CODEWITHSUNDEEP
pythonopencv
Wesley
Wesley

Reputation: 1947

How to remove light impact on image

Here is origin image:

Now, I wanna remove the light impact to get image like this:

And, I am trying to get it by the following code:

#!/usr/bin/env python
# coding: utf-8
import cv2
import numpy as np
debug = True
table = np.array([((i / 255.0) ** (1.0/0.3)) * 255 for i in np.arange(0, 256)]).astype("uint8")


def parse(image):
    dilated_img = cv2.dilate(image, np.ones((7, 7), np.uint8))
    # if debug:
    #     cv2.imshow('dilated', dilated_img)
    #     cv2.waitKey(0)
    bg_img = cv2.medianBlur(dilated_img, 21)
    # if debug:
    #     cv2.imshow('median blur', bg_img)
    #     cv2.waitKey(0)
    diff_img = 255 - cv2.absdiff(image, bg_img)
    if debug:
        cv2.imshow('origin vs back diff', diff_img)
        cv2.waitKey(0)
    norm_img = diff_img.copy()
    cv2.normalize(diff_img, diff_img, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8UC1)
    if debug:
        cv2.imshow('first norm', norm_img)
        cv2.waitKey(0)
    _, thr_img = cv2.threshold(norm_img, 253, 0, cv2.THRESH_TRUNC)

    # thr_img = norm_img
    cv2.normalize(thr_img, thr_img, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8UC1)


    thr_img = cv2.LUT(thr_img, table)
    if debug:
        cv2.imshow('second norm', thr_img)
        cv2.waitKey(0)
        cv2.destroyAllWindows()
    compare = cv2.resize(np.hstack([image, cv2.imread("reult.JPEG", 0), thr_img]), None, fx=0.5, fy=0.5)
    cv2.imshow("Analysis", compare)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    cv2.imwrite('./nijie.jpg', thr_img)


if __name__ == '__main__':
    parse(cv2.imread("original.JPG", 0))

I got image like this:

Seems almost done, but the middle is a little dark, and the top right line is not so clear.

Is there any way to make it better?

Env:

Python: 3.6.5

Opencv: 3.4.0

Any suggestion for this is appreciated.

Thanks.

Upvotes: 3

Views: 2012

Answers (1)

fmw42
fmw42

Reputation: 53091

You can improve your image by using adaptive thresholding in Python/OpenCV.

Input:

enter image description here

import cv2

# read image
img = cv2.imread("kanji.jpg")

# convert img to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# do adaptive threshold on gray image
thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 51, 25)

# write results to disk
cv2.imwrite("kanji_threshold.jpg", thresh)

# display it
cv2.imshow("THRESHOLD", thresh)
cv2.waitKey(0)

Threshold:

enter image description here

Upvotes: 1

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