# Embedding Bilateral Filter in Least Squares for Efficient Edge-preserving Image Smoothing

## TL;DR

This paper introduces a new global edge-preserving smoothing method that combines bilateral filtering with least squares, achieving high performance with significantly improved efficiency over existing global methods.

## Contribution

The paper presents a novel approach embedding bilateral filter into the least squares model, balancing the accuracy of global methods with the speed of local methods.

## Key findings

- Comparable performance to state-of-the-art global methods
- Significantly faster processing times
- Flexible framework adaptable with bilateral filter variants

## Abstract

Edge-preserving smoothing is a fundamental procedure for many computer vision and graphic applications. This can be achieved with either local methods or global methods. In most cases, global methods can yield superior performance over local ones. However, local methods usually run much faster than global ones. In this paper, we propose a new global method that embeds the bilateral filter in the least squares model for efficient edge-preserving smoothing. The proposed method can show comparable performance with the state-of-the-art global method. Meanwhile, since the proposed method can take advantages of the efficiency of the bilateral filter and least squares model, it runs much faster. In addition, we show the flexibility of our method which can be easily extended by replacing the bilateral filter with its variants. They can be further modified to handle more applications. We validate the effectiveness and efficiency of the proposed method through comprehensive experiments in a range of applications.