Added automated bit sync and BER

bit2image.py

@@ -24,18 +24,67 @@
 from PIL import Image
 import numpy as np
 import math
+import pickle
+
+
+filename_bin = 'dat/received_241022_2.dat'
+DECODE_IMAGE = True
 
-filename_bin = 'dat/recepcion.dat'
 img_height = 800
 img_width = 549
 sync_start = [0,128,255]*10
 sync_size = 30
 
-array_rx = np.fromfile(filename_bin, dtype='uint8')
-columnas = img_height + sync_size
-filas = int(len(array_rx)/columnas)
 
-DECODE_IMAGE = True
+def sync_bits(array_bytes):
+    print('\n Performing bit synchronization...',end="")
+    nr_shift = 0
+    corr = correlate_preamble(array_bytes)
+    for i in range(1,7):
+        array_bytes_shifted = shift_bits_bytes(array_bytes,shift_nr_bits=i,nr_bytes=len(array_bytes))
+        corr_i = correlate_preamble(array_bytes_shifted)
+        if corr_i > corr:
+            nr_shift = i
+            corr = corr_i
+    print("Shifting {} bits. ".format(nr_shift),end="")
+    print('Completed!')
+    return shift_bits_bytes(array_bytes,shift_nr_bits=nr_shift,nr_bytes=len(array_bytes))
+
+def correlate_preamble(array_bytes):
+    sync_start = np.array([0,128,255]*10,dtype=np.float32)
+    return np.max(np.correlate(array_bytes.astype(np.float32)-127.0, sync_start-127.0,mode = 'valid'))
+
+def shift_bits_bytes(array_bytes,shift_nr_bits,nr_bytes):
+    bits = [format(x,'08b') for x in array_bytes[0:nr_bytes]]
+
+    array_bytes_sync = np.zeros(len(bits)-1,dtype='uint8')
+
+    for i in range(len(bits)-1):
+        # Shift bits and get new bytes
+        array_bytes_sync[i] = int(bits[i][shift_nr_bits:] + bits[i+1][0:shift_nr_bits],2)
+
+    return array_bytes_sync
+
+def get_BER(image_bytes):
+    filename_baseline_bin = 'dat/imagen_bin.dat'
+    
+    array_baseline_bytes = np.fromfile(filename_baseline_bin, dtype='uint8')
+    array_received_bytes = image_bytes.flatten()
+
+    total_bits = 8*len(array_baseline_bytes)
+    bit_errors = 0
+    for i in range(len(array_baseline_bytes)):
+        bits_baseline = format(array_baseline_bytes[i],'08b')
+        bits_received = format(array_received_bytes[i],'08b')
+        errors = sum(bits_baseline != bits_received for bits_baseline,bits_received in zip(bits_baseline,bits_received))
+        bit_errors += errors
+    return bit_errors/total_bits
+
+
+
+
+
+
 
 def get_PSNR(image1,image2):
     value = 0
@@ -92,9 +141,16 @@ def get_sync_peaks(signal, sync):
     return peaks 
 
 
-''' Visualización de señal en recepción '''
 
-array_rx = array_rx[0:filas*columnas]
+array_bytes = np.fromfile(filename_bin, dtype='uint8')
+array_bytes_sync = sync_bits(array_bytes)
+
+columnas = img_height + sync_size
+filas = int(len(array_bytes_sync)/columnas)
+
+
+''' Visualización de señal en recepción '''
+array_rx = array_bytes_sync[0:filas*columnas]
 image_rx=np.reshape(array_rx,(filas, columnas))
 image = Image.fromarray(image_rx.astype('uint8'))
 image.save('images/imagen_recibida.png')
@@ -102,29 +158,44 @@ image.show()
 
 
 if DECODE_IMAGE:
+    print('\n Decoding image...',end="")
     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)
+    print('Completed!')
+    nr_images = len(peaks) - 1
+    print("\n Se identificaron ", nr_images, " imágenes.")
+
 
     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))
 
+            with open('images/imagen_recibida_'+str(i)+'.pkl', 'wb') as handle:
+                pickle.dump(matrix, handle, protocol=pickle.HIGHEST_PROTOCOL)
+
             ''' 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.save('images/imagen_recibida_'+str(i)+'.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()
+    for i in range(0,nr_images):
+        img_rx = Image.open('images/imagen_recibida_'+str(i)+'.png') #Seleccionar aquí la imagen correspondiente
         img_rx.load()
 
         MSE, PSNR = get_PSNR(img,img_rx)
+        print("\nImage ",i, ":\n")
         print("MSE: ", MSE)
         print("PSNR (dB): ", PSNR)
+        try:
+            with open('images/imagen_recibida_'+str(i)+'.pkl', 'rb') as handle:
+                matrix_deframed = pickle.load(handle)
+                BER = get_BER(matrix_deframed)
+            print("BER: ", BER)
+        except:
+            print('I/O error.')
+