Abstract: A method for developing an enhancement model for low-quality visual data, the method comprising the steps of receiving one or more sections of higher-quality visual data; and training a hierarchical algorithm. The hierarchical algorithm is operable to increase the quality of one or more sections of lower-quality visual data so as to substantially reproduce the one or more sections of higher-quality visual data. The hierarchical algorithm is then outputted.

Abstract: A method for increasing the quality of a section of visual data communicated over a network from a first node to a second node, the method at the second node including receiving a lower-quality visual data via a network, receiving a corresponding reference to an algorithm operable to increase a quality of the lower-quality visual data, the algorithm selected based on a higher-quality visual data from which the lower-quality visual data was generated, and using the algorithm to increase the quality of the lower-quality visual data to recreate the higher-quality visual data.

Abstract: A method for enhancing one or more sections of lower-quality visual data using a hierarchical algorithm, the method comprising receiving one or more sections of lower-quality visual data. The one or more sections of lower-quality visual data are enhanced to one or more sections of higher-quality visual data using the hierarchical algorithm. Additionally, at least the first step of the hierarchical algorithm is performed in a lower-quality domain; and wherein the hierarchical algorithm operates in both a higher-quality domain and the lower-quality domain.

Abstract: A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method including 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.

Abstract: A method for enhancing lower-quality visual data using hierarchical algorithms, the method comprising the steps of: receiving one or more sections of lower-quality visual data; applying a hierarchical algorithm to the one or more sections of lower-quality visual data to enhance the one or more sections of lower-quality visual data to one or more sections of higher-quality visual data, wherein the hierarchical algorithm was developed using a learned approach; and outputting the one or more sections of higher-quality visual data.

Abstract: A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method comprises receiving at least one section of lower-quality visual data; and extracting a subset of features, from the at least one section of lower-quality visual data. A plurality of layers of reduced-dimension visual data from the extracted features are formed and enhanced to form at least one section of higher-quality visual data. The at least one section of higher-quality visual data corresponds to the at least one section of lower-quality visual data received.

Abstract: 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.

Abstract: A method for enhancing at least a section of lower-quality visual data, the method comprising at least a section of the lower-quality visual data being received. A hierarchical algorithm is then selected from a plurality of hierarchical algorithms, wherein the step of selection is based on a predetermined metric and wherein the hierarchical algorithms were developed using a learned approach and at least one of the hierarchical algorithms is operable to increase the quality of the lower-quality visual data. The selected hierarchical algorithm is then used to increase the quality of the lower-quality visual data to create a higher-quality visual data.

Abstract: A method for training learned hierarchical algorithms, the method comprising the steps of receiving input data and generating metrics from the input data. At least one hierarchical algorithm is then selected from a plurality of predetermined hierarchical algorithms based on comparing the generated metrics from the input data and like metrics for each of the plurality of predetermined hierarchical algorithms. The selected hierarchical algorithm is developed based on the input data and the developed hierarchical algorithm is outputted.

Abstract: A method for enhancing visual data when communicating visual data over a network from a first node to a second node. The method at the first node comprises developing at least one modified hierarchical algorithm from a known hierarchical algorithm operable to substantially recreate at least one section of higher-quality visual data. References to one or more known hierarchical algorithms from which the modified hierarchical algorithms were developed are transmitted to the second node along with one or more modifications to the one or more known hierarchical algorithms operable to reproduce the one or more modified hierarchical algorithms from the known hierarchical algorithms. The second node is able to recreate substantially the higher-quality video using the modified hierarchical algorithm.

Abstract: A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method comprises receiving at least one section of lower-quality visual data; and extracting a subset of features, from the at least one section of lower-quality visual data. A plurality of layers of reduced-dimension visual data from the extracted features are formed and enhanced to form at least one section of higher-quality visual data. The at least one section of higher-quality visual data corresponds to the at least one section of lower-quality visual data received.

Abstract: A method for training learned hierarchical algorithms, the method comprising the steps of receiving input data and generating metrics from the input data. At least one hierarchical algorithm is then selected from a plurality of predetermined hierarchical algorithms based on comparing the generated metrics from the input data and like metrics for each of the plurality of predetermined hierarchical algorithms. The selected hierarchical algorithm is developed based on the input data and the developed hierarchical algorithm is outputted.

Abstract: A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method including 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.

Abstract: A method for enhancing lower-quality visual data using hierarchical algorithms, the method comprising the steps of: receiving one or more sections of lower-quality visual data; applying a hierarchical algorithm to the one or more sections of lower-quality visual data to enhance the one or more sections of lower-quality visual data to one or more sections of higher-quality visual data, wherein the hierarchical algorithm was developed using a learned approach; and outputting the one or more sections of higher-quality visual data.

Abstract: A method for enhancing at least a section of lower-quality visual data, the method comprising at least a section of the lower-quality visual data being received. A hierarchical algorithm is then selected from a plurality of hierarchical algorithms, wherein the step of selection is based on a predetermined metric and wherein the hierarchical algorithms were developed using a learned approach and at least one of the hierarchical algorithms is operable to increase the quality of the lower-quality visual data. The selected hierarchical algorithm is then used to increase the quality of the lower-quality visual data to create a higher-quality visual data.

Abstract: A method for increasing the quality of a section of visual data communicated over a network from a first node to a second node, the method at the second node including receiving a lower-quality visual data via a network, receiving a corresponding reference to an algorithm operable to increase a quality of the lower-quality visual data, the algorithm selected based on a higher-quality visual data from which the lower-quality visual data was generated, and using the algorithm to increase the quality of the lower-quality visual data to recreate the higher-quality visual data.

Abstract: A method for enhancing visual data when communicating visual data over a network from a first node to a second node. The method at the first node comprises developing at least one modified hierarchical algorithm from a known hierarchical algorithm operable to substantially recreate at least one section of higher-quality visual data. References to one or more known hierarchical algorithms from which the modified hierarchical algorithms were developed are transmitted to the second node along with one or more modifications to the one or more known hierarchical algorithms operable to reproduce the one or more modified hierarchical algorithms from the known hierarchical algorithms. The second node is able to recreate substantially the higher-quality video using the modified hierarchical algorithm.

Abstract: 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.

Abstract: A method for enhancing one or more sections of lower-quality visual data using a hierarchical algorithm, the method comprising receiving one or more sections of lower-quality visual data. The one or more sections of lower-quality visual data are enhanced to one or more sections of higher-quality visual data using the hierarchical algorithm. Additionally, at least the first step of the hierarchical algorithm is performed in a lower-quality domain; and wherein the hierarchical algorithm operates in both a higher-quality domain and the lower-quality domain.

Abstract: A method for developing an enhancement model for low-quality visual data, the method comprising the steps of receiving one or more sections of higher-quality visual data; and training a hierarchical algorithm. The hierarchical algorithm is operable to increase the quality of one or more sections of lower-quality visual data so as to substantially reproduce the one or more sections of higher-quality visual data. The hierarchical algorithm is then outputted.