Systems and methods for image compression at multiple, different bitrates

Number: 11983906
Published: 2024-05-14
Filed: 2022-03-25
Assignee: Disney Enterprises, Inc.
Inventors: Schroers; Christopher et al.
CPC: H04N19/50; H04N19/147; H04N19/124; G06T9/20
Verdict: Set aside image/video compression codec
Source: Google Patents · FreePatentsOnline

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.

Background

TECHNICAL FIELD (1) The present disclosure relates generally to image compression. BRIEF SUMMARY OF THE DISCLOSURE (2) Embodiments of the disclosure are directed to systems and methods for predicting a target set of pixels. (3) In one embodiment, a computer-implemented method may be implemented in a computer system that includes non-transient electronic storage and one or more physical computer processors. The computer-implemented method may include obtaining, from the non-transient electronic storage, target content that includes the target set of pixels to be predicted. The computer-implemented method may include convolving, with the one or more physical computer processors, the target set of pixels to generate an estimated set of pixels. The computer-implemented method may include matching, with the one or more physical computer processors, a second set of pixels in the target content to the target set of pixels. The second set of pixels is within a distance from the target set of pixels. The computer-implemented method may include refining, with the one or more physical computer processors, the estimated set of pixels to generate a refined set of pixels using a second set of pixels in the target content. (4) In embodiments, the computer-implemented method may further include generating, with the one or more physical computer processors, a residual between the refined set of pixels and the target set of pixels. (5) In embodiments, refining the estimated set of pixels may i

Claims

1. A computer-implemented method for compressing target content, the method comprising: selecting a target set of pixels from a plurality of pixels included in the target content; generating, using an auto-encoder included in a prediction neural network, an estimated set of pixels based on one or more convolutions performed on the target set of pixels; matching the target set of pixels to a second set of pixels included in the plurality of pixels; and generating, using a decoder included in the prediction neural network based on input that includes the estimated set of pixels and the second set of pixels, a refined set of pixels. || 11. One or more non-transitory computer-readable medium including instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of: selecting a target set of pixels from a plurality of pixels included in a target content; generating, using an auto-encoder included in a prediction neural network, an estimated set of pixels based on one or more convolutions performed on the target set of pixels; matching the target set of pixels to a second set of pixels included in the plurality of pixels; and generating, using a decoder included in the prediction neural network based on input that includes the estimated set of pixels and the second set of pixels, a refined set of pixels. || 20. A system comprising: one or more memories storing instructions; and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to: select a target set of pixels from a plurality of pixels included in a target content; generate, using an auto-encoder included in a prediction neural network, an estimated set of pixels based on one or more convolutions performed on the target set of pixels; match the target set of pixels to a second set of pixels included in the plurality of pixels; and generate, using a decoder included in the prediction neural network based on input that includes the estimated set of pixels and the second set of pixels, a refined set of pixels.