An efficient graph reduction framework for interactive texture segmentation
作者：
Highlights：
• A block based graph reduction framework for texture aware image segmentation is proposed.
• Texture features are extracted using non-decimated complex wavelet transform.
• Pixel level accuracy is preserved at the boundary by specially treating the pixels in boundary blocks.
• Superiority of the approach in segmenting both gray and color texture images is demonstrated.
• Significant reduction in computational time and storage is achieved.
摘要
•A block based graph reduction framework for texture aware image segmentation is proposed.•Texture features are extracted using non-decimated complex wavelet transform.•Pixel level accuracy is preserved at the boundary by specially treating the pixels in boundary blocks.•Superiority of the approach in segmenting both gray and color texture images is demonstrated.•Significant reduction in computational time and storage is achieved.
论文关键词：Graph cuts,Graph reduction,Non-decimated Complex Wavelet Transform,Texture descriptor,Object segmentation
论文评审过程：Received 4 October 2018, Revised 25 January 2019, Accepted 27 January 2019, Available online 1 February 2019, Version of Record 8 February 2019.
论文官网地址：https://doi.org/10.1016/j.image.2019.01.010
