  Probability distribution modeling is the basis for most competitive methods
for lossless coding of screen content. One such state-of-the-art method is
known as soft context formation (SCF). For each pixel to be encoded, a
probability distribution is estimated based on the neighboring pattern and the
occurrence of that pattern in the already encoded image. Using an arithmetic
coder, the pixel color can thus be encoded very efficiently, provided that the
current color has been observed before in association with a similar pattern.
If this is not the case, the color is instead encoded using a color palette or,
if it is still unknown, via residual coding. Both palette-based coding and
residual coding have significantly worse compression efficiency than coding
based on soft context formation. In this paper, the residual coding stage is
improved by adaptively trimming the probability distributions for the residual
error. Furthermore, an enhanced probability modeling for indicating a new color
depending on the occurrence of new colors in the neighborhood is proposed.
These modifications result in a bitrate reduction of up to 2.9% on average.
Compared to HEVC (HM-16.21 + SCM-8.8) and FLIF, the improved SCF method saves
on average about 11% and 18% rate, respectively.
