H04N19/63

Video encoding system
11653026 · 2023-05-16 · ·

A video encoding system in which pixel data is decomposed into frequency bands prior to encoding. The frequency bands are organized into blocks that are provided to a block-based encoder. The encoded frequency data is packetized and transmitted to a receiving device. On the receiving device, the encoded data is decoded to recover the frequency bands. Wavelet synthesis is then performed on the frequency bands to reconstruct the pixel data for display. The system may encode parts of frames (tiles or slices) using one or more encoders and transmit the encoded parts as they are ready. A pre-filter component may perform a lens warp on the pixel data prior to the wavelet transform.

Dynamic lighting capture and reconstruction

Systems and techniques for dynamically capturing and reconstructing lighting are provided. The systems and techniques may be based on a stream of images capturing the lighting within an environment as a scene is shot. Reconstructed lighting data may be used to illuminate a character in a computer-generated environment as the scene is shot. For example, a method may include receiving a stream of images representing lighting of a physical environment. The method may further include compressing the stream of images to reduce an amount of data used in reconstructing the lighting of the physical environment and may further include outputting the compressed stream of images for reconstructing the lighting of the physical environment using the compressed stream, the reconstructed lighting being used to render a computer-generated environment.

AUTOMATED WAVELET-BASED DATA COMPRESSION SYSTEMS AND METHODS
20170359478 · 2017-12-14 · ·

Systems and methods for processing online data are disclosed. One such method includes receiving a plurality of data points in a time-series at a short term storage. The method also includes calculating at least one approximation coefficient based on the plurality of data points using a wavelet transform, including calculating a highest level approximation coefficient, and calculating estimated value based on the highest level approximation coefficient. The method further includes calculating differences between the estimated value and the plurality of data points of the short term storage, and determining whether a maximum difference among the calculated differences is less than a predetermined threshold. The method further includes, based on the maximum difference being greater than or equal to the predetermined threshold, storing the oldest data point of the short term storage in a long term storage.

Encoding and decoding based on blending of sequences of samples along time

Computer processor hardware receives image data specifying element settings for each image of multiple original images in a sequence. The computer processor hardware analyzes the element settings across the multiple original images. The computer processor hardware then utilizes the element settings of the multiple original images in the sequence to produce first encoded image data specifying a set of common image element settings, the set of common image element settings being a baseline to substantially reproduce each of the original images in the sequence.

Encoding and decoding based on blending of sequences of samples along time

Computer processor hardware receives image data specifying element settings for each image of multiple original images in a sequence. The computer processor hardware analyzes the element settings across the multiple original images. The computer processor hardware then utilizes the element settings of the multiple original images in the sequence to produce first encoded image data specifying a set of common image element settings, the set of common image element settings being a baseline to substantially reproduce each of the original images in the sequence.

CASCADE CONVOLUTIONAL NEURAL NETWORK

In one embodiment, an apparatus comprises a communication interface and a processor. The communication interface is to communicate with a plurality of devices. The processor is to: receive compressed data from a first device, wherein the compressed data is associated with visual data captured by sensor(s); perform a current stage of processing on the compressed data using a current CNN, wherein the current stage of processing corresponds to one of a plurality of processing stages associated with the visual data, and wherein the current CNN corresponds to one of a plurality of CNNs associated with the plurality of processing stages; obtain an output associated with the current stage of processing; determine, based on the output, whether processing associated with the visual data is complete; if the processing is complete, output a result associated with the visual data; if the processing is incomplete, transmit the compressed data to a second device.

IMAGE ENCODING APPARATUS AND CONTROL METHOD THEREFOR
20170353724 · 2017-12-07 ·

An image encoding apparatus includes a plane conversion unit which generates, from image data of one frame of the moving image data, a plurality of planes each formed from a single component, a frequency conversion unit which generates a plurality of subbands for each plane by performing frequency conversion for each plane, a quantization unit which quantizes coefficients in each subband using a quantization parameter, an encoder which encodes the quantized coefficient data, and a control unit which updates the quantization parameter so that a code amount of the encoded data becomes equal to a target code amount set for each plane. The control unit updates the quantization parameter by accumulating a difference between the target code amount set for each plane and a generated code amount of each plane, and distributing the accumulated differences to the plurality of planes.

Online Training of Hierarchical Algorithms

A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method comprising receiving at least a plurality of neighbouring sections of lower-quality visual data. A plurality of input sections from the received plurality of neighbouring sections of lower quality visual data are selected and features are extracted from those plurality of input sections of lower-quality visual data. A target section based on the extracted features from the plurality of input sections of lower-quality visual data is then enhanced.

Methods And Systems For Wavelet Based Representation
20220365946 · 2022-11-17 ·

Methods and systems for representing data are disclosed. An example method can comprise providing a first representation of data and receiving a request to change resolution of the data. An example method can comprise, transforming, based on at least one wavelet function, the data to at least one of reduced data or expanded data. An example method can comprise providing a second representation of the data based on at least one of the reduced data or expanded data.

Methods And Systems For Wavelet Based Representation
20220365946 · 2022-11-17 ·

Methods and systems for representing data are disclosed. An example method can comprise providing a first representation of data and receiving a request to change resolution of the data. An example method can comprise, transforming, based on at least one wavelet function, the data to at least one of reduced data or expanded data. An example method can comprise providing a second representation of the data based on at least one of the reduced data or expanded data.