Contrast Limited Adaptive Histogram Equalization in 360 images

I am currently applying the Contrast Limited Adaptive Histogram Equalization algorithm together with an algorithm to perform the photo denoise.

My problem is that I am working with 360 photos. As the contrast generates different values ​​at the edges when I join the photo, the edge line is highly noticeable. How can I mitigate that line? What changes should I make so that it is not noticeable and the algorithm is applied consistently?

Original Photo:

Code to Contrast Limited Adaptive Histogram Equalization:

    # CLAHE (Contrast Limited Adaptive Histogram Equalization)
    clahe = cv2.createCLAHE(clipLimit=1., tileGridSize=(6, 6))

    lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)  # convert from BGR to LAB color space
    l, a, b = cv2.split(lab)  # split on 3 different channels

    l2 = clahe.apply(l)  # apply CLAHE to the L-channel

    lab = cv2.merge((l2, a, b))  # merge channels
    img2 = cv2.cvtColor(lab, cv2.COLOR_LAB2BGR)  # convert from LAB to BGR


360 performed:

** It is highly notorious line of separation because it is not taken into account that the photo is joined later. What can I do?**