如何修复图像中的损坏文本

Question

我有一幅需要校正其亮度和对比度的图像，并且代码需要是动态的，以便将来在获得新图像时，我可以轻松地运行相同的代码来校正亮度和对比度，而无需对图像进行任何更改。代码。

我能够正确校正图像的亮度和对比度。

import cv2
import numpy as np
import glob,os,sys
from PIL import Image, ImageEnhance 

class ImageEnhancement:  

    def readImages(inputFolder):
        ext = ['.png', '.jpg', '.gif', '.jpeg', '.tif', '.tiff']
        files = []
        path = inputFolder + '/*.*'
        files = glob.glob(path)
        imageFiles=[]
        for i in files:
                exten=os.path.splitext(i)[1]
                if exten in ext:
                        imageFiles.append(i)
        return imageFiles

    def processImages(imageFiles):
        for imagePath in imageFiles:
            img_name = os.path.splitext(os.path.basename(imagePath))[0]
            new_folder = sys.argv[2]+'/'+img_name+'/'
            os.makedirs(new_folder, exist_ok=True)

            src_img = cv2.imread(imagePath)


            #Create the identity filter, but with the 1 shifted to the right!
            kernel = np.zeros( (9,9), np.float32)
            kernel[4,4] = 2.0   #Identity, times two! 

            #Create a box filter:
            boxFilter = np.ones( (9,9), np.float32) / 81.0

            #Subtract the two:
            kernel = kernel - boxFilter

            #Note that we are subject to overflow and underflow here...but I believe that
            # filter2D clips top and bottom ranges on the output, plus you'd need a
            # very bright or very dark pixel surrounded by the opposite type.

            custom = cv2.filter2D(src_img, -1, kernel)

            img_hsv = cv2.cvtColor(custom, cv2.COLOR_BGR2HSV)
            img_hsv[:,:,2] = [[max(pixel - 25, 0) if pixel < 190 else min(pixel + 25, 255) for pixel in row] for row in img_hsv[:,:,2]]

            #cv2.imwrite(new_folder+'/'+img_name+'.png',cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR))

            grayscaled = cv2.cvtColor(cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR),cv2.COLOR_BGR2GRAY)
            retval, threshold = cv2.threshold(grayscaled, 200, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)

            #k = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], np.uint8)
            #closing = cv2.morphologyEx(threshold, cv2.MORPH_CLOSE, k)
            #cv2.imshow("closing", closing)
            #cv2.waitKey(0)
            #cv2.destroyAllWindows()

            #k1 = np.ones((3, 3), np.uint8)
            #erosion = cv2.erode(threshold, k1, iterations = 1)
            #cv2.imshow("erosion", erosion)
            #cv2.waitKey(0)
            #cv2.destroyAllWindows()

            #contour,_= cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
            #cv2.drawContours(threshold,contour, -1, 0,0)

            #kernel = np.zeros((2,1),np.uint8)
            #dilation = cv2.dilate(threshold,kernel,iterations=1)

            #kernel = np.zeros((3,3),np.uint8)
            #erosion = cv2.erode(threshold,kernel,iteration=1)
            #dilation = cv2.morphologyEx(threshold, cv2.MORPH_CLOSE, kernel)

            cv2.imwrite(new_folder+'/'+img_name+'.png',threshold)



imageFiles = ImageEnhancement.readImages(sys.argv[1])
ImageEnhancement.processImages(imageFiles)

在输出的图像中，亮度和对比度得到了校正，但是出现了一个新问题，即几乎没有字符被损坏（只有半个字符可用）。我希望获得相同的帮助，以便我可以在图像中获得完整的字符。

Input Image

Output with damaged characters