Abstract: A technique for modifying digital video includes receiving a plurality of digital video frames recorded by a camera. Each frame has a spherical field of view and a viewing angle associated therewith, where the viewing angle is with respect to a fixed reference frame. A motion of the camera relative to the fixed reference frame is calculated across at least some of the digital video frames. The viewing angle associated with each digital video frame is reoriented during post-processing of the digital video frames based at least in part on the calculated motion of the camera and at least one constraint to produce a digitally modified video such the viewing angle associated with at least one of the reoriented digital video frames is different than the viewing angle associated with the same digital video frame before reorientation.

Abstract: A low-illumination image processing method and device address the problem of noise amplification in existing contrast enhancement techniques when applied to original low-illumination image. A noise suppression filter is additionally arranged before an operation of contrast enhancement, and smoothing processing is performed on an inverse color image of a low-illumination image by adopting a first filtering coefficient and a second filtering coefficient, so that image contrast is enhanced while random noise is suppressed. Texture and noise level parameter of an image are calculated according to a local characteristic inside block of the image. Weighted averaging is performed on a first smoothing image and a second smoothing image after smoothing processing according to the texture and noise level parameters.

Abstract: A technique for modifying digital video includes receiving a plurality of digital video frames recorded by a camera. Each frame has a spherical field of view and a viewing angle associated therewith, where the viewing angle is with respect to a fixed reference frame. A motion of the camera relative to the fixed reference frame is calculated across at least some of the digital video frames. The viewing angle associated with each digital video frame is reoriented during post-processing of the digital video frames based at least in part on the calculated motion of the camera and at least one constraint to produce a digitally modified video such the viewing angle associated with at least one of the reoriented digital video frames is different than the viewing angle associated with the same digital video frame before reorientation.

Abstract: A low-illumination image processing method and device address the problem of noise amplification in existing contrast enhancement techniques when applied to original low-illumination image. A noise suppression filter is additionally arranged before an operation of contrast enhancement, and smoothing processing is performed on an inverse color image of a low-illumination image by adopting a first filtering coefficient and a second filtering coefficient, so that image contrast is enhanced while random noise is suppressed. Texture and noise level parameter of an image are calculated according to a local characteristic inside block of the image. Weighted averaging is performed on a first smoothing image and a second smoothing image after smoothing processing according to the texture and noise level parameters.

Abstract: A motion vector estimation method in video encoding: First, a feature point is detected in a video frame. Next, motion estimation is performed on the feature point to obtain a motion vector of the feature point. Next, the feature point is mapped to a feature image block, and the motion vector of the feature point is used as an initial motion vector of the feature image block. Finally, a distance between each image block and the feature image block is calculated, motion estimation is performed on the image blocks in an ascending order of the distances between the image blocks and the feature image block, and an obtained motion vector of an image block is used as an initial motion vector of an image block that is adjacent to the image block and has not undergone motion estimation, until motion estimation is completed for the image blocks in the entire video frame.

Abstract: A motion vector estimation method in video encoding: First, a feature point is detected in a video frame. Next, motion estimation is performed on the feature point to obtain a motion vector of the feature point. Next, the feature point is mapped to a feature image block, and the motion vector of the feature point is used as an initial motion vector of the feature image block. Finally, a distance between each image block and the feature image block is calculated, motion estimation is performed on the image blocks in an ascending order of the distances between the image blocks and the feature image block, and an obtained motion vector of an image block is used as an initial motion vector of an image block that is adjacent to the image block and has not undergone motion estimation, until motion estimation is completed for the image blocks in the entire video frame.