Estimate white background - opencv

Question

I have image with white uneven background (due to lighting). I'm trying to estimate background color and transform image into image with true white background. For this I estimated white color for each 15x15 pixels block based on its luminosity. So I've got the following map (on the right):
Now I want to interpolate color so it will be more smooth transition from 15x15 block to neighboring block, plus I want it to eliminate outliers (pink dots on left hand side). Could anyone suggest good technique/algorithm for this? (Ideally within OpenCV library, but not necessary)

Answer 1

Starting from this image:
You could find the text on the whiteboard as the parts of your images that have a high gradient, and apply a little dilation to deal with thick parts of the text. You'll get a mask that separates background from foreground pretty well:
Background:
Foreground:
You can then apply inpainting using the computed mask on the original image (you need OpenCV contrib module photo):
Just to show that this works independently of the text color, I tried on a different image:
Resulting in:
Code:
#include <opencv2/opencv.hpp>
#include <opencv2/photo.hpp>
using namespace cv;
void findText(const Mat3b& src, Mat1b& mask)
{
// Convert to grayscale
Mat1b gray;
cvtColor(src, gray, COLOR_BGR2GRAY);
// Compute gradient magnitude
Mat1f dx, dy, mag;
Sobel(gray, dx, CV_32F, 1, 0);
Sobel(gray, dy, CV_32F, 0, 1);
magnitude(dx, dy, mag);
// Remove low magnitude, keep only text
mask = mag > 10;
// Apply a dilation to deal with thick text
Mat1b K = getStructuringElement(MORPH_ELLIPSE, Size(3, 3));
dilate(mask, mask, K);
}
int main(int argc, const char * argv[])
{
Mat3b img = imread("path_to_image");
// Segment white
Mat1b mask;
findText(img, mask);
// Show intermediate images
Mat3b background = img.clone();
background.setTo(0, mask);
Mat3b foreground = img.clone();
foreground.setTo(0, ~mask);
// Apply inpainting
Mat3b inpainted;
inpaint(img, mask, inpainted, 21, CV_INPAINT_TELEA);
imshow("Original", img);
imshow("Foreground", foreground);
imshow("Background", background);
imshow("Inpainted", inpainted);
waitKey();
return 0;
}