lzz 77 compression image rgb

Question

if I insert an image of size (205,205) the algorithm compresses it very quickly. But if I insert a larger image, the algorithm takes a very long time to compress it. my intention would be to optimize the code and consequently speed up the compression phase do you have any suggestions?

library

from PIL import Image
import numpy as np 
from cv2 import cv2

**function of compression**

def lz77Compress (image,sw,lab):
    img = cv2.imread(image)
    flat = np.array(img).flatten()
    row = img.shape[0]
    col = img.shape[1]
    ch = img.shape[2]
    tot = row * col * ch
    slidingWindows = sw
    lookAhead = lab 

array of tuple and char

 encodedTuple = np.array([], dtype=np.uint16) 
    encodedChar = np.array([], dtype=np.uint8)
    **# Lunghezza del Search Buffer**

sbSize = slidingWindows - lookAhead
    for it in range(sbSize):
        encodedTuple = np.append(encodedTuple, (0, 0))
        encodedChar = np.append(encodedChar, flat[it])
    **# pointer in the  Search Buffer**
 sbPointer = 0
while sbPointer < tot :
        max_match = 0
        max_match_go_back = 0        
        selChar = sbPointer + sbSize
     # corrispondenza del carattere in Sb da lookAd
        encodeCharacters = flat[selChar] 
    **#sequenza vuota[]**
       seqY = np.array([],dtype=np.int16)
        for i in range(sbPointer,sbPointer + sbSize):
            if(flat[i] == encodeCharacters):
                seqY = np.append(seqY,i)
        
    **check of corrispondence and insert in encodedtuple and encodedChar**
        if(seqY.size == 0 ):
            encodedTuple = np.append(encodedTuple,(0,0))
            encodedChar = np.append (encodedChar,encodeCharacters)

else:
            for j in seqY:
            **size of corrisponddence**
                matchLenght= 0
                returnBack= selChar - j
                it = 0 
                while selChar + it < tot :
                    if flat[it + j] == flat[selChar + it]:
                        matchLenght +=1
                        it +=1
                  **# if there is not corrispondence*
                    else: 
                        break
                if matchLenght>max_match:
                   max_match = matchLenght
                   returnBack= max_match_go_back

           
            encodedTuple = np.append(encodedTuple,(max_match_go_back,max_match))
            encodedChar = np.append(encodedChar,flat[selChar + max_match - 1])
            
        sbPointer+= 1 +max_match
    **save encoedTupe and encodedChar and image size for the compression**
    np.save("encodedTuple", encodedTuple) 
    np.save("encodedChar", encodedChar)
    print("File compresso in : Copressed.txt")
    output = open("Compressed.txt","w+")
    output.write(str(c))