Abstract: Techniques are provided for temporal control of a spatially adaptive tone mapping (SATM). The techniques can be applied to a sequence of video images (e.g., high dynamic range (HDR) video). The temporal control may reduce flickering and other undesirable artifacts that can be introduced by SATM processing. An example system includes an SATM circuit configured to perform SATM on sequential image frames of an input video, to reduce the dynamic range of the video to a level suitable for display on a conventional (lower dynamic range) device. The SATM operation is based on frame parameters. The system also includes a parameter smoothing circuit configured to apply a smoothing filter to the parameters used on the current frame to generate a new set of parameters for use by the SATM circuit on the next frame. The system also includes an adaptation circuit to compress variation of SATM exposure correction over time.

Abstract: Video stabilization is described using content-aware camera motion estimation. In some versions a luminance target frame and a luminance source frame of a sequence of video frames of a scene are received. Motion is extracted from the received luminance target and source frames and the motion is represented as a motion vector field and weights. The weights are divided into a first set of zeros weights for motion in the motion vector field that is near zero motion and a second set of peak weights for motion in the motion field that is not near zero. The zeros weights are compared to a threshold to determine whether there is motion in the scene and if the zeros weights exceed the threshold then selecting a zero motion motion model. A frame of the video sequence is adjusted corresponding to the target frame based on the selected motion model.

Abstract: Video stabilization is described using content-aware camera motion estimation. In some versions a luminance target frame and a luminance source frame of a sequence of video frames of a scene are received. Motion is extracted from the received luminance target and source frames and the motion is represented as a motion vector field and weights. The weights are divided into a first set of zeros weights for motion in the motion vector field that is near zero motion and a second set of peak weights for motion in the motion field that is not near zero. The zeros weights are compared to a threshold to determine whether there is motion in the scene and if the zeros weights exceed the threshold then selecting a zero motion motion model. A frame of the video sequence is adjusted corresponding to the target frame based on the selected motion model.

Abstract: Techniques are provided for spatially adaptive tone mapping for display or reproduction of HDR images on devices with lower dynamic range capability. An example system may include a log-conversion circuit to convert luminance data, from a received image, to a logarithm domain. The system may also include an edge-aware filter circuit to decompose the log domain luminance data into a base layer, a small scale detail layer, and a large scale detail layer. The system may further include an amplitude adjustment circuit to shift and scale data amplitudes in each of the layers to a selected range and a linear-conversion circuit to convert the adjusted layers from the log domain back to the linear domain. The system may further include a tone compression circuit to generate compressed linear domain layers and a luminance data reconstruction circuit to generate compressed luminance data based on the compressed linear domain layers.