Obtaining a depth map

A method comprising:

• a) for each image pixel of a depth map:
• a1) acquiring samples via a corresponding imager pixel and calculating a distance from the samples, each imager pixel belonging to an array of imager pixels of an indirect time of flight sensor, and
• a2) defining a window of N*N image pixels with the image pixel at a center of the window, N being an odd integer equal to or greater than 3;
• b) for each window:
• b1) classifying the image pixels of the window into groups, the groups and the classification of the image pixels into the groups being determined by a distance threshold and the distances calculated for the image pixels of the window, each group corresponding to a range of distances, and each image pixel of the window being classified into the group in response to the distance calculated for the image pixel being comprised in the range of distances of the group,
• b2) for each group of the window:
• calculating a number of image pixels in the group, and
• calculating a confidence factor of each image pixel and a confidence factor of the group equal to a sum of the confidence factors of the image pixels of the group, the confidence factor of each image pixel being determined from the samples acquired for the image pixel, and
• b3) scanning the image pixels of the window from a central image pixel by comparing, for each scanned image pixel, the confidence factor of the group of the image pixel with a first threshold and the number of image pixels in the group of the image pixel with a second threshold, and determining whether the central image pixel is retained or replaced with another image pixel of the window, or discarded from the depth map based on the comparisons.

A method comprising:

• a) for each image pixel of a depth map:
• a1) acquiring samples via a corresponding imager pixel and calculating a distance from the samples, and
• a2) defining a window of N*N image pixels with the image pixel at a center of the window, N being an odd integer equal to or greater than 3;
• b) for each window:
• b1) classifying the image pixels of the window into groups, the groups and the classification of the image pixels into the groups being determined by a distance threshold and the distances calculated for the image pixels of the window,
• b2) for each group of the window:
• calculating a number of image pixels in the group, and
• calculating a confidence factor of each image pixel and a confidence factor of the group equal to a sum of the confidence factors of the image pixels of the group, the confidence factor of each image pixel being determined from the samples acquired for the image pixel, and
• b3) scanning, in a spiral pattern, the image pixels of the window from a central image pixel by comparing, for each scanned image pixel, the confidence factor of the group of the image pixel with a first threshold and the number of image pixels in the group of the image pixel with a second threshold, the first and second thresholds being empirically determined, and determining whether the central image pixel is retained replaced with another image pixel of the window, or discarded from the depth map based on the comparisons.