Title :
High Resolution Local Structure-Constrained Image Upsampling
Author :
Yang Zhao ; Ronggang Wang ; Wenmin Wang ; Wen Gao
Author_Institution :
Shenzhen Grad. Sch., Sch. of Electron. & Comput. Eng., Peking Univ., Shenzhen, China
Abstract :
With the development of ultra-high-resolution display devices, the visual perception of fine texture details is becoming more and more important. A method of high-quality image upsampling with a low cost is greatly needed. In this paper, we propose a fast and efficient image upsampling method that makes use of high-resolution local structure constraints. The average local difference is used to divide a bicubic-interpolated image into a sharp edge area and a texture area, and these two areas are reconstructed separately with specific constraints. For reconstruction of the sharp edge area, a high-resolution gradient map is estimated as an extra constraint for the recovery of sharp and natural edges; for the reconstruction of the texture area, a high-resolution local texture structure map is estimated as an extra constraint to recover fine texture details. These two reconstructed areas are then combined to obtain the final high-resolution image. The experimental results demonstrated that the proposed method recovered finer pixel-level texture details and obtained top-level objective performance with a low time cost compared with state-of-the-art methods.
Keywords :
image resolution; image sampling; image texture; average local difference; bicubic-interpolated image; fine texture details; high resolution local structure-constrained image upsampling; high-resolution gradient map; pixel-level texture details; sharp edge area; texture area; Dictionaries; Estimation; Image edge detection; Image reconstruction; Image resolution; Interpolation; Morphology; Image upsampling; gradient morphology; image upsampling; image upscaling; local binary pattern; super-resolution; superresolution;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2015.2456416