Inter frame

About: Inter frame is a research topic. Over the lifetime, 4154 publications have been published within this topic receiving 63549 citations.

Methods for adaptive noise reduction based on global motion estimation

Abstract: An improved temporal noise reduction method and system detects the global motion and adjusts the overall gain of the temporal filtering. Temporal noise reduction is applied to two video frames, wherein one video frame is the current input noisy frame, and the other video frame is a previous filtered frame stored in memory. In this method, noise estimation is first performed to estimate the noise variance/standard deviation in the input video sequence. Then, motion estimation is applied to obtain the motion vectors indicating relative motion between the pixels in the current noisy frame and the corresponding pixels in the previous noise-reduced frame. From such motion vectors, global motion estimation is applied to estimate the camera motion of the video sequence. If reliable global motion is obtained, the overall gain of the temporal filtering is reduced by adjusting the estimated noise level. Motion blur is thus prevented.

Apparatus and method for motion detection of image in digital video recording system using MPEG video compression

Abstract: Provided are apparatus and method for precise motion detection in a digital video recording (DVR) system using a Moving Picture Expert Group (MPEG) video compression technique and a computer-readable recording medium for recording a program that implements the method. The motion detection apparatus performs motion detection by using a motion vector generated in the MPEG video compression process. The motion detection apparatus includes: a motion estimation unit for receiving a reference image frame and a current image frame, and estimating a motion vector (MV=(mx,my)) for a motion of an object; a motion compensation unit for calculating a motion compensated prediction error E MV (i) based on the estimated motion vector (MV=(mx,my)); a frame difference calculation unit for calculating a frame difference between the reference image frame and the current image frame; a motion block accumulation unit for accumulating the number (B motion ) of motion blocks in the current image frame based on the motion compensated prediction error E MV (i) and the frame difference E 0 (i); and a motion frame determination unit for determining whether the current image frame has a motion, based on the accumulated number B motion of motion blocks.

Method and apparatus for estimating motion vector fields by rejecting local outliers

Abstract: An image analysis system generates a motion vector field from first and second images in a sequence of steps. First, random, initial motion vector values are assigned to each pixel in the image frame. Next, an objective function is defined for each motion vector and its corresponding motion vector in the other frame. The differences between the motion vectors of the target pixel value in the current frame and the other frame are minimized by minimizing the objective function values, first based on all neighboring pixel values. Next, the motion vector differences are further minimized by reducing the objective function values by rejecting motion vectors which correspond to the neighboring pixel values for which the value of the difference between the respective objective functions is outside of a threshold range. In one embodiment, pixel values in the first image frame are compared to neighboring pixel values in a second image frame which occurs after the first image and to other neighboring pixel values in a third image frame which occurs before the first image frame. This embodiment substantially eliminates motion vector errors due to both motion discontinuities and occlusion of pixels in the image.

Video signal processing to derive motion vectors representing motion between successive fields or frames

Abstract: A method of processing a digital video signal to derive motion vectors representing motion between successive fields or frames of the video signal comprises compares the contents of blocks of pixels in a first field or frame of the video signal with the contents of a plurality of blocks of pixels in a following field or frame, and produces for each block in the first field or frame a correlation surface representing the difference between the contents so compared in the two fields or frames. A grown correlation surface is produced for each block in the first field or frame by weighting the correlation surfaces for that block and a plurality of other blocks in an area around that block so as to accentuate features of the correlation surface for that block relative to those for the other blocks, and summing the weighted correlation surfaces. From each grown correlation surface, a motion vector is derived representing the motion of the content of the corresponding block between the two frames in dependence upon a minimum difference value represented by the grown correlation surface.

Motion compensation using second-order geometric transformations

Abstract: Motion compensation is a very effective process which can be used in video data compression for increasing the prediction accuracy in inter-frame coding. The conventional way of performing motion compensation as defined in the H.261 and MPEG standards, is to divide the "new" frame into a number of nonoverlapping rectangular blocks and then find the best match for each of these blocks by displacing a search window of the same size in the "previous" frame (or also the next frame for bidirectional prediction in MPEG). A block prediction based on this method is only accurate if the motion between the two frames is of a translational nature. There is no flexibility to change the size, rotation, or shape of objects if the motion that has taken place between the two frames contains such distortion. We evaluate the use of second-order geometric transformations (GTs) as a means of motion compensation. These transformations are capable of modeling the kind of changes mentioned above and therefore when used properly they have the potential of providing a much more accurate prediction during motion compensation. >