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The original delogo algorithm interpolates both horizontally and vertically and uses the average to compute the resulting sample. This works reasonably well when the logo area is almost square. However when the logo area is significantly larger than high or higher than large, the result is largely suboptimal. The issue can be clearly seen by testing the delogo filter with a fake logo area that is 200 pixels large and 2 pixels high. Vertical interpolation gives a very good result in that case, horizontal interpolation gives a very bad result, and the overall result is poor, because both are given the same weight. Even when the logo is roughly square, the current algorithm gives poor results on the borders of the logo area, because it always gives horizontal and vertical interpolations an equal weight, and this is suboptimal on borders. For example, in the middle of the left hand side border of the logo, you want to trust the left known point much more than the right known point (which the current algorithm already does) but also much more than the top and bottom known points (which the current algorithm doesn't do.) By properly weighting each known point when computing the value of each interpolated pixel, the visual result is much better, especially on borders and/or for high or large logo areas. The algorithm I implemented guarantees that the weight of each of the 4 known points directly depends on its distance to the interpolated point. It is largely inspired from the original algorithm, the key difference being that it computes the relative weights globally instead of separating the vertical and horizontal interpolations and combining them afterward. Signed-off-by: Jean Delvare <khali@linux-fr.org> Signed-off-by: Stefano Sabatini <stefasab@gmail.com> |
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