Image loses quality with cv2.warpPerspective

I am working with OpenCV 3.1 and with Python.

My problem comes when I try to deskew (fix the tilt of) an image with text. I am using cv2.warpPerspective to make it possible, but the image loses a lot of quality. You can see here the original part of the image:

and then, here, the "rotated" image:

it is like smoothed.

I was using morphological transformation like:

kernel = np.ones((2, 2), np.uint8)
blur_image = cv2.erode(tresh, kernel, iterations=1)

and

white_mask2 = cv2.morphologyEx(white_mask2, cv2.MORPH_OPEN, kernel)

to see if it improves something, but nothing.

I saw this example here in SO, but those guys had the same problem: and

So, I don't have idea what can I do. Maybe there is a way to not losing the quality of the image, or, there's another method to rotate the image without quality lost. I know this method:

root_mat = cv2.getRotationMatrix2D(to_rotate_center, angle, 1.0)
result = cv2.warpAffine(to_rotate, root_mat, to_rotate.shape, flags=cv2.INTER_LINEAR)

But it doesn't work for me, as I have to rotate every rectangle here:

and not the whole image. It means, the best way I found to do it, was warpPerspective, and it works fine, but with quality loss. I would appreciate an advice to avoid the quality lost.

The problem is related to the interpolation required by the warping. If you don't want things to appear smoother, you should switch from default interpolation method, which is INTER_LINEAR to another one, such as INTER_NEAREST. It would help you with the sharpness of the edges.

Try flags=cv2.INTER_NEAREST on your warp call, be it warpAffine() or warpPerspective().

Interpolation flags are listed here.

enum InterpolationFlags { 
    INTER_NEAREST = 0, 
    INTER_LINEAR = 1, 
    INTER_CUBIC = 2, 
    INTER_AREA = 3, 
    INTER_LANCZOS4 = 4, 
    INTER_MAX = 7, 
    WARP_FILL_OUTLIERS = 8, 
    WARP_INVERSE_MAP = 16 
}