Histogram matching

import numpy as np
import cv2
from matplotlib import pyplot as plt
 
asli = cv2.imread('dst.jpg')
 
plt.imshow(cv2.cvtColor(asli, cv2.COLOR_BGR2RGB))
plt.axis('off')
plt.title('Destination image')
plt.show()
 
equ = np.copy(asli)
 
for i  in range (3) :
    equ[:,:,i] = cv2.equalizeHist(asli[:,:,i])
 
referensi =  cv2.imread('ref.jpg')
 
plt.imshow(cv2.cvtColor(referensi, cv2.COLOR_BGR2RGB))
plt.axis('off')
plt.title('Reference image')
plt.show()
 
hasilmatch = np.copy(asli)
 
def hist_match(asli, referensi):
 
    asli_shape = asli.shape
 
    asli = asli.ravel()
    referensi = referensi.ravel()
 
    o_values, bin_idx, o_counts = np.unique(asli, return_inverse=True,return_counts=True)
    b_values, b_counts = np.unique(referensi, return_counts=True)
 
    o_quantiles = np.cumsum(o_counts).astype(np.float64)
    o_quantiles /= o_quantiles[-1]
    b_quantiles = np.cumsum(b_counts).astype(np.float64)
    b_quantiles /= b_quantiles[-1]
 
    interp_t_values = np.interp(o_quantiles, b_quantiles, b_values)
 
    return interp_t_values[bin_idx].reshape(asli_shape)
 
for i  in range (3) :
    hasilmatch[:,:,i] = hist_match(asli[:,:,i], referensi[:,:,i])
 
plt.imshow(cv2.cvtColor(hasilmatch, cv2.COLOR_BGR2RGB))
plt.axis('off')
plt.title('Histogram matching')
plt.show()