Sentence examples for mean pixel values from inspiring English sources

NDVI and VOD perform better than dB in characterizing land cover variation based on mean pixel values; while dB represents more reliable and robust vegetation sensitivity to precipitation.

In this study, we estimate land cover fraction at a satellite pixel scale by employing an existing 'Mean-Sensitivity Unmixing Algorithm' (MSUA), which is based on a state space defined by two key variables: (1) mean pixel values (referring to mean vegetation states), and (2) inter-annual sensitivity of pixel values to precipitation (referring to vegetation sensitivity to precipitation).

There was a moderate negative correlation (r2 = 0.12, P < 0.05; Pearson's Product Moment and r2 = 0.23, P < 0.05; ANCOVA) between mean pixel heterogeneity (standard deviation of mean pixel values) of the follicular wall proper (all follicles ≥5 mm in diameter) and serum concentrations of oestradiol after sponge withdrawal.

We estimated the mean for the county by adjusting the mean pixel values to compensate for estimated deviation resulting from systematic model prediction error.

The uncorrected and corrected mean pixel values were extracted for each VOI and SUVmean were computed as follows, assuming a 1 g/mL density: mathrm{S}mathrm{U}mathrm{V}=frac{mathrm{tumor} mathrm{activity}kern0.5em left(frac{mathrm{Bq}}{mathrm{mL}}right) times mathrm{body} mathrm{weight}kern0.5em left(mathrm{g}right)}{mathrm{injected} mathrm{dose} left(mathrm{Bq}right)}.

Fetch window b s, d from b s with size (w, h) around (x + d, y); Compute ZSAD cost c x, y, d) between b r and b s, d : c ( x, y, d ) = ∑ ( x, y ) | b r ( x, y ) - b ̄ r - b s, d ( x, y ) + b ̄ s, d | where b ̄ r and b ̄ s, d denote the mean pixel values.

At first, all suspicious MCs are preserved by thresholding a filtered mammogram via a wavelet filter according to the MPV (mean pixel value) of that image.

The RGB image, with pixel values ranging between 0 and 255, is normalized by subtracting the mean pixel value.

Regions that exceed the image boundaries are padded with the mean pixel value of the RGB training dataset.

The SNR is defined as the ratio of the mean pixel value (mean) to the standard deviation (SD) in the observed region: SNR = Mean SD. (1).

For each ROI, the image coefficient of variation (COV) was determined by dividing the standard deviation to the mean pixel value within this ROI.