### Table 2: 2{D multiscale relaxation algorithm.

1995

"... In PAGE 9: ....g., horizontal, vertical and diagonal bands. While the order in which the horizontal and vertical bands are processed appears arbitrary, the diagonal band is processed last for consistency with the multiresolution approach. The relaxation algorithm is summarized in Table2 . The inter{scale error feedback term (s;j ) j includes terms from scale j + 1 and from all bands at scale j visited prior to .... In PAGE 11: ... perceptually at domain where the unweighted criterion (4) is useful [19], as shown in Fig. 4. The pre lter P has magnitude{squared frequency response approximating W(u; v). The output z of this lter is subband coded using the algorithm in Table2 (unweighted L2 criterion) with identical quantizers in all bands. At the decoder, the post ltered image ^ y is such that ^ EW = kP(y ? ^ yk2 = kz ? ^ zk2 is minimized.... ..."

Cited by 15

### Table 2: Distribution of execution time between the tasks performed within the multiscale color ratio approach.

2001

"... In PAGE 7: ... Table 1 shows the execution times obtained, where saliency detection with our multiscale color ratio method presents lower execution time than the other approaches. Table2 shows the distribution of computing time between the most important tasks carried out by the proposed algorithm. The computation of center- surround differences is only 8% of the total execution time, because these differences are computed at the scale of the centers, instead of at the source image scale.... ..."

Cited by 1

### Table 1: Summary of multiscale models.

"... In PAGE 14: ... 4 Physical and Mathematical Submodels and their Integration We describe below specific physical and mathematical representations of key biological mechanisms operating at the various scales of our model. Table1 summarizes the mechanisms and the corresponding submodels. For each mechanism a specific parameter controls the behavior of the corresponding submodel.... In PAGE 31: ...ther sub-modules implement different cell responses, e.g., cell growth and mitosis. We used the Visualization ToolKit (VTK), available as freeware9 to develop our visualization software. 5 Discussion of Simulation Results How do parameters affect the integrated model? We start with an initial distribution of undifferentiated cells in the ECM, with a cell-volume less than the average cell volume ( Table1 ), no initial fibronectin and a small, randomly perturbed, distribution of activator and inhibitor. The combination of morphogens, cell dynamics and cell differentiation produces the roughly periodic pattern of the major chondrogenic elements in the chick limb.... ..."

### Table 1. Summary of multiscale models.

"... In PAGE 6: ... PHYSICAL AND MATHEMATICAL SUBMODELS AND THEIR INTEGRATION We describe below specific physical and mathematical representations of key biological mechanisms opera- ting at the various scales of our model. Table1 sum- marizes the mechanisms and the corresponding submodels, and their characteristic spatial and temporal scales. For each mechanism, a specific parameter controls the behaviour of the corresponding submodel.... ..."

### Table 1: Timing in seconds for our global (Equation 3) and local (Equation 9) operators. The middle rows show the timing for the approximated Gaussian convolution using a multiscale spline ap- proach [Burt and Adelson 1983].

2002

"... In PAGE 9: ... Timings obtained on a 1.8 GHz Pentium 4 PC are given in Table1 for two different image sizes. While we have not counted any disk I/O, the timings for preprocessing as well as the main tone mapping algorithm are presented.... ..."

Cited by 2

### Table 1: Timing in seconds for our global (Equation 3) and local (Equation 9) operators. The middle rows show the timing for the approximated Gaussian convolution using a multiscale spline ap- proach [Burt and Adelson 1983].

"... In PAGE 8: ... Timings obtained on a 1.8 GHz Pentium 4 PC are given in Table1 for two different image sizes. While we have not counted any disk I/O, the timings for preprocessing as well as the main tone mapping algorithm are presented.... ..."

### Table 2: Comparison of multiscale and single scale methods. First row: Quality measured in terms of (7). Second row: run{time in seconds measured on a Pentium Pro 200Mhz. The images were quantized to 16 colors.

1998

Cited by 9

### Table 4: Performance of the algorithm in presence of various sources of noise in mixtures: Normal- ized mean-squared (NSE) and cross-talk (CTE) errors for image separation, applying our multiscale adaptive approach along with the Natural Gradient based separation.

2003

"... In PAGE 20: ... Therefore, at sufficiently high signal-to-noise energy ratios (SNR), the large coefficients of the signals are only slightly distorted by the noise coefficients. As a result, the presence of noise has a minor effect on the estimation of the unmixing matrix (see the CTE entries in Table4 ). Note, that the NSE entries reflect the noise energy passed to the reconstructed sources from the mixtures.... ..."

Cited by 4

### Table 4: Performance of the algorithm in presence of various sources of noise in mixtures: Normal- ized mean-squared (NSE) and cross-talk (CTE) errors for image separation, applying our multiscale adaptive approach along with the Natural Gradient based separation.

2003

"... In PAGE 20: ... Therefore, at sufficiently high signal-to-noise energy ratios (SNR), the large coefficients of the signals are only slightly distorted by the noise coefficients. As a result, the presence of noise has a minor effect on the estimation of the unmixing matrix (see the CTE entries in Table4 ). Note, that the NSE entries reflect the noise energy passed to the reconstructed sources from the mixtures.... ..."

Cited by 4