_wiener >= cost_norestore) process_tile[tile_idx] = 0;
+  }
+  // Cost for Wiener filtering
+  bits = 0;
+  for (tile_idx = 0; tile_idx < ntiles; ++tile_idx) {
+    bits += (process_tile[tile_idx] ? (WIENER_FILT_BITS + 1) : 1);
+    rsi.wiener_level[tile_idx] = process_tile[tile_idx];
+  }
+  err = try_restoration_frame(src, cpi, &rsi, partial_frame);
+  cost_wiener = RDCOST_DBL(x->rdmult, x->rddiv,
+                           (bits << (VP10_PROB_COST_SHIFT - 4)), err);
+
+  for (tile_idx = 0; tile_idx < ntiles; ++tile_idx) {
+    if (process_tile[tile_idx] == 0) continue;
+    for (i = 0; i < RESTORATION_HALFWIN; ++i) {
+      vfilter[tile_idx][i] = rsi.vfilter[tile_idx][i];
+      hfilter[tile_idx][i] = rsi.hfilter[tile_idx][i];
+    }
+  }
+
+  vpx_free(rsi.vfilter);
+  vpx_free(rsi.hfilter);
+  vpx_free(rsi.wiener_level);
+
+  vpx_yv12_copy_y(&cpi->last_frame_uf, cm->frame_to_show);
+  if (cost_wiener < cost_norestore) {
+    if (best_cost_ret) *best_cost_ret = cost_wiener;
+    return 1;
+  } else {
+    if (best_cost_ret) *best_cost_ret = cost_norestore;
+    return 0;
+  }
+}
+
+void vp10_pick_filter_restoration(const YV12_BUFFER_CONFIG *sd, VP10_COMP *cpi,
+                                  LPF_PICK_METHOD method) {
+  VP10_COMMON *const cm = &cpi->common;
+  struct loopfilter *const lf = &cm->lf;
+  int wiener_success = 0;
+  int bilateral_success = 0;
+  double cost_bilateral = DBL_MAX;
+  double cost_wiener = DBL_MAX;
+  double cost_norestore = DBL_MAX;
+  int ntiles;
+
+  ntiles =
+      vp10_get_restoration_ntiles(BILATERAL_TILESIZE, cm->width, cm->height);
+  cm->rst_info.bilateral_level =
+      (int *)vpx_realloc(cm->rst_info.bilateral_level,
+                         sizeof(*cm->rst_info.bilateral_level) * ntiles);
+  assert(cm->rst_info.bilateral_level != NULL);
+
+  ntiles = vp10_get_restoration_ntiles(WIENER_TILESIZE, cm->width, cm->height);
+  cm->rst_info.wiener_level = (int *)vpx_realloc(
+      cm->rst_info.wiener_level, sizeof(*cm->rst_info.wiener_level) * ntiles);
+  assert(cm->rst_info.wiener_level != NULL);
+  cm->rst_info.vfilter = (int(*)[RESTORATION_HALFWIN])vpx_realloc(
+      cm->rst_info.vfilter, sizeof(*cm->rst_info.vfilter) * ntiles);
+  assert(cm->rst_info.vfilter != NULL);
+  cm->rst_info.hfilter = (int(*)[RESTORATION_HALFWIN])vpx_realloc(
+      cm->rst_info.hfilter, sizeof(*cm->rst_info.hfilter) * ntiles);
+  assert(cm->rst_info.hfilter != NULL);
+
+  lf->sharpness_level = cm->frame_type == KEY_FRAME ? 0 : cpi->oxcf.sharpness;
+
+  if (method == LPF_PICK_MINIMAL_LPF && lf->filter_level) {
+    lf->filter_level = 0;
+    cm->rst_info.restoration_type = RESTORE_NONE;
+  } else if (method >= LPF_PICK_FROM_Q) {
+    const int min_filter_level = 0;
+    const int max_filter_level = vp10_get_max_filter_level(cpi);
+    const int q = vp10_ac_quant(cm->base_qindex, 0, cm->bit_depth);
+// These values were determined by linear fitting the result of the
+// searched level, filt_guess = q * 0.316206 + 3.87252
+#if CONFIG_VP9_HIGHBITDEPTH
+    int filt_guess;
+    switch (cm->bit_depth) {
+      case VPX_BITS_8:
+        filt_guess = ROUND_POWER_OF_TWO(q * 20723 + 1015158, 18);
+        break;
+      case VPX_BITS_10:
+        filt_guess = ROUND_POWER_OF_TWO(q * 20723 + 4060632, 20);
+        break;
+      case VPX_BITS_12:
+        filt_guess = ROUND_POWER_OF_TWO(q * 20723 + 16242526, 22);
+        break;
+      default:
+        assert(0 &&
+               "bit_depth should be VPX_BITS_8, VPX_BITS_10 "
+               "or VPX_BITS_12");
+        return;
+    }
+#else
+    int filt_guess = ROUND_POWER_OF_TWO(q * 20723 + 1015158, 18);
+#endif  // CONFIG_VP9_HIGHBITDEPTH
+    if (cm->frame_type == KEY_FRAME) filt_guess -= 4;
+    lf->filter_level = clamp(filt_guess, min_filter_level, max_filter_level);
+    bilateral_success = search_bilateral_level(
+        sd, cpi, lf->filter_level, method == LPF_PICK_FROM_SUBIMAGE,
+        cm->rst_info.bilateral_level, &cost_bilateral);
+    wiener_success = search_wiener_filter(
+        sd, cpi, lf->filter_level, method == LPF_PICK_FROM_SUBIMAGE,
+        cm->rst_info.vfilter, cm->rst_info.hfilter, cm->rst_info.wiener_level,
+        &cost_wiener);
+    if (cost_bilateral < cost_wiener) {
+      if (bilateral_success)
+        cm->rst_info.restoration_type = RESTORE_BILATERAL;
+      else
+        cm->rst_info.restoration_type = RESTORE_NONE;
+    } else {
+      if (wiener_success)
+        cm->rst_info.restoration_type = RESTORE_WIENER;
+      else
+        cm->rst_info.restoration_type = RESTORE_NONE;
+    }
+  } else {
+    int blf_filter_level = -1;
+    bilateral_success = search_filter_bilateral_level(
+        sd, cpi, method == LPF_PICK_FROM_SUBIMAGE, &blf_filter_level,
+        cm->rst_info.bilateral_level, &cost_bilateral);
+    lf->filter_level = vp10_search_filter_level(
+        sd, cpi, method == LPF_PICK_FROM_SUBIMAGE, &cost_norestore);
+    wiener_success = search_wiener_filter(
+        sd, cpi, lf->filter_level, method == LPF_PICK_FROM_SUBIMAGE,
+        cm->rst_info.vfilter, cm->rst_info.hfilter, cm->rst_info.wiener_level,
+        &cost_wiener);
+    if (cost_bilateral < cost_wiener) {
+      lf->filter_level = blf_filter_level;
+      if (bilateral_success)
+        cm->rst_info.restoration_type = RESTORE_BILATERAL;
+      else
+        cm->rst_info.restoration_type = RESTORE_NONE;
+    } else {
+      if (wiener_success)
+        cm->rst_info.restoration_type = RESTORE_WIENER;
+      else
+        cm->rst_info.restoration_type = RESTORE_NONE;
+    }
+    // printf("[%d] Costs %g %g (%d) %g (%d)\n", cm->rst_info.restoration_type,
+    //        cost_norestore, cost_bilateral, lf->filter_level, cost_wiener,
+    //        wiener_success);
+  }
+  if (cm->rst_info.restoration_type != RESTORE_BILATERAL) {
+    vpx_free(cm->rst_info.bilateral_level);
+    cm->rst_info.bilateral_level = NULL;
+  }
+  if (cm->rst_info.restoration_type != RESTORE_WIENER) {
+    vpx_free(cm->rst_info.vfilter);
+    cm->rst_info.vfilter = NULL;
+    vpx_free(cm->rst_info.hfilter);
+    cm->rst_info.hfilter = NULL;
+    vpx_free(cm->rst_info.wiener_level);
+    cm->rst_info.wiener_level = NULL;
+  }
+}