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You can't get back information you lost due to pixel saturation. All you can do is to try some synthetic reconstruction using information from neighbour like cv::inpaint function does. Just to show, below is a simple code that use uses cv::inpaint.

//helper function
void Morphology(const Mat &imgIn,Mat &imgOut,int morpOp=MORPH_CLOSE,
                           int minThickess=2,int shape=MORPH_ELLIPSE)
{
  int size = minThickess / 2;
  Point anchor = Point(size, size);
  Mat element = getStructuringElement(shape, Size(2 * size + 1, 2 * size + 1), anchor);
  morphologyEx(imgIn, imgOut, morpOp, element, anchor);
}
void Main_Inpaint()
{
  Mat src,blur,mask,bkMask,fgMask,dst;
  vector<vector<Point> > contours;
  src = imread("pixel-saturation1.png");
  // remove noise
  cv::GaussianBlur(src,blur,Size(),2,2);
  //CREATE A MASK FOR THE SATURATED PIXEL
  int minBrightness=253;
  int dilateSize=20;
  //convert to HSV
  Mat src_hsv,brightness,saturation;
  vector<Mat> hsv_planes;
  cvtColor(blur, src_hsv, COLOR_BGR2HSV);
  split(src_hsv, hsv_planes);
  brightness = hsv_planes[2];
  //get the mask
  threshold(brightness,mask,minBrightness,255,THRESH_BINARY);
  //dialte a bit the selection
  Morphology(mask,mask,MORPH_DILATE,dilateSize);
  //INPAINTING
  float radius=5.0;
  inpaint(src,mask,dst,radius,INPAINT_NS);
  imshow("Navier-Stokes based method",dst);

  inpaint(src,mask,dst,radius,INPAINT_TELEA);
  imshow("Method by Alexandru Telea ",dst);
  //show the selection on src
  findContours(mask, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
  for (int i = 0; i < contours.size(); i++)
    drawContours(src,contours,i,Scalar(0,0,255),2);
  imshow("Inpaint mask",src);
  waitKey(0);
}

The result is pretty nice with 1st image but fails with your 2nd case.

I know it's a completely total different approach, but if you can control camera/acquisition, you could try to reduce the brightness/gain/shutter down to remove spotlight...

It would be easier to recover dark region if a bit of information will survive see Automated Removal of Partial Occlusion Blur for reference.

Another option is High Dynamic Range...

You can't get back information you lost due to pixel saturation. All you can do is to try some synthetic reconstruction using information from neighbour like cv::inpaint function does. Just to show, below is a simple code that use uses cv::inpaint.

//helper function
void Morphology(const Mat &imgIn,Mat &imgOut,int morpOp=MORPH_CLOSE,
                           int minThickess=2,int shape=MORPH_ELLIPSE)
{
  int size = minThickess / 2;
  Point anchor = Point(size, size);
  Mat element = getStructuringElement(shape, Size(2 * size + 1, 2 * size + 1), anchor);
  morphologyEx(imgIn, imgOut, morpOp, element, anchor);
}
void Main_Inpaint()
{
  Mat src,blur,mask,bkMask,fgMask,dst;
  vector<vector<Point> > contours;
  src = imread("pixel-saturation1.png");
  // remove noise
  cv::GaussianBlur(src,blur,Size(),2,2);
  //CREATE A MASK FOR THE SATURATED PIXEL
  int minBrightness=253;
  int dilateSize=20;
  //convert to HSV
  Mat src_hsv,brightness,saturation;
  vector<Mat> hsv_planes;
  cvtColor(blur, src_hsv, COLOR_BGR2HSV);
  split(src_hsv, hsv_planes);
  brightness = hsv_planes[2];
  //get the mask
  threshold(brightness,mask,minBrightness,255,THRESH_BINARY);
  //dialte a bit the selection
  Morphology(mask,mask,MORPH_DILATE,dilateSize);
  //INPAINTING
  float radius=5.0;
  inpaint(src,mask,dst,radius,INPAINT_NS);
  imshow("Navier-Stokes based method",dst);

  inpaint(src,mask,dst,radius,INPAINT_TELEA);
  imshow("Method by Alexandru Telea ",dst);
  //show the selection on src
  findContours(mask, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
  for (int i = 0; i < contours.size(); i++)
    drawContours(src,contours,i,Scalar(0,0,255),2);
  imshow("Inpaint mask",src);
  waitKey(0);
}

The result is pretty nice with 1st image but fails with your 2nd case.

I know it's a completely total different approach, but if you can control camera/acquisition, you could try to reduce the brightness/gain/shutter down to remove spotlight...

It would be easier to recover dark region if a bit of information will survive see Automated Removal of Partial Occlusion Blur for reference.

Another option is High Dynamic Range...