/*
* Copyright 2009 ZXing authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*      http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

namespace ZXing.Common
{
   /// <summary> This class implements a local thresholding algorithm, which while slower than the
   /// GlobalHistogramBinarizer, is fairly efficient for what it does. It is designed for
   /// high frequency images of barcodes with black data on white backgrounds. For this application,
   /// it does a much better job than a global blackpoint with severe shadows and gradients.
   /// However it tends to produce artifacts on lower frequency images and is therefore not
   /// a good general purpose binarizer for uses outside ZXing.
   /// 
   /// This class extends GlobalHistogramBinarizer, using the older histogram approach for 1D readers,
   /// and the newer local approach for 2D readers. 1D decoding using a per-row histogram is already
   /// inherently local, and only fails for horizontal gradients. We can revisit that problem later,
   /// but for now it was not a win to use local blocks for 1D.
   /// 
   /// This Binarizer is the default for the unit tests and the recommended class for library users.
   /// 
   /// </summary>
   /// <author>  dswitkin@google.com (Daniel Switkin)
   /// </author>
   /// <author>www.Redivivus.in (suraj.supekar@redivivus.in) - Ported from ZXING Java Source 
   /// </author>
   public sealed class HybridBinarizer : GlobalHistogramBinarizer
   {
      override public BitMatrix BlackMatrix
      {
         get
         {
            binarizeEntireImage();
            return matrix;
         }
      }

      // This class uses 5x5 blocks to compute local luminance, where each block is 8x8 pixels.
      // So this is the smallest dimension in each axis we can accept.
      private const int BLOCK_SIZE_POWER = 3;
      private const int BLOCK_SIZE = 1 << BLOCK_SIZE_POWER; // ...0100...00
      private const int BLOCK_SIZE_MASK = BLOCK_SIZE - 1;   // ...0011...11
      private const int MINIMUM_DIMENSION = 40;
      private const int MIN_DYNAMIC_RANGE = 24;

      private BitMatrix matrix = null;

      public HybridBinarizer(LuminanceSource source)
         : base(source)
      {
      }

      public override Binarizer createBinarizer(LuminanceSource source)
      {
         return new HybridBinarizer(source);
      }

      /// <summary>
      /// Calculates the final BitMatrix once for all requests. This could be called once from the
      /// constructor instead, but there are some advantages to doing it lazily, such as making
      /// profiling easier, and not doing heavy lifting when callers don't expect it.
      /// </summary>
      private void binarizeEntireImage()
      {
         if (matrix == null)
         {
            LuminanceSource source = LuminanceSource;
            int width = source.Width;
            int height = source.Height;
            if (width >= MINIMUM_DIMENSION && height >= MINIMUM_DIMENSION)
            {
               byte[] luminances = source.Matrix;

               int subWidth = width >> BLOCK_SIZE_POWER;
               if ((width & BLOCK_SIZE_MASK) != 0)
               {
                  subWidth++;
               }
               int subHeight = height >> BLOCK_SIZE_POWER;
               if ((height & BLOCK_SIZE_MASK) != 0)
               {
                  subHeight++;
               }
               int[][] blackPoints = calculateBlackPoints(luminances, subWidth, subHeight, width, height);

               var newMatrix = new BitMatrix(width, height);
               calculateThresholdForBlock(luminances, subWidth, subHeight, width, height, blackPoints, newMatrix);
               matrix = newMatrix;
            }
            else
            {
               // If the image is too small, fall back to the global histogram approach.
               matrix = base.BlackMatrix;
            }
         }
      }

      /// <summary>
      /// For each 8x8 block in the image, calculate the average black point using a 5x5 grid
      /// of the blocks around it. Also handles the corner cases (fractional blocks are computed based
      /// on the last 8 pixels in the row/column which are also used in the previous block).
      /// </summary>
      /// <param name="luminances">The luminances.</param>
      /// <param name="subWidth">Width of the sub.</param>
      /// <param name="subHeight">Height of the sub.</param>
      /// <param name="width">The width.</param>
      /// <param name="height">The height.</param>
      /// <param name="blackPoints">The black points.</param>
      /// <param name="matrix">The matrix.</param>
      private static void calculateThresholdForBlock(byte[] luminances, int subWidth, int subHeight, int width, int height, int[][] blackPoints, BitMatrix matrix)
      {
         for (int y = 0; y < subHeight; y++)
         {
            int yoffset = y << BLOCK_SIZE_POWER;
            int maxYOffset = height - BLOCK_SIZE;
            if (yoffset > maxYOffset)
            {
               yoffset = maxYOffset;
            }
            for (int x = 0; x < subWidth; x++)
            {
               int xoffset = x << BLOCK_SIZE_POWER;
               int maxXOffset = width - BLOCK_SIZE;
               if (xoffset > maxXOffset)
               {
                  xoffset = maxXOffset;
               }
               int left = cap(x, 2, subWidth - 3);
               int top = cap(y, 2, subHeight - 3);
               int sum = 0;
               for (int z = -2; z <= 2; z++)
               {
                  int[] blackRow = blackPoints[top + z];
                  sum += blackRow[left - 2];
                  sum += blackRow[left - 1];
                  sum += blackRow[left];
                  sum += blackRow[left + 1];
                  sum += blackRow[left + 2];
               }
               int average = sum / 25;
               thresholdBlock(luminances, xoffset, yoffset, average, width, matrix);
            }
         }
      }

      private static int cap(int value, int min, int max)
      {
         return value < min ? min : value > max ? max : value;
      }

      /// <summary>
      /// Applies a single threshold to an 8x8 block of pixels.
      /// </summary>
      /// <param name="luminances">The luminances.</param>
      /// <param name="xoffset">The xoffset.</param>
      /// <param name="yoffset">The yoffset.</param>
      /// <param name="threshold">The threshold.</param>
      /// <param name="stride">The stride.</param>
      /// <param name="matrix">The matrix.</param>
      private static void thresholdBlock(byte[] luminances, int xoffset, int yoffset, int threshold, int stride, BitMatrix matrix)
      {
         int offset = (yoffset * stride) + xoffset;
         for (int y = 0; y < BLOCK_SIZE; y++, offset += stride)
         {
            for (int x = 0; x < BLOCK_SIZE; x++)
            {
               int pixel = luminances[offset + x] & 0xff;
               // Comparison needs to be <= so that black == 0 pixels are black even if the threshold is 0.
               matrix[xoffset + x, yoffset + y] = (pixel <= threshold);
            }
         }
      }

      /// <summary>
      /// Calculates a single black point for each 8x8 block of pixels and saves it away.
      /// See the following thread for a discussion of this algorithm:
      /// http://groups.google.com/group/zxing/browse_thread/thread/d06efa2c35a7ddc0
      /// </summary>
      /// <param name="luminances">The luminances.</param>
      /// <param name="subWidth">Width of the sub.</param>
      /// <param name="subHeight">Height of the sub.</param>
      /// <param name="width">The width.</param>
      /// <param name="height">The height.</param>
      /// <returns></returns>
      private static int[][] calculateBlackPoints(byte[] luminances, int subWidth, int subHeight, int width, int height)
      {
         int[][] blackPoints = new int[subHeight][];
         for (int i = 0; i < subHeight; i++)
         {
            blackPoints[i] = new int[subWidth];
         }

         for (int y = 0; y < subHeight; y++)
         {
            int yoffset = y << BLOCK_SIZE_POWER;
            int maxYOffset = height - BLOCK_SIZE;
            if (yoffset > maxYOffset)
            {
               yoffset = maxYOffset;
            }
            for (int x = 0; x < subWidth; x++)
            {
               int xoffset = x << BLOCK_SIZE_POWER;
               int maxXOffset = width - BLOCK_SIZE;
               if (xoffset > maxXOffset)
               {
                  xoffset = maxXOffset;
               }
               int sum = 0;
               int min = 0xFF;
               int max = 0;
               for (int yy = 0, offset = yoffset * width + xoffset; yy < BLOCK_SIZE; yy++, offset += width)
               {
                  for (int xx = 0; xx < BLOCK_SIZE; xx++)
                  {
                     int pixel = luminances[offset + xx] & 0xFF;
                     // still looking for good contrast
                     sum += pixel;
                     if (pixel < min)
                     {
                        min = pixel;
                     }
                     if (pixel > max)
                     {
                        max = pixel;
                     }
                  }
                  // short-circuit min/max tests once dynamic range is met
                  if (max - min > MIN_DYNAMIC_RANGE)
                  {
                     // finish the rest of the rows quickly
                     for (yy++, offset += width; yy < BLOCK_SIZE; yy++, offset += width)
                     {
                        for (int xx = 0; xx < BLOCK_SIZE; xx++)
                        {
                           sum += luminances[offset + xx] & 0xFF;
                        }
                     }
                  }
               }

               // The default estimate is the average of the values in the block.
               int average = sum >> (BLOCK_SIZE_POWER * 2);
               if (max - min <= MIN_DYNAMIC_RANGE)
               {
                  // If variation within the block is low, assume this is a block with only light or only
                  // dark pixels. In that case we do not want to use the average, as it would divide this
                  // low contrast area into black and white pixels, essentially creating data out of noise.
                  //
                  // The default assumption is that the block is light/background. Since no estimate for
                  // the level of dark pixels exists locally, use half the min for the block.
                  average = min >> 1;

                  if (y > 0 && x > 0)
                  {
                     // Correct the "white background" assumption for blocks that have neighbors by comparing
                     // the pixels in this block to the previously calculated black points. This is based on
                     // the fact that dark barcode symbology is always surrounded by some amount of light
                     // background for which reasonable black point estimates were made. The bp estimated at
                     // the boundaries is used for the interior.

                     // The (min < bp) is arbitrary but works better than other heuristics that were tried.
                     int averageNeighborBlackPoint = (blackPoints[y - 1][x] + (2 * blackPoints[y][x - 1]) +
                         blackPoints[y - 1][x - 1]) >> 2;
                     if (min < averageNeighborBlackPoint)
                     {
                        average = averageNeighborBlackPoint;
                     }
                  }
               }
               blackPoints[y][x] = average;
            }
         }
         return blackPoints;
      }
   }
}