Abstract: A video intermodal transcoder converts a compressed bitstream formulated according a type-1 compression scheme to a type-2 compressed bitstream formulated according to a type-2 compression scheme. The transcoder includes an augmented type-1 decoder, a transcoder kernel, and an augmented type-2 encoder. The transcoder kernel performs processes of creating motion-vector candidates and pre-computing prediction errors for each cell of a predefined image coding block and for each candidate motion vector for repetitive use in evaluating various image partitions. In an implementation where the type-1 compression scheme follows the H.264 standard and the type-2 compression scheme follows the HEVC standard, the transcoder exploits the flexibility of the coding-tree structure and other HEVC features to significantly reduce the bit rate of the compressed bit stream. The pre-computation of prediction errors significantly reduces the processing effort, hence increases the throughput of the transcoder.

Abstract: Methods and systems for parallel rate-constrained motion estimation in a video encoder are provided. Embodiments of the present invention provide a solution for the problem of the reliance upon spatial dependencies when processing parallel RCME on a frame. In order to solve this problem, embodiments of the present invention determine a list of at least two Motion Vector Predictor Candidates (MVPC), determine, in parallel for at least two of said at least two MVPCs, corresponding Motion Vector Candidates (MVC) using Rate-Constrained Motion Estimation (RCME) and determine the optimal Motion Vector (MV) among the determined MVCs based on rate distortion optimization.

Abstract: Methods and systems for parallel rate-constrained motion estimation in a video encoder are provided. Embodiments of the present invention provide a solution for the problem of the reliance upon spatial dependencies when processing parallel RCME on a frame. In order to solve this problem, embodiments of the present invention determine a list of at least two Motion Vector Predictor Candidates (MVPC), determine, in parallel for at least two of said at least two MVPCs, corresponding Motion Vector Candidates (MVC) using Rate-Constrained Motion Estimation (RCME) and determine the optimal Motion Vector (MV) among the determined MVCs based on rate distortion optimization.

Abstract: A video intermodal transcoder converts a compressed bitstream formulated according a type-1 compression scheme to a type-2 compressed bitstream formulated according to a type-2 compression scheme. The transcoder includes an augmented type-1 decoder, a transcoder kernel, and an augmented type-2 encoder. The transcoder kernel performs processes of creating motion-vector candidates and pre-computing prediction errors for each cell of a predefined image coding block and for each candidate motion vector for repetitive use in evaluating various image partitions. In an implementation where the type-1 compression scheme follows the H.264 standard and the type-2 compression scheme follows the HEVC standard, the transcoder exploits the flexibility of the coding-tree structure and other HEVC features to significantly reduce the bit rate of the compressed bit stream. The pre-computation of prediction errors significantly reduces the processing effort, hence increases the throughput of the transcoder.

Abstract: A method and system for parallel encoding of frames in a video are described, exploiting parallel processing at both frame and slice levels. One or more slices are processed in a preceding frame by one or more cores in a multi-core processor, and a slice is processed in a succeeding frame provided at least one of said one or more cores in the multi-core processor is available for processing; and the processing of a slice from said one or more slices at same physical location in the preceding input frame has been completed, the processing of frames and slices in the preceding and succeeding frames being performed at least partially in parallel. A significant speedup in comparison to the sequential encoding approach is achieved while maintaining high visual quality for the output video. A corresponding system for parallel encoding of a video is also provided.

Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.

Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.

Abstract: A method for quality-aware transcoding of an input image into an output image for display on a terminal having device file size and image size constraints are disclosed. The method extracts features of the input image including dimensions and file size of the input image, predicts a file size of the output image taking into account constraints of the terminal and extracted features, including selecting a set of feasible transcoding parameters so that a corresponding predicted file size of the output image meets the device file size constraint of the terminal, determines quality metric values of the output image, characterizing a measure of distortion of the input image introduced by the transcoding, corresponding to the feasible transcoding parameters in the set of feasible transcoding parameters, and selects those transcoding parameters from the set of feasible transcoding parameters, which yield the highest quality metric value. A corresponding system is also provided.

Abstract: A method for quality-aware transcoding of an input image into an output image for display on a terminal having device file size and image size constraints are disclosed. The method extracts features of the input image including dimensions and file size of the input image, predicts a file size of the output image taking into account constraints of the terminal and extracted features, including selecting a set of feasible transcoding parameters so that a corresponding predicted file size of the output image meets the device file size constraint of the terminal, determines quality metric values of the output image, characterizing a measure of distortion of the input image introduced by the transcoding, corresponding to the feasible transcoding parameters in the set of feasible transcoding parameters, and selects those transcoding parameters from the set of feasible transcoding parameters, which yield the highest quality metric value. A corresponding system is also provided.

Abstract: A system and method for predicting a file size of an image subject to transformation by scaling and a change of at least one quality-controlling parameter are described. The system receives the file size of the image before transformation, information about at least one quality-controlling parameter of the image before transformation, information about at least one quality-controlling parameter and a scaling factor to be applied to the image during transformation. A relative size prediction is calculated using the received quality-controlling parameters information and the scaling factor. The file size of the image after the transformation is finally calculated as a function of the file size of the image before the transformation and the calculated relative size prediction. Images are partitioned into classes of images, and for each class of images, an array of relative file size predictions, having at least two dimensions, is computed.

Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.

Abstract: A system and method for predicting a tile size of an image subject to transformation by scaling and a change about at least one quality-controlling parameter, in which an input receives the file size of the image before transformation, information about at least one quality-controlling parameter of the image before transformation, information about at least one quality- controlling parameter for application to the image during transformation, and a scaling factor for application to the image during transformation. A relative size prediction is calculated on the basis of the received quality-controlling parameters information and scaling factor. The file size of the image after transformation is finally calculated as a function of the file size of the image before transformation and the calculated relative size prediction. Images are partitioned into classes of images, and for each class of images, an array of relative file size predictions is computed, the array having at least two dimensions.

Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.

Abstract: A system and method for predicting a file size of an image subject to transformation by scaling and a change about at least one quality-controlling parameter, in which an input receives (a) the file size of the image before transformation, (b) information about at least one quality-controlling parameter of the image before transformation, (c) information about at least one quality-controlling parameter for application to the image during transformation, and (d) a scaling factor for application to the image during transformation. A relative size prediction is calculated on the basis of the received quality-controlling parameters information and scaling factor. The file size of the image after transformation is finally calculated as a function of the file size of the image before transformation and the calculated relative size prediction.

Abstract: A method and system for parallel encoding of frames in a video are described, exploiting parallel processing at both frame and slice levels. One or more slices are processed in a preceding frame by one or more cores in a multi-core processor, and a slice is processed in a succeeding frame provided at least one of said one or more cores in the multi-core processor is available for processing; and the processing of a slice from said one or more slices at same physical location in the preceding input frame has been completed, the processing of frames and slices in the preceding and succeeding frames being performed at least partially in parallel. A significant speedup in comparison to the sequential encoding approach is achieved while maintaining high visual quality for the output video. A corresponding system for parallel encoding of a video is also provided.

Abstract: A system and method for predicting a file size of an image subject to transformation by scaling and a change about at least one quality-controlling parameter, in which an input receives (a) the file size of the image before transformation, (b) information about at least one quality-controlling parameter of the image before transformation, (c) information about at least one quality-controlling parameter for application to the image during transformation, and (d) a scaling factor for application to the image during transformation. A relative size prediction is calculated on the basis of the received quality-controlling parameters information and scaling factor. The file size of the image after transformation is finally calculated as a function of the file size of the image before transformation and the calculated relative size prediction.

Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.

Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.