A system and a method for compressing an image based on a FLASH in-memory computing array are provided. The system includes: a convolutional neural network for encoding of the FLASH in-memory computing array, a convolutional neural network for decoding based on the FLASH in-memory computing array, and a quantization module; the convolutional neural network for encoding based on the FLASH in-memory computing array is configured to encode an original image to obtain a feature image; the quantization module is configured to quantize the feature image to obtain a quantized image; the convolutional neural network for decoding based on the FLASH in-memory computing array is configured to decode the quantized image to obtain a compressed image.

A system and a method for compressing an image based on a FLASH in-memory computing array are provided. The system includes: a convolutional neural network for encoding of the FLASH in-memory computing array, a convolutional neural network for decoding based on the FLASH in-memory computing array, and a quantization module; the convolutional neural network for encoding based on the FLASH in-memory computing array is configured to encode an original image to obtain a feature image; the quantization module is configured to quantize the feature image to obtain a quantized image; the convolutional neural network for decoding based on the FLASH in-memory computing array is configured to decode the quantized image to obtain a compressed image.

A Scalable Video Coding (SVC) process is provided for scalable video coding that takes into account color gamut primaries along with spatial resolution. The process provides for re-sampling using video color data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to enable improved encoding and decoding in an enhancement layer (EL) or higher layers taking into account color conversion between layers. Examples of applicable SVC include MPEG-4 Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC). With the SVC process, video data expressed in one color gamut space can be used for prediction in encoding with a possibly different color space, and accommodation for different spatial resolution and bit-depth can be made as well.

A Scalable Video Coding (SVC) process is provided for scalable video coding that takes into account color gamut primaries along with spatial resolution. The process provides for re-sampling using video color data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to enable improved encoding and decoding in an enhancement layer (EL) or higher layers taking into account color conversion between layers. Examples of applicable SVC include MPEG-4 Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC). With the SVC process, video data expressed in one color gamut space can be used for prediction in encoding with a possibly different color space, and accommodation for different spatial resolution and bit-depth can be made as well.

A Scalable Video Coding (SVC) process is provided for scalable video coding that takes into account color gamut primaries along with spatial resolution. The process provides for re-sampling using video color data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to enable improved encoding and decoding in an enhancement layer (EL) or higher layers taking into account color conversion between layers. Examples of applicable SVC include MPEG-4 Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC). With the SVC process, video data expressed in one color gamut space can be used for prediction in encoding with a possibly different color space, and accommodation for different spatial resolution and bit-depth can be made as well.

A Scalable Video Coding (SVC) process is provided for scalable video coding that takes into account color gamut primaries along with spatial resolution. The process provides for re-sampling using video color data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to enable improved encoding and decoding in an enhancement layer (EL) or higher layers taking into account color conversion between layers. Examples of applicable SVC include MPEG-4 Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC). With the SVC process, video data expressed in one color gamut space can be used for prediction in encoding with a possibly different color space, and accommodation for different spatial resolution and bit-depth can be made as well.

The Cloud-based Video Streaming Service (CVSS) architecture is disclosed to transcode video streams in an on-demand manner. The architecture provides a platform for streaming service providers to utilize cloud resources in a cost-efficient manner and with respect to the Quality of Service (QoS) demands of video streams. In particular, the architecture includes a QoS-aware scheduling method to efficiently map video streams to cloud resources, and a cost-aware dynamic (i.e., elastic) resource provisioning policy that adapts the resource acquisition with respect to the video streaming QoS demands. Simulation results based on realistic cloud traces and with various workload conditions, demonstrate that the CVSS architecture can satisfy video streaming QoS demands and reduces the incurred cost of stream providers up to 70%.

The Cloud-based Video Streaming Service (CVSS) architecture is disclosed to transcode video streams in an on-demand manner. The architecture provides a platform for streaming service providers to utilize cloud resources in a cost-efficient manner and with respect to the Quality of Service (QoS) demands of video streams. In particular, the architecture includes a QoS-aware scheduling method to efficiently map video streams to cloud resources, and a cost-aware dynamic (i.e., elastic) resource provisioning policy that adapts the resource acquisition with respect to the video streaming QoS demands. Simulation results based on realistic cloud traces and with various workload conditions, demonstrate that the CVSS architecture can satisfy video streaming QoS demands and reduces the incurred cost of stream providers up to 70%.

A method of decoding an enhanced video stream composed of base layer video access units and enhancement layer video access units, each access unit comprising a plurality of syntax structures, includes passing the syntax structures of the base layer access units to a base layer buffer, passing syntax structures of the enhancement layer access units to an enhancement layer buffer, outputting the syntax structures passed to the base layer buffer in a predetermined sequence, outputting the syntax structures passed to the enhancement layer buffer in a predetermined sequence, and recombining the sequences of syntax structures output by the base layer buffer and the enhancement layer buffer respectively to form a complete enhanced access unit, composed of base layer syntax structures and enhancement layer syntax structures in a predetermined sequence.

A method of decoding an enhanced video stream composed of base layer video access units and enhancement layer video access units, each access unit comprising a plurality of syntax structures, includes passing the syntax structures of the base layer access units to a base layer buffer, passing syntax structures of the enhancement layer access units to an enhancement layer buffer, outputting the syntax structures passed to the base layer buffer in a predetermined sequence, outputting the syntax structures passed to the enhancement layer buffer in a predetermined sequence, and recombining the sequences of syntax structures output by the base layer buffer and the enhancement layer buffer respectively to form a complete enhanced access unit, composed of base layer syntax structures and enhancement layer syntax structures in a predetermined sequence.