Hello! I have this

The code I used is: import os

import cv2

import numpy as np

import matplotlib.pyplot as plt

import rasterio

from skimage import exposure, filters

def load_rgb_image(folder_path, red_band, green_band, blue_band):

# Lista de nume de fișiere TIF din folder

file_names = os.listdir(folder_path)

# Citirea datelor din benzile specifice

bands_data =  ]

for band in ired_band, green_band, blue_band]:

    band_path = os.path.join(folder_path, band + '.tif')

    with rasterio.open(band_path) as src:

        band_data = src.read(1)

        bands_data.append(band_data)



# Crearea imaginii RGB

rgb_image = np.dstack(bands_data)



return rgb_image

Setare căi către foldere

folder_path_1 = “/content/drive/MyDrive/sentinel/S2A_MSIL2A_20170426T091031_N0204_R050_T35TMK_20170426T091503_buc”

folder_path_2 = “/content/drive/MyDrive/sentinel/S2A_MSIL2A_20170705T090551_N0205_R050_T35TMK_20170705T090814_buc”

Specificarea benzilor roșu, verde și albastru pentru RGB

red_band = “B04”

green_band = “B03”

blue_band = “B02”

Încărcarea imaginii RGB pentru Sentinel-2A

image1 = load_rgb_image(folder_path_1, red_band, green_band, blue_band)

image2 = load_rgb_image(folder_path_2, red_band, green_band, blue_band)

Ajustarea contrastului și luminozității

image1_adjusted = exposure.adjust_gamma(image1, gamma=1.2)

image2_adjusted = exposure.adjust_gamma(image2, gamma=1.2)

Ajustarea contrastului și luminozității folosind ajustare sigmoidală

image1_sigmoid_adjusted = exposure.adjust_sigmoid(image1, cutoff=0.5, gain=10)

image2_sigmoid_adjusted = exposure.adjust_sigmoid(image2, cutoff=0.5, gain=10)

Egalizarea histogramei

image1_eq = exposure.equalize_hist(image1_adjusted)

image2_eq = exposure.equalize_hist(image2_adjusted)

Aplicarea filtrului unsharp

image1_unsharp = filters.unsharp_mask(image1_eq, radius=1.0, amount=1.0)

image2_unsharp = filters.unsharp_mask(image2_eq, radius=1.0, amount=1.0)

Afisare imagini

plt.figure(figsize=(10, 5))

plt.subplot(1, 2, 1)

plt.imshow(image1_unsharp, cmap=‘gray’)

plt.title(‘26 aprilie 2017’)

plt.subplot(1, 2, 2)

plt.imshow(image2_unsharp, cmap=‘gray’)

plt.title(‘5 iulie 2017’)

plt.tight_layout()

plt.show()

Now my task is to display the histograms for the three channels, and then calculate the Kullback-Leibler divergence. I tried, but on my code, it doesn’t display anything. It only displays something if I use image1 and image2 (not image1_unsharp, image2_unsharp), but it doesn’t display correctly because the Kullback-Leibler divergence gives me 0 even though the images are different.

I believe I don’t have the correct code for displaying the images, even though I can see them properly. Could you please help me with a correct code to display the histogram and calculate the divergence?