diff --git a/bit2image.py b/bit2image.py
index edcda1ebb4f294eec139727248ba78b8c85dee75..e7b78b7bd96c2e612cba85c344d000019313fb8f 100644
--- a/bit2image.py
+++ b/bit2image.py
@@ -1,15 +1,130 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright 2019
+# Author: Gonzalo Belcredi, gbelcredi@fing.edu.uy
+# Instituto de Ingenieria Electrica, Facultad de Ingenieria,
+# Universidad de la Republica, Uruguay.
+#
+# This is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 3, or (at your option)
+# any later version.
+#
+# This software is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this software; see the file COPYING. If not, write to
+# the Free Software Foundation, Inc., 51 Franklin Street,
+# Boston, MA 02110-1301, USA.
+
from PIL import Image
import numpy as np
+import math
+filename_bin = 'dat/recepcion_2.dat'
+img_height = 800
+img_width = 549
+sync_start = [0,128,255]*10
+sync_size = 30
-array_rx = np.fromfile('dat/recepcion.dat', dtype='uint8')
-columnas = 830
-filas = len(array_rx)/830
-array_rx = array_rx[0:filas*columnas]
+array_rx = np.fromfile(filename_bin, dtype='uint8')
+columnas = img_height + sync_size
+filas = len(array_rx)/columnas
+DECODE_IMAGE = False
-image_rx=np.reshape(array_rx,(filas, columnas))
+def get_PSNR(image1,image2):
+ value = 0
+
+ matrix = np.asarray(image1, dtype="int8" )
+ matrix_rx = np.asarray(image2, dtype="int8" )
+
+ M = matrix.shape[0]
+ N = matrix.shape[1]
+
+ for i in range(0,M):
+ for j in range(0,N):
+ value += (float(matrix[i,j])-float(matrix_rx[i,j])) **2
+
+ MSE = value /(M * N)
+ if MSE < 10e-6:
+ MSE = 10e-6
+ PSNR = 10 * math.log10((2**8-1)/MSE)
+
+ return MSE,PSNR
+
+def get_sync_peaks(signal, sync):
+ """!@brief Devuelve los indices de comienzo del cuadro de sincronización.
+ @param signal Señal
+ @param sync Vector de sincronización
+ @result peaks Indices de sincronización.
+ """
+ # list of maximum correlations found: (index, value)
+ peaks_corr = [(0, 0)]
+
+ # minimum distance between peaks
+ mindistance = columnas*img_width - 1000
+
+ # need to shift the values down to get meaningful correlation values
+ signalshifted = [x-128 for x in signal]
+ sync = [x-128 for x in sync]
+
+ for i in range(0,len(signalshifted) - len(sync)):
+
+ corr = np.dot(sync, signalshifted[i : i+len(sync)])
+
+ # if previous peak is too far, keep it and add this value to the
+ # list as a new peak
+ if i - peaks_corr[-1][0] > mindistance:
+ peaks_corr.append((i, corr))
+
+ # else if this value is bigger than the previous maximum, set this
+ # one
+ elif corr > peaks_corr[-1][1]:
+ peaks_corr[-1] = (i, corr)
+ peaks = [i[0] for i in peaks_corr] # retrieve peak indexes from peaks_corr
+
+ return peaks
+
+
+''' Visualización de señal en recepción '''
+
+array_rx = array_rx[0:filas*columnas]
+image_rx=np.reshape(array_rx,(filas, columnas))
image = Image.fromarray(image_rx.astype('uint8'))
image.save('images/imagen_recibida.png')
image.show()
+
+
+if DECODE_IMAGE:
+ peaks = get_sync_peaks(array_rx,sync_start)
+ nr_images = len(peaks)
+ print "Se identificaron ", nr_images, " imágenes."
+ print "Indices de comienzo de imagen:", peaks
+
+ for i in range(0,nr_images):
+ if (peaks[i]+img_width*columnas) < len(array_rx):
+ array = array_rx[peaks[i]:peaks[i]+img_width*columnas]
+ matrix = np.reshape(array,(img_width, columnas))
+
+ ''' Quito el frame de sincronización para recuperar la imagen original'''
+ matrix_deframed = matrix[:,30:]
+ image = Image.fromarray(matrix_deframed.astype('uint8'))
+ image.save('images/imagen_recibida_'+str(i+1)+'.png')
+ image.show()
+
+
+ ''' Calculo MSE y PSNR '''
+ img = Image.open('images/image.png' )
+ img_rx = Image.open('images/imagen_recibida_1.png') #Seleccionar aquí la imagen correspondiente
+ img.load()
+ img_rx.load()
+
+ MSE, PSNR = get_PSNR(img,img_rx)
+ print "MSE: ", MSE
+ print "PSNR (dB): ", PSNR
\ No newline at end of file
diff --git a/dat/recepcion.dat b/dat/recepcion.dat
index b5fe8e392b088fc1705b1a39894e91efd7af1b06..3490eb8ecad54f07fb4d9f5100e1ce96125b5c90 100644
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diff --git a/dat/recepcion_1.dat b/dat/recepcion_1.dat
deleted file mode 100644
index 3490eb8ecad54f07fb4d9f5100e1ce96125b5c90..0000000000000000000000000000000000000000
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diff --git a/images/image.png b/images/image.png
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diff --git a/images/imagen_frame_recibida.png b/images/imagen_frame_recibida.png
new file mode 100644
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diff --git a/images/imagen_recibida.png b/images/imagen_recibida.png
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diff --git a/images/imagen_recibida_5.png b/images/imagen_recibida_5.png
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diff --git a/images/imagen_recibida_6.png b/images/imagen_recibida_6.png
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