|
|
|
|
|
|
|
| |
|
Abstract
We propose a perceptually based method for downscaling images that
provides a better apparent depiction of the input image. We formulate
image downscaling as an optimization problem where the difference
between the input and output images is measured using a widely adopted
perceptual image quality metric. The downscaled images retain
perceptually important features and details, resulting in an accurate
and spatio-temporally consistent representation of the high resolution
input. We derive the solution of the optimization problem in
closed-form, which leads to a simple, efficient and parallelizable
implementation with sums and convolutions. The algorithm has running
times similar to linear filtering and is orders of magnitude faster
than the state-of-the-art for image downscaling. We validate the
effectiveness of the technique with extensive tests on many images,
video, and by performing a user study, which indicates a clear
preference for the results of the new algorithm.
Patent Pending
More example image and video results, and code will be available soon.
Paper | Bibtex | Video | Presentation | Supplementary Material | Supplementary Results | Supplementary Video | User Study Images | Code
|
|
| |
|
| |
|