def imageenhancement(image): hsv=cv2.cvtColor(image,cv2.COLOR_BGR2HSV) bgImg,fundusMask = computebgimg(image) bgImg = cv2.multiply(image[:,:,1].astype(float),bgImg.astype(float)) ldrift,cdrift = LumConDrift(bgImg,fundusMask) g = image[:,:,1].astype(float) imgCorr = cv2.divide(cv2.subtract(g,ldrift),(cv2.add(cdrift,0.0001))) imgCorr = cv2.multiply(imgCorr,fundusMask.astype(float)) imgCorr = cv2.add(imgCorr,np.abs(np.min(imgCorr))) imgCorr = cv2.divide(imgCorr,np.max(imgCorr)) imgCorr = cv2.multiply(imgCorr,fundusMask.astype(float)) image = image.astype(float) image[:,:,0] = cv2.divide(cv2.multiply(imgCorr,image[:,:,0]),hsv[:,:,2].astype(float)) image[:,:,1] = cv2.divide(cv2.multiply(imgCorr,image[:,:,1]),hsv[:,:,2].astype(float)) image[:,:,2] = cv2.divide(cv2.multiply(imgCorr,image[:,:,2]),hsv[:,:,2].astype(float)) fundusMask = fundusMask.astype(float) image[:,:,0] = cv2.multiply(image[:,:,0],fundusMask) image[:,:,1] = cv2.multiply(image[:,:,1],fundusMask) image[:,:,2] = cv2.multiply(image[:,:,2],fundusMask) out = image[:,:,1]*255 return out
import numpy as np import cv2 import cv2.cv as cv from PIL import Image import scipy import scipy.io from matplotlib import pyplot as plt from computebgimg import computebgimg from LumConDrift import LumConDrift image = cv2.imread( 'C:\Users\AK PUJITHA\Desktop\iiit h\semester 6\honors project 2\Image Enahancement-Matlab\output\image010.png', 1) hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) bgImg, fundusMask = computebgimg(image) bgImg = cv2.multiply(image[:, :, 1].astype(float), bgImg.astype(float)) ldrift, cdrift = LumConDrift(bgImg, fundusMask) g = image[:, :, 1].astype(float) imgCorr = cv2.divide(cv2.subtract(g, ldrift), (cv2.add(cdrift, 0.0001))) imgCorr = cv2.multiply(imgCorr, fundusMask.astype(float)) imgCorr = cv2.add(imgCorr, np.abs(np.min(imgCorr))) imgCorr = cv2.divide(imgCorr, np.max(imgCorr)) imgCorr = cv2.multiply(imgCorr, fundusMask.astype(float)) image = image.astype(float) image[:, :, 0] = cv2.divide(cv2.multiply(imgCorr, image[:, :, 0]), hsv[:, :, 2].astype(float)) image[:, :, 1] = cv2.divide(cv2.multiply(imgCorr, image[:, :, 1]),
import numpy as np import cv2 import cv2.cv as cv from PIL import Image import scipy import scipy.io from matplotlib import pyplot as plt from computebgimg import computebgimg from LumConDrift import LumConDrift image = cv2.imread('C:\Users\AK PUJITHA\Desktop\drive.jpg',1) hsv=cv2.cvtColor(image,cv2.COLOR_BGR2HSV) bgImg,fundusMask = computebgimg(image) bgImg = cv2.multiply(image[:,:,1].astype(float),bgImg.astype(float)) ldrift,cdrift = LumConDrift(bgImg,fundusMask) g = image[:,:,1].astype(float) imgCorr = cv2.divide(cv2.subtract(g,ldrift),(cv2.add(cdrift,0.0001))) imgCorr = cv2.multiply(imgCorr,fundusMask.astype(float)) imgCorr = cv2.add(imgCorr,np.abs(np.min(imgCorr))) imgCorr = cv2.divide(imgCorr,np.max(imgCorr)) imgCorr = cv2.multiply(imgCorr,fundusMask.astype(float)) image = image.astype(float) image[:,:,0] = cv2.divide(cv2.multiply(imgCorr,image[:,:,0]),hsv[:,:,2].astype(float)) image[:,:,1] = cv2.divide(cv2.multiply(imgCorr,image[:,:,1]),hsv[:,:,2].astype(float)) image[:,:,2] = cv2.divide(cv2.multiply(imgCorr,image[:,:,2]),hsv[:,:,2].astype(float))