Abstract: The invention concerns image data processing, through noise reduction comprising the following steps: associating a learning zone (ZA) with a reference point (Pref) of the image (IM); for each variable point (PC, PC?) of the learning zone, evaluating a distance (d,d?,) between: values of points in a first window (f1) of the image, centered on the reference point, and values of points in a second window (f2, f2,), of similar format as the format of the first window and centered on the variable point; repeating said distance calculation for all the points of the learning zone as successive variable points and estimating an average value to assign to the reference point, said average being weighted on the basis of the distances evaluated for each variable point.

Abstract: The invention concerns image data processing, through noise reduction comprising the following steps: associating a learning zone (ZA) with a reference point (Pref) of the image (IM); for each variable point (PC, PC?) of the learning zone, evaluating a distance (d,d?,) between: values of points in a first window (f1) of the image, centered on the reference point, and values of points in a second window (f2, f2,), of similar format as the format of the first window and centered on the variable point; repeating said distance calculation for all the points of the learning zone as successive variable points and estimating an average value to assign to the reference point, said average being weighted on the basis of the distances evaluated for each variable point.

Abstract: The invention concerns image data processing, through noise reduction comprising the following steps: associating a learning zone (ZA) with a reference point (Pref) of the image (IM); for each variable point (PC, PC?,) of the learning zone, evaluating a distance (d, d?,) between: values of points in a first window (f1) of the image, centered on the reference point, and values of points in a second window (f2, f?2,), of similar format as the format of the first window and centered on the variable point; repeating said distance calculation for all the points of the learning zone as successive variable points and estimating an average value to assign to the reference point, said average being weighted on the basis of the distances evaluated for each variable point.