A New Seam Carving Method for Image Resizing Based on Entropy Energy and Lyapunov Exponent

One of the most popular techniques in the field of image retargeting or content-aware resizing a digital image is the seam-carving technique. The performance of image resizing algorithms based on seam-carving indicates that these algorithms are highly dependent on the extraction of importance map techniques. So far, various algorithms have been proposed to extract the importance map. In this paper, a new method based on information entropy is proposed to extract of importance map. Also, a new method for selecting the most optimal seam based on the calculation of the Lyapunov exponents is presented. In simulating the proposed method, two datasets MSRA and RetargetMe have been used, which use two statistical opinions criteria and aspect ratio similarity (ARS) to evaluate the performance of the proposed method. Simulation results based on dynamical systems analysis showed that the proposed algorithm performs better than the classical seam-carving and generalized seam-carving algorithms.