Abstract: Systems and methods for predicting a target set of pixels are disclosed. In one embodiment, a method may include obtaining target content. The target content may include a target set of pixels to be predicted. The method may also include convolving the target set of pixels to generate an estimated set of pixels. The method may include matching a second set of pixels in the target content to the target set of pixels. The second set of pixels may be within a distance from the target set of pixels. The method may include refining the estimated set of pixels to generate a refined set of pixels using a second set of pixels in the target content.

Abstract: Systems and methods are disclosed for compressing a target video. A computer-implemented method may use a computer system that include one or more physical computer processors and non-transient electronic storage. The computer-implemented method may include: obtaining the target video, extracting one or more frames from the target video, and generating an estimated optical flow based on a displacement of pixels between the one or more frames. The one or more frames may include one or more of a key frame and a target frame.

Abstract: Systems and methods for distortion removal at multiple quality levels are disclosed. In one embodiment, a method may include receiving training content. The training content may include original content, reconstructed content, and training distortion quality levels corresponding to the reconstructed content. The reconstructed content may be derived from distorted original content. The method may also include training distortion quality levels corresponding to the reconstructed content. The method may further include receiving an initial distortion removal model. The method may include generating a conditioned distortion removal model by training the initial distortion removal model using the training content. The method may further include storing the conditioned distortion removal model.

Abstract: A scene-by-scene (S×S) compression process enables improved visual quality within applicable compression constraints to be obtained. A compressed video signal is analyzed, generating compression statistics. A scene of the video signal is identified for re-compression and a maximum target bit rate for re-compressing the identified scene is determined based on the compression statistics and applicable compression constraints. A target bit rate for re-compressing the scene is selected based on the maximum target bit rate, and compression parameters for the scene are determined based on the scene's compression statistics and the selected target bit rate.

Abstract: Systems and methods of encoding a video signal that includes a succession of images are disclosed. A system may include a plurality of independently programmable processing elements (PEs), an input interface device adapted to receive, buffer, and divide the input video signal in a manner appropriate to the plurality of PEs, and an output interface device adapted to receive encoded bitstreams generated by the plurality of PEs and provide an encoded video signal. Each PE is configurable to carry out the steps of a selected encoding algorithm and includes a digital processor and a memory in communication with the digital processor. The memories are independently accessible, and PEs communicate with each another during the encoding.