Figure 2
From: Efficient robust image interpolation and surface properties using polynomial texture mapping
Comparison of outlier detection with LMS and with mode-finding approach. (a) One original image; consider pixel at yellow ‘x’. (b) Outlier detection with 6D to 1D LMS regression. Here, the pixels are displayed in ascending order sorted by luminance. The approximated values are shown as blue circles. Inlier pixel values (at this 1 pixel, over the set of 50 lights) with estimated values that fall within the green inlier band are displayed as black dots and outlier measured luminances, including values with negative luminance estimates that fall below the horizontal line at L=0, as black dots with red crosses. The blue dashed lines indicate the boundaries of the inlier band automatically identified by LMS. (c) Outlier detection with luminance-mode finder. Here the blue solid line shows the location of the (scalar) mode, bracketed by a horizontal inlier band; inliers also exclude negative- lights. (d) Red vs. green chromaticity, with outliers for green mode showing red circles (see Section 4.3).