  This paper presents a histogram based reversible data hiding (RDH) scheme,
which divides image pixels into different cell frequency bands to sort them for
data embedding. Data hiding is more efficient in lower cell frequency bands
because it provides more accurate prediction. Using pixel existence probability
in some pixels of ultra-low cell frequency band, another sorting is performed.
Employing these two novel sorting methods in combination with the hiding
intensity analysis that determines optimum prediction error, we improve the
quality of the marked image especially for low embedding capacities. In effect,
comparing to existent RDH algorithms, the hiding capacity is increased for a
specific level of the distortion for the marked image. Experimental results
confirm that the proposed algorithm outperforms state of the art ones.
