Image segmentation based on modified information cut in wavelet domain

To solve the mis-clusters caused by the traditional information cut algorithm when it is applied to segment images with gray changes, modified information cut in wavelet domain (W-MIC) algorithm is proposed. First, using the gray relevance and space relevance between image pixels, a modified information cut (MIC) is presented, which utilizes a new Parzen windowing function to evaluate probability density functions, and reduces the effect of gray changes to image segmentation; further, considering the difficulties of selecting the optimal parameter in MIC, the proposed W-MIC can reduce the complexity of parameter selection via the smoothing role of wavelet, and improve segmentation results by fusing low frequency information and high frequency information derived from undecimated wavelet decomposition. Segmentation experiments demonstrate that it effectively decreases the influence of parameters selection, and it can not only avoid the mis-clusters caused by gray changes, but also keep image edges.