Low Cost Edge Sensing for High Quality Demosaicking

TL;DR

This paper introduces a low-cost, fast edge sensing method for demosaicking that outperforms similar computational cost algorithms in accuracy and is significantly faster, making it suitable for real-time digital camera applications.

Contribution

The paper presents a novel low-cost edge sensing scheme inspired by Hamilton-Adams demosaicking, achieving high accuracy and speed in real-time image processing.

Findings

Outperforms similar-cost algorithms in accuracy

Achieves comparable quality to top methods at lower computational cost

Runs tens of times faster on high-resolution images

Abstract

Digital cameras that use Color Filter Arrays (CFA) entail a demosaicking procedure to form full RGB images. As today's camera users generally require images to be viewed instantly, demosaicking algorithms for real applications must be fast. Moreover, the associated cost should be lower than the cost saved by using CFA. For this purpose, we revisit the classical Hamilton-Adams (HA) algorithm, which outperforms many sophisticated techniques in both speed and accuracy. Inspired by HA's strength and weakness, we design a very low cost edge sensing scheme. Briefly, it guides demosaicking by a logistic functional of the difference between directional variations. We extensively compare our algorithm with 28 demosaicking algorithms by running their open source codes on benchmark datasets. Compared to methods of similar computational cost, our method achieves substantially higher accuracy, Whereas compared to methods of similar accuracy, our method has significantly lower cost. Moreover, on test images of currently popular resolution, the quality of our algorithm is comparable to top performers, whereas its speed is tens of times faster.