How to threshold a grayscale image with lighting and noise

Question

I am trying to threshold images with challenging noise.

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The numbers on the side are the dimensions. I have tried various standard methods:

ret,thresh1 = cv2.threshold(img,95,255,0) 
#cv2.THRESH_BINARY

thresh2 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,7,0.5)
thresh3 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,3,1.5)


# Otsu's thresholding after Gaussian filtering
blur = cv2.GaussianBlur(img,(3,3),0)
ret3,th3 = cv2.threshold(blur,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

I want to segment the "lighter" portion inside the darker grey zone (or vice versa). I have played with various kernel sizes, and constant values but nothing is giving me a good segmentation. Any ideas what else i can try or how to improve the results? Some sample results i get using the code is