Guided Linear Upsampling
Shuangbing Song Fan Zhong Tianju Wang Xueying Qin Changhe Tu
Guided upsampling is an effective approach for accelerating high-resolution
image processing. In this paper, we propose a simple yet effective guided
upsampling method. Each pixel in the high-resolution image is represented as a
linear interpolation of two low-resolution pixels, whose indices and weights
are optimized to minimize the upsampling error. The downsampling can be jointly
optimized in order to prevent missing small isolated regions. Our method can be
derived from the color line model and local color transformations. Compared to
previous methods, our method can better preserve detail effects while
suppressing artifacts such as bleeding and blurring. It is efficient, easy to
implement, and free of sensitive parameters. We evaluate the proposed method
with a wide range of image operators, and show its advantages through
quantitative and qualitative analysis. We demonstrate the advantages of our
method for both interactive image editing and real-time high-resolution video
processing. In particular, for interactive editing, the joint optimization can
be precomputed, thus allowing for instant feedback without hardware
acceleration.