Methods and apparatus of video processing for a video coding system using Neural Network (NN) are disclosed. According to this method, a shifted region is determined for the filter region to avoid unavailable reconstructed or filtered-reconstructed video data for the NN processing of the filter region, where boundaries of the shifted region comprises region boundaries derived by shifting target boundaries upward, leftward, or both upward and leftward, and wherein the target boundaries correspond to one or more top boundaries and one or more left boundaries of target processing region including the current block and one or more remaining un-processed blocks. According to another method, the areas outside boundaries of pictures, slices, tiles, or tile groups are padded. In yet another method, a flag is used to indicate whether the NN processing is allowed to cross a boundary between two slices, two tiles or two tile groups.

A method, computer program, and computer system for video coding is provided. Video data including one or more quantized coefficients is received. One or more index values associated with the quantized coefficients are mapped to one or more step values based on an exponential mapping. The video data is decoded based on the one or more step values.

System and method for decoding digital video data. The decoding system employs hardware accelerators that assist a core processor in performing selected decoding tasks. The hardware accelerators are configurable to support a plurality of existing and future encoding/decoding formats. The accelerators are configurable to support substantially any existing or future encoding/decoding formats that fall into the general class of DCT-based, entropy decoded, block-motion-compensated compression algorithms. The hardware accelerators illustratively comprise a programmable entropy decoder, an inverse quantization module, a inverse discrete cosine transform module, a pixel filter, a motion compensation module and a de-blocking filter. The hardware accelerators function in a decoding pipeline wherein at any given stage in the pipeline, while a given function is being performed on a given macroblock, the next macroblock in the data stream is being worked on by the previous function in the pipeline.

System and method for decoding digital video data. The decoding system employs hardware accelerators that assist a core processor in performing selected decoding tasks. The hardware accelerators are configurable to support a plurality of existing and future encoding/decoding formats. The accelerators are configurable to support substantially any existing or future encoding/decoding formats that fall into the general class of DCT-based, entropy decoded, block-motion-compensated compression algorithms. The hardware accelerators illustratively comprise a programmable entropy decoder, an inverse quantization module, a inverse discrete cosine transform module, a pixel filter, a motion compensation module and a de-blocking filter. The hardware accelerators function in a decoding pipeline wherein at any given stage in the pipeline, while a given function is being performed on a given macroblock, the next macroblock in the data stream is being worked on by the previous function in the pipeline.

Systems and methods are disclosed for image signal processing. For example, systems may include an image sensor and a processing apparatus. The image sensor captures image data using a plurality of selectable exposure times. The processing apparatus receives a first image from the image sensor captured with a first exposure time and receives a second image from the image sensor captured with a second exposure time that is less than the first exposure time. A high dynamic range image is determined based on the first image and the second image, wherein an image portion of the high dynamic range image is based on a corresponding image portion of the second image when a pixel of a corresponding image portion of the first image is saturated. An output image that is based on the high dynamic range image is stored, displayed, or transmitted.

Systems and methods are disclosed for image signal processing. For example, systems may include an image sensor and a processing apparatus. The image sensor captures image data using a plurality of selectable exposure times. The processing apparatus receives a first image from the image sensor captured with a first exposure time and receives a second image from the image sensor captured with a second exposure time that is less than the first exposure time. A high dynamic range image is determined based on the first image and the second image, wherein an image portion of the high dynamic range image is based on a corresponding image portion of the second image when a pixel of a corresponding image portion of the first image is saturated. An output image that is based on the high dynamic range image is stored, displayed, or transmitted.

A method of encoding video data, the method comprising: generating prediction data of the video data; generating residual data based on the prediction data and digital sample values of the video data; generating coefficients based on the residual data; performing an interlacing process to generate an interlaced amplitude value, wherein the interlacing process interlaces bits of two or more of the coefficients to generate the interlaced amplitude value; modulating an analog signal based on the interlaced amplitude value; generating digital values based on the prediction data; and outputting the analog signal and digital values based on the prediction block.

A method for encoding video data comprises generating coefficients based on video data; generating coefficient vectors, wherein each of the coefficient vectors includes n of the coefficients; for each of the coefficient vectors, determining an amplitude value for the coefficient vector based on a mapping pattern, wherein for each respective allowed coefficient vector in a plurality of allowed coefficient vectors: the mapping pattern maps the respective allowed coefficient vector to a respective amplitude value in a plurality of amplitude values, and the respective amplitude value is adjacent in an n-dimensional space to at least one other amplitude value in the plurality of amplitude values that is adjacent to the respective amplitude value in a monotonic number line of the amplitude values; and modulating an analog signal based on the amplitude values for the coefficient vectors.

A method of encoding video data comprising: generating coefficients based on digital sample values of the video data; determining a spectral efficiency for a channel; determining a value n based on the spectral efficiency of the channel; generating coefficient vectors, wherein each of the coefficient vectors includes n of the coefficients; determining an amplitude value for a coefficient vector based on a mapping pattern, wherein for each respective allowed coefficient vector in a plurality of allowed coefficient vectors: the mapping pattern maps the respective allowed coefficient vector to a respective amplitude value in a plurality of amplitude values, and the respective amplitude value is adjacent in an n-dimensional space to at least one other amplitude value in the plurality of amplitude values that is adjacent to the respective amplitude value in a monotonic number line of the amplitude values, and modulating an analog signal based on the amplitude values.

Methods and apparatus provide cloud-based video encoding that generates encoded video data by one or more encoders in a cloud platform for a plurality of cloud encoding sessions. The methods and apparatus generate operational improvement tradeoff data in response to operational encoding metrics associated with the one or more encoders and change operational characteristics of the one or more encoders for at least one of the cloud encoding sessions based on the operational improvement tradeoff data.