An improved image re-indexing technique by self organizing motor maps

The paper presents a novel Motor Map neural network for re-indexing color mapped images. The overall learning process is able to smooth the local spatial redundancy of the indexes of the input image. Differently than before, the proposed optimization process is specifically devoted to re-organize the matrix of differences of the indexes computed according to some predefined patterns. Experimental results show that the proposed approach achieves good performances both in terms of compression ratio and zero order entropy of local differences. Also its computational complexity is competitive with previous works in the field.