Automatically improving image quality using tensor voting

作者：Toan Dinh Nguyen; Park Jonghyun; Kim Soohyung; Park Hyukro; Lee Gueesang^*

来源：Neural Computing & Applications, 2011, 20(7): 1017-1026.

DOI：10.1007/s00521-010-0394-4

• Tensor voting
• Image restoration
• Text stroke enhancement
• Image repairing

A novel corrupted region detection technique based on tensor voting is proposed to automatically improve the image quality. This method is suitable for restoring degraded images and enhancing binary images. First, the input images are converted into layered images in which each layer contains objects having similar characteristics. By encoding the pixels in the layered images with second-order tensors and performing voting among them, the corrupted regions are automatically detected using the resulting tensors. These corrupted regions are then restored to improve the image quality. The experimental results obtained from automatic image restoration and binary image enhancement applications show that our method can successfully detect and correct the corrupted regions.

• 出版日期2011-10