Content adaptive screen image scaling

TL;DR

This paper introduces a content adaptive screen image scaling method that classifies screen regions and applies optimized shift linear interpolation to enhance visual quality while maintaining low computational complexity for real-time applications.

Contribution

It presents a novel classification-based adaptive scaling scheme with offline optimized shift offsets for improved real-time screen image scaling.

Findings

Achieves good visual quality in real-time scaling

Maintains low computational complexity

Effectively classifies screen content into text and pictorial regions

Abstract

This paper proposes an efficient content adaptive screen image scaling scheme for the real-time screen applications like remote desktop and screen sharing. In the proposed screen scaling scheme, a screen content classification step is first introduced to classify the screen image into text and pictorial regions. Afterward, we propose an adaptive shift linear interpolation algorithm to predict the new pixel values with the shift offset adapted to the content type of each pixel. The shift offset for each screen content type is offline optimized by minimizing the theoretical interpolation error based on the training samples respectively. The proposed content adaptive screen image scaling scheme can achieve good visual quality and also keep the low complexity for real-time applications.