The present invention discloses a method of volume-
panorama imaging processing, which generates a volume-
panorama image by subsequently splicing respective image frames from an
image sequence obtained in a real-time way or stored in a medium based upon the fact that the immediately adjacent image frames have the largest correlation. The method comprises the steps of: reading the
image sequence, and firstly initializing an aligned image and a spliced image; dividing the i-th
image frame Fi into a plurality of sub-regions; calculating a
motion vector of the i-t
image frame with respect to the aligned image; fitting the
motion vector to calculate a transform coefficient; splicing the Fi to the current spliced
image based upon the transform coefficient, and updating the aligned image; entering into a self-
adaptive selection of a next
image frame until the end of the splicing; and outputting the current spliced image as a
resultant image. Additionally, when the image Fi is spliced, double-filtering architecture of selecting characteristic points through a filtering and selecting the valid
motion vector of the selected characteristic points through the other filtering to reduce an alignment error may be adopted. According to the present invention, the volume-
panorama imaging can be done quickly and accurately so that the reliability of images particularly meets a very high requirement of the ultrasonic iatric diagnose.