# The bilateral solver for quality estimation based multi-focus image fusion

## TL;DR

This paper introduces BS-QEBIF, a fast bilateral solver-based multi-focus image fusion method that produces high-quality all-in-focus images by smoothing focus-level maps while preserving edges, outperforming existing methods.

## Contribution

The paper presents a novel fast bilateral solver approach for smoothing focus-level maps in multi-focus image fusion, improving quality and boundary handling.

## Key findings

- Outperforms 13 other fusion methods objectively and subjectively.
- Produces all-in-focus images with preserved details and no residual errors.
- Effectively handles focus-level-changed boundary regions without artifacts.

## Abstract

In this work, a fast Bilateral Solver for Quality Estimation Based multi-focus Image Fusion method (BS-QEBIF) is proposed. The all-in-focus image is generated by pixel-wise summing up the multi-focus source images with their focus-levels maps as weights. Since the visual quality of an image patch is highly correlated with its focus level, the focus-level maps are preliminarily obtained based on visual quality scores, as pre-estimations. However, the pre-estimations are not ideal. Thus the fast bilateral solver is then adopted to smooth the pre-estimations, and edges in the multi-focus source images can be preserved simultaneously. The edge-preserving smoothed results are utilized as final focus-level maps. Moreover, this work provides a confidence-map solution for the unstable fusion in the focus-level-changed boundary regions. Experiments were conducted on $25$ pairs of source images. The proposed BS-QEBIF outperforms the other $13$ fusion methods objectively and subjectively. The all-in-focus image produced by the proposed method can well maintain the details in the multi-focus source images and does not suffer from any residual errors. Experimental results show that BS-QEBIF can handle the focus-level-changed boundary regions without any blocking, ringing and blurring artifacts.