Abstract: A method of quantifying perceptual information and entropy for a data input signal uses an appropriate perceptual model to produce a perceptual response. The perceptual response is then entropy converted to produce the perceptual information and entropy. The entropy conversion may include the application of a transform function, such as a Karhunen-Loeve transform function, to the perceptual response to produce a set of coefficients, which coefficients then have probabilities calculated for them based on coefficient histograms of massive tests. The probabilities are used to calculate the perceptual information and entropy using standard techniques. The perceptual information and entropy may be used in applications for achieving greater accuracy subjective quality determinations for the data input signal.

Abstract: An apparatus and method for predicting human vision perception and perceptual differences provides a perceptual difference model that merges two human vision systems, one for a reference video signal and the other for an impaired version of the reference video signal. The respective video signals are processed by spatio-temporal filters and, prior to differencing, by noise masking modules that apply a noise mask as a function of pupil size and luminance. The differenced filtered signal is an initial perceptual difference map to which other masking is applied to take into account correlation and contrast gain based upon the noise masks and filtered luminance from the spatio-temporal filters. The result is a more precise output perceptual difference map.

Abstract: A variable sample rate recursive digital filter is an adaptive digital filter where its coefficients are recalculated for each sample rate being processed in such a way as to maintain a constant frequency rate for all sample rates. An equivalent resampling is done by taking the ratio of the bilinear transforms at the respective sample rates. From an initial or calibrated sample rate and a corresponding initial filter coefficient, a new filter coefficient for a new sample rate is obtained by multiplying the initial filter coefficient by a constant or coefficient factor that is a function of the initial filter coefficient and a ratio of the initial and new sample rates: zFactor(z,R):=(1/z){(z(1+R)+(1?R))/(z(1?R)+(1+R))} The resulting new filter coefficient provides the adaptive digital filter with a constant frequency response when compared to the initial sample rate frequency response.

Abstract: A method of measuring frequencies of multiple sinusoidal bursts in a signal uses a time-domain window that includes all the bursts which are then transformed to the frequency by domain an FFT. The magnitudes of the frequency bins are filtered and smoothed to create a minimum magnitude threshold array. An adaptive threshold is calculated from the minimum magnitude threshold array, maximum magnitudes of the frequency bins and an adjustable constant. The magnitudes are then compared to the adaptive threshold and the number of consecutive frequency bins above the adaptive threshold are counted and, if correct for the given signal, a centroid is determined for each frequency bin. If the number of bursts is not correct, then the adjustable constant is altered and the adaptive threshold recalculated. The centroids are converted to measured frequencies for the multiple sinusoidal bursts.

Abstract: Locating of points of interest in an impaired image derived from video processing of a reference image is achieved by generating an impairment map for the impaired image. Then a cross-fade is performed between the impaired image and the impairment map so that points of interest indicated by the impairment map are accurately located on the impaired image.

Abstract: Temporal processing for realtime human vision system behavioral modeling is added at the input of a spatial realtime human vision system behavioral modeling algorithm. The temporal processing includes a linear and a non-linear temporal filter in series in each of a reference channel and a test channel, the input to the reference channel being a reference image signal and the input to the test channel being a test image signal that is an impaired version of the reference image signal. The non-linear temporal filter emulates a process with neural attack and decay to compensate for a shift in peak sensitivity and for frequency doubling in a spatio-temporal sensitivity function. The linear temporal filter accounts for the remaining subtleties in the spatio-temporal sensitivity function.

Abstract: An adaptive spatio-temporal filter for use in video quality of service instruments based on human vision system models has a pair of parallel, lowpass, spatio-temporal filters receiving a common video input signal. The outputs from the pair of lowpass spatio-temporal filters are differenced to produce the output of the adaptive spatio-temporal filter, with the bandwidths of the pair being such as to produce an overall bandpass response. A filter adaptation controller generates adaptive filter coefficients for each pixel processed based on a perceptual parameter, such as the local average luminance, contrast, etc., of either the input video signal or the output of one of the pair of lowpass spatio-temporal filters. Each of the pair of lowpass spatio-temporal filters has a temporal IIR filter in cascade with a 2-D spatial IIR filter, and each individual filter is composed of a common building block,5 i.e., a first order, unity DC gain, tunable lowpass filter having a topology suitable for IC implementation.

Abstract: A method of interpolating data for a waveform or vector display provides a variable interpolation rate based upon a distance between consecutive samples of input data. The distance is used to access a coefficient look-up table from among a plurality of coefficient look-up tables, the number of look-up tables being a function of the number of interpolation rates desired. The distance is also used to control a clock for reading out the coefficients from the coefficient look-up table. The distance is variable between consecutive samples. A finite impulse response (FIR) filter receives the coefficients from the coefficient look-up table and provides interpolated data between each set of consecutive samples. The distance may also be used to control the intensity of an electronic beam for a display device upon which the interpolated data is displayed.

Abstract: A method of predicting subjective quality ratings of processed video from corresponding human vision model perceptual difference scores obtains perceptual difference scores for a “Worst” quality video training sequence and for a “Best” quality video training sequence. Corresponding subjective quality rating values are assigned to the perceptual difference scores as modified by any single-ended measures of impairments that may exist in the reference video training sequences from which the “Worst” and “Best” quality video training sequences are derived.

Abstract: Subjectively weighting noise measurements for multiple video formats based upon a defined standard for a standard definition video format uses a ratio between the active line time for the standard definition video format and the active line time for another video format to be measured in order to rescale a unified weighting filter for the standard definition video format for the another video format.

Abstract: A method of measuring frequencies of multiple sinusoidal bursts in a signal uses a time-domain window that includes all the bursts which are then transformed to the frequency-domain by an FFT. The magnitudes of the frequency bins are filtered and smoothed to create a minimum magnitude threshold array. An adaptive threshold is calculated from the minimum magnitude threshold array, maximum magnitudes of the frequency bins and an adjustable constant. The magnitudes are then compared to the adaptive threshold and the number of consecutive frequency bins above the adaptive threshold are counted and, if correct for the given signal, a centroid is determined for each frequency bin. If the number of bursts is not correct, then the adjustable constant is altered and the adaptive threshold recalculated. The centroids are converted to measured frequencies for the multiple sinusoidal bursts. The fundamental burst frequencies are measured even in the presence of burst side-lobes, non-linear distortions and noise.

Abstract: A method of automatically setting gain and offset for a signal is achieved by defining a region of interest within the signal, such as a portion of a video line, and acquiring the signal. Max and min values for the region of interest are determined and tested against respective clipping levels. If either value clips, then the gain and offset are adjusted. Alternatively if only one value clips, then only the offset is adjusted, while if both values clip then the gain is adjusted until only one value clips. The adjustments of the gain and offset continue until a maximum number of attempts is reached or neither max/min value is clipped. The resulting display of the signal shows the region of interest of the signal making optimum use of the display area.

Abstract: A method of frequency response measurement for a sinusoidal test signal, such as a swept sinusoid signal, a multi-burst sinusoidal signal or the like, uses a complex sinusoid window at a particular frequency for correlation with the sinusoidal test signal. The resulting complex correlation magnitude signal is thresholded as a function of a percentage of a maximum complex correlation magnitude. A centroid of the thresholded complex correlation magnitude signal is found, and the complex correlation magnitude at the centroid is the frequency response at the particular frequency.

Abstract: An efficient predictor for subjective video quality rating measures processes a reference video and an impaired video corresponding to the reference video in respective processing channels. Each channel applies a contrast sensitivity function from a human vision system model to the respective videos and a contrast discrimination function for self-masking to the output of the contrast sensitivity function. The outputs from the channels are input to a differencing circuit to obtain absolute difference values. The absolute difference values are modified by a global masking factor derived from the output from the reference video channel, and the resulting values are converted into units conforming to a standard quality rating metric.

Abstract: A method of realtime human vision system modeling to produce a measure of impairment of a test image signal derived from a reference image signal processes the two signals in respective channels. The signals are converted to luminance image signals and low-pass filtered in two dimensions. The processed image signals are then segmented and block means values are obtained which are subtracted from the pixels in the corresponding processed image signals. Noise is injected into the segmented processed image signals and a variance is calculated for the reference segmented processed image signal and also for the difference between the segmented processed image signals. The variance of difference segmented processed image signal is normalized by the variance for the reference segmented processed image signal, and the Nth root of the result is taken as the measure of visible impairment of the test image signal. The measure of visible impairment may be converted into appropriate units, such as JND, MOS, etc.

Abstract: Locating of points of interest in an impaired image derived from video processing of a reference image is achieved by generating an impairment map for the impaired image. Then a cross-fade is performed between the impaired image and the impairment map so that points of interest indicated by the impairment map are accurately located on the impaired image.

Abstract: A method of measuring peak signal to noise ratio (PSNR) of full color video, both total and component contributions as well as providing PSNR full color and component maps includes converting the components of the full color video for both reference and impaired video signals to GBR values, and computing the error energy for each of the G, B and R channels between the reference and impaired video signals. Each component contribution to the error for the full color video components is assessed by setting the other components to a reference value, such as zero. Also the total full color PSNR is computed in GBR. Finally a color residual PSNR map is generated and displayed together with the computed PSNR results to enable a user to visualize where the significant impairments occur in the impaired video.

Abstract: A picture quality diagnostics apparatus and method generates a human vision model response based on a human vision model for a test input video signal. Also objective measure maps for different impairment types are generated from the test input video signal. The objective measure maps are applied as masks to the human vision model response to produce objectively filtered subjective maps. The objectively filtered subjective maps are analyzed to give the respective proportions of the different objective impairment types contributing to perceptual impairment or difference for the test input video signal.

Abstract: A method of quantifying perceptual information and entropy for a data input signal uses an appropriate perceptual model to produce a perceptual response. The perceptual response is then entropy converted to produce the perceptual information and entropy. The entropy conversion may include the application of a transform function, such as a Karhunen-Loeve transform function, to the perceptual response to produce a set of coefficients, which coefficients then have probabilities calculated for them based on coefficient histograms of massive tests. The probabilities are used to calculate the perceptual information and entropy using standard techniques. The perceptual information and entropy may be used in applications for achieving greater accuracy subjective quality determinations for the data input signal.

Abstract: An apparatus and method for predicting human vision perception and perceptual differences provides a perceptual difference model that merges two human vision systems, one for a reference video signal and the other for an impaired version of the reference video signal. The respective video signals are processed by spatio-temporal filters and, prior to differencing, by noise masking modules that apply a noise mask as a function of pupil size and luminance. The differenced filtered signal is an initial perceptual difference map to which other masking is applied to take into account correlation and contrast gain based upon the noise masks and filtered luminance from the spatio-temporal filters. The result is a more precise output perceptual difference map.