摘要:
An adaptive filter is applied (160) to samples in an initial pattern of samples. The samples in the initial pattern correspond to a subset of the image pixels which are to be predicted using the samples. A level value of each sample in the pattern is varied (165). The level value corresponds to the intensity/signal value of the sample, and may have a strong effect on the prediction power of the samples. A first prediction pattern (i.e., the prediction signal corresponding to the sampling pattern) is generated from the samples. A sample movement process is performed (170) on a current sample in the first prediction pattern to change a current position of the current sample in the first prediction pattern. A local prediction of pixels influenced by the sample is updated if the sample's position is changed. A sample removal process is performed (175) on the current sample to remove the sample from the first pattern if a criteria is satisfied. A local prediction of pixels is updated if the current sample is removed. A second prediction pattern (i.e., the prediction signal corresponding to the new/second sampling pattern) is generated from the samples remaining in the first pattern. The second pattern is output.
摘要:
An initial decimation filter is applied to an original frame to generate a decimated frame. An optimized prediction filter is extracted from both the decimated frame and the original frame, while the initial decimation filter is held fixed. A predicted from is generated from the optimized prediction filter and the decimated frame, and an optimize decimation filter is extracted from the decimated frame and the predicted frame, while the optimized prediction filter remains fixed.
摘要:
An adaptive filter is applied (160) to samples in an initial pattern of samples. The samples in the initial pattern correspond to a subset of the image pixels which are to be predicted using the samples. A level value of each sample in the pattern is varied (165). The level value corresponds to the intensity/signal value of the sample, and may have a strong effect on the prediction power of the samples. A first prediction pattern (i.e., the prediction signal corresponding to the sampling pattern) is generated from the samples. A sample movement process is performed (170) on a current sample in the first prediction pattern to change a current position of the current sample in the first prediction pattern. A local prediction of pixels influenced by the sample is updated if the sample's position is changed. A sample removal process is performed (175) on the current sample to remove the sample from the first pattern if a criteria is satisfied. A local prediction of pixels is updated if the current sample is removed. A second prediction pattern (i.e., the prediction signal corresponding to the new/second sampling pattern) is generated from the samples remaining in the first pattern. The second pattern is output.
摘要:
Multi-field taps are defined based on a decimated field. The multi-field taps are used to generate correlation matrices, the elements of which are used to generate covariance matrices. A principal component space is obtained by projecting the correlation matrix elements on to eigenvectors. The principal component space is partitioned into classes and a least square filter set is generated for each class.
摘要:
Multi-field taps are defined based on a decimated field. The multi-field taps are used to generate correlation matrices, the elements of which are used to generate covariance matrices. A principal component space is obtained by projecting the correlation matrix elements on to eigenvectors. The principal component space is partitioned into classes and a least square filter set is generated for each class.