Guided Linear Upsampling

TL;DR

This paper introduces a guided linear upsampling technique that optimizes pixel interpolation and downsampling jointly to enhance detail preservation and artifact suppression in high-resolution image processing.

Contribution

It presents a novel, efficient guided upsampling method based on linear interpolation and joint optimization, improving detail retention and reducing artifacts compared to previous approaches.

Findings

Better detail preservation and artifact suppression.

Efficient and easy to implement.

Suitable for real-time high-resolution video processing.

Abstract

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.