Microsoft Technology Licensing, LLC

Shir Aharon

Lihua Zhu

B Anil Kumar

Jeroen E Van Eesteren

Sridhar Sankuratri

Costin Hagiu

Yongjun Wu

Shyam Sadhwani

Olof L E Mases

Guosheng Sun

Winston M Johnston

Eric Rall

Olof LE Mases

Innovations in motion estimation adapted for screen remoting scenarios are described. For example, a video encoder calculates a hash value for a current block in a current picture. The video encoder searches, subject to a spatial constraint, for a matching block in a reference picture (e.g., the previous picture in display order) based at least in part on the hash value for the current block. The spatial constraint defines a search area in the reference picture within which hash values for candidate blocks in the reference picture may be compared to the hash value for the current block. By using a spatial constraint to limit the range of the local hash-based motion estimation, the video encoder can speed up the motion estimation process while still considering the candidate blocks in the reference picture that are most likely to match the current block.

Local hash-based motion estimation for screen remoting scenarios

A GPU loads point sprites that represent coded blocks of transform coefficients of one or more frames encoded in a bitstream and loads a transform kernel as a transform kernel texture. The GPU constructs an output frame using an inverse transform on the coded blocks of transform coefficients by transforming the point sprites with the transform kernel texture and by optionally dequantizing the point sprites. A single render pass may be used in which the rasterization formula performs the inverse transform and optionally dequantization. To preserve bandwidth, a CPU may refrain from sending the GPU at least some zero valued transform coefficients for the point sprites. Also, to reduce processing, the transform coefficients can remain in a zig-zag arrangement. The transform kernel texture used in the decoding can correspond to a modified version of the basis matrices used to encode the frame, which compensates for the zig-zag arrangement.

Video decoding using point sprites

Variations of rho-domain rate control for video encoding or other media encoding are presented. For example, in some of the variations, an encoder sets a rho value for a unit of media based at least in part on a bit allocation for the unit. The encoder also computes transform coefficients for the unit using a frequency transform having multiple location-dependent scale factors, sets a value of quantization parameter ('QP') for the unit using a mapping of QP values to rho values, and uses the value of QP for the unit during quantization of the transform coefficients of the unit. When the QP-rho mapping is determined, a location-independent scale factor that approximates the multiple location-dependent scale factors is used and/or certain scaling operations are integrated, which reduces computational complexity while still supporting accurate rate control decisions. Implementations of such variations of rate control can exploit opportunities for caching and parallel computation.

Variations of rho-domain rate control

Innovations in encoding of video pictures in a high-resolution chroma sampling format (such as YUV 4:4:4) using a video encoder operating on coded pictures in a low-resolution chroma sampling format (such as YUV 4:2:0) are presented. For example, according to a set of decision rules, high chroma resolution details are selectively encoded on a region-by-region basis such that increases in bit rate (due to encoding of sample values for the high chroma resolution details) happen when and where corresponding increases in chroma resolution are likely to improve quality in noticeable ways. In this way, available encoders operating on coded pictures in the low-resolution chroma sampling format can be effectively used to provide high chroma resolution details.

Dynamically updating quality to higher chroma sampling rate

Techniques are described for performing multi-stage image classification. For example, multi-stage image classification can comprise a first classification stage and a second classification stage. The first classification stage can determine an overall classification for an input image (e.g., based on a relative entropy result calculated for the input image). The second classification stage can be performed by dividing the image into a plurality of blocks and classifying individual blocks, or groups of blocks, based on a classification model that is specific to the overall classification of the image determined in the first classification stage.

Multi-stage image classification

Innovations are provided for encoding and/or decoding video and/or image content using transform coefficient level gradual updating. Transform coefficient level gradual updating can be applied by encoding (or decoding) different subsets of the transform coefficients for the blocks, macroblocks, or other coding unit for each of a sequence of pictures. For example, a first subset of the transform coefficients of the blocks of a first picture can be encoded with the first picture, a second subset of the transform coefficients of the blocks of a second picture can be encoded with the second picture, and so on. A decoder can reconstruct pictures with increasing quality by receiving additional subsets of the transform coefficients.

Gradual updating using transform coefficients for encoding and decoding

Innovations in encoding and decoding of video pictures in a high-resolution chroma sampling format (such as YUV 4:4:4) using a video encoder and decoder operating on coded pictures in a low-resolution chroma sampling format (such as YUV 4:2:0) are presented. For example, high chroma resolution details are selectively encoded on a region-by-region basis. Or, as another example, coded pictures that contain sample values for low chroma resolution versions of input pictures and coded pictures that contain sample values for high chroma resolution details of the input pictures are encoded as separate sub-sequences of a single sequence of coded pictures, which can facilitate effective motion compensation. In this way, available encoders and decoders operating on coded pictures in the low-resolution chroma sampling format can be effectively used to provide high chroma resolution details.

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Shir Aharon