Method and system for training a neural network with adaptive weight updating and adaptive pruning in principal components space

A method and apparatus for assessing the visibility of differences between two input image sequences. The apparatus comprises a visual discrimination measure having a retinal sampling section, a plurality of temporal filters and a spatial discrimination section. The retinal sampling section applies a plurality of transformations to the input image sequences for simulating the image-processing properties of human vision. The temporal filters separate the sequences of retinal images into two temporal channels producing a lowpass temporal response and a bandpass temporal response. The spatial discrimination section applies spatial processing to the temporal responses to produce an image metric which is used to assess the visibility of differences between the two input image sequences. Also published as: WO9737325 (A1) JP2002503360 (A) EP0898764 (A1) EP0898764 (A4) EP0898764 (B1) DE69726567 (T2

Method and apparatus for training a neural network to learn and use fidelity metric as a control mechanism

A signal processing apparatus and concomitant method for learning and using fidelity metric as a control mechanism and to process large quantities of fidelity metrics from a visual discrimination measure (VDM) to a manageable subjective image quality ratings. The signal processing apparatus incorporates a VDM and a neural network. The VDM receives input image sequences and generates fidelity metrics, which are received by a neural network. The neural network is trained to learn and use the fidelity metrics as a control mechanism, e.g., to control a video encoder

Method and apparatus for assessing the visibility of differences between two image sequences

WO9737325 (A1) ¿ 1997-10-09 Also published as: US5974159 (A) JP2002503360 (A) EP0898764 (A1) EP0898764 (A4) EP0898764 (B1) DE69726567 (T2) less A method and apparatus for assessing the visibility of differences between two input image sequences. The apparatus comprises a visual discrimination measure (112) having a retinal sampling section (330), a plurality of temporal filters (334, 335) and a spatial discrimination section (240). The retinal sampling section (330) applies a plurality of transformations to the input image sequences (310, 320) for simulating the image-processing properties of human vision. The temporal filters (334, 335) separate the sequences of retinal images into two temporal channels producing a lowpass temporal response and a bandpass temporal response. The spatial discrimination section (240) applies spatial processing to the temporal responses to produce an image metric (250) which is used to assess the visibility of differences between the two input image sequences