Abstract: A method and apparatus for estimating the motion of an image region (the “center” region) from a source video frame to a target video frame. The motion estimation is locally constrained in that the estimated motion of the “center region” is affected by the estimated motion of neighboring regions. Advantageously, this may reduce common motion matching problems such as false and ambiguous matches. In one embodiment, the locally-constrained motion estimation may be implemented by biasing an error map of the center region using error maps of the neighboring regions.

Abstract: A method and apparatus for estimating the motion of an image region (the “center” region) from a source video frame to a target video frame. The motion estimation is locally constrained in that the estimated motion of the “center region” is affected by the estimated motion of neighboring regions. Advantageously, this may reduce common motion matching problems such as false and ambiguous matches. In one embodiment, the locally-constrained motion estimation may be implemented by biasing an error map of the center region using error maps of the neighboring regions.

Abstract: A method and apparatus for estimating the motion of an image region (the “center” region) from a source video frame to a target video frame. The motion estimation is locally constrained in that the estimated motion of the “center region” is affected by the estimated motion of neighboring regions. Advantageously, this may reduce common motion matching problems such as false and ambiguous matches. In one embodiment, the locally-constrained motion estimation may be implemented by biasing an error map of the center region using error maps of the neighboring regions.

Abstract: A method and apparatus for estimating the motion of an image region (the “center” region) from a source video frame to a target video frame. The motion estimation is locally constrained in that the estimated motion of the “center region” is affected by the estimated motion of neighboring regions. Advantageously, this may reduce common motion matching problems such as false and ambiguous matches. In one embodiment, the locally-constrained motion estimation may be implemented by biasing an error map of the center region using error maps of the neighboring regions.

Abstract: Using image segmentation in video compression brings about a limitation in video quality when a segment moves in position from frame to frame. The limitation arises because color contributions (bleeding or blurring) naturally occur between neighboring segments. The above-identified problem is overcome by providing solutions to compensate for color contributions between neighboring segments. In accordance with one embodiment, a method and apparatus de-blurs an image segment. De-blurring involves removing from the segment approximate color contributions from neighboring segments. This results in a segment that is approximately independent of color contributions from neighboring segments. In accordance with another embodiment, a method and apparatus re-blurs an image segment. Re-blurring involves adding to the segment approximate color contributions from a new arrangement of neighboring segments. This results in more realistic rendering of the segment, as it is located in the new arrangement.

Abstract: A method and apparatus for estimating the motion of an image region (the “center” region) from a source video frame to a target video frame. The motion estimation is locally constrained in that the estimated motion of the “center region” is affected by the estimated motion of neighboring regions. Advantageously, this may reduce common motion matching problems such as false and ambiguous matches. In one embodiment, the locally-constrained motion estimation may be implemented by biasing an error map of the center region using error maps of the neighboring regions.

Abstract: Using image segmentation in video compression brings about a limitation in video quality when a segment moves in position from frame to frame. The limitation arises because color contributions (bleeding or blurring) naturally occur between neighboring segments. The above-identified problem is overcome by providing solutions to compensate for color contributions between neighboring segments. In accordance with one embodiment, a method and apparatus de-blurs an image segment. De-blurring involves removing from the segment approximate color contributions from neighboring segments. This results in a segment that is approximately independent of color contributions from neighboring segments. In accordance with another embodiment, a method and apparatus re-blurs an image segment. Re-blurring involves adding to the segment approximate color contributions from a new arrangement of neighboring segments. This results in more realistic rendering of the segment, as it is located in the new arrangement.