Python implementation of homomorphic filtering for image enhancement - 20221204 work summary

reference

[1]https://wenku.baidu.com/view/4eb598180a12a21614791711cc7931b765ce7ba9.html?wkts=1670054222364&bdQuery=%E5%90%8C%E6%80%81%E6%BB%A4%E6%B3%A2python%E5%AE%9E%E7%8E%B0

Homomorphic filtering python implementation

code

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

def cv_show(name,img):
    cv2.imshow(name,img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


def homomorphic_filter(src,d0=10,r1=0.5,rh=2,c=4,h=2.0,l=0.5):
    gray = src
    if len(src.shape)>2:
        gray = cv2.cvtColor(src,cv2.COLOR_BGR2GRAY)
    gray = np.float64(gray)
    rows,cols = gray.shape
    gray_fft = np.fft.fft2(gray)
    gray_fftshift = np.fft.fftshift(gray_fft)
    dst_fftshift = np.zeros_like(gray_fftshift)
    M,N = np.meshgrid(np.arange(-cols//2,cols//2),np.arange(-rows//2,rows//2))
    D = np.sqrt(M**2+N**2)
    Z = (rh-r1)*(1-np.exp(-c*(D**2/d0**2)))+r1
    dst_fftshift = Z*gray_fftshift
    dst_fftshift = (h-l)*dst_fftshift+l
    dst_ifftshift = np.fft.ifftshift(dst_fftshift)
    dst_ifft = np.fft.ifft2(dst_ifftshift)
    dst = np.real(dst_ifft)
    dst = np.uint8(np.clip(dst,0,255))
    return dst

imageDir = "./img/"
saveDir = "./HomoFilter_results/"

for name in os.listdir(imageDir):
    img = Image.open(os.path.join(imageDir, name))
    img = img.convert('L')
    img = np.array(img)
    #print(img,img.shape)
    img_new = homomorphic_filter(img)
    #print('new img shape is {}',format(img_new.shape))
    #cv_show('1',img_new)
    cv2.imwrite(os.path.join(saveDir, name),img_new)

Effect

Original image on the left, enhancement on the bottom

Aiming at the tiny blisters, it has a certain enhancement effect
Original image on the left, enhancement on the right