Robust image metamorphosis immune from ghost and blur

In this paper, we propose a novel method for the metamorphosis between two different images. By the approach, the transition sequence is generated by stitching two forward and backward warped sequences in a three-dimensional space along transition surface. In contrast to the traditional methods by blending two warped images at each intermediate frame, we continuously warp images on opposite direction without blending until the two warped images match in a three-dimensional space leading to a better transition in quality. Furthermore, for each pixel, we make decision of choosing a given input image best suitable so as to produce plausible in-between images to prevent from ghost and blur. By our scheme, the transition surface is computed by minimizing an energy function in terms of graph-cut optimization. Depending on the transition surface, a warp function is proposed to create a smooth and clear transformation. We demonstrate the advantage of our framework by performing transformation test to various kinds of image couples. © 2012 Springer-Verlag.In this paper, we propose a novel method for the metamorphosis between two different images. By the approach, the transition sequence is generated by stitching two forward and backward warped sequences in a three-dimensional space along transition surface. In contrast to the traditional methods by blending two warped images at each intermediate frame, we continuously warp images on opposite direction without blending until the two warped images match in a three-dimensional space leading to a better transition in quality. Furthermore, for each pixel, we make decision of choosing a given input image best suitable so as to produce plausible in-between images to prevent from ghost and blur. By our scheme, the transition surface is computed by minimizing an energy function in terms of graph-cut optimization. Depending on the transition surface, a warp function is proposed to create a smooth and clear transformation. We demonstrate the advantage of our framework by performing transformation test to various kinds of image couples. © 2012 Springer-Verlag