Learning to Deblur Polarized Images

TL;DR

This paper introduces a polarization-aware deblurring method for polarized images captured by polarization cameras, effectively addressing motion blur issues while preserving polarization information for improved vision applications.

Contribution

The paper proposes a novel divide-and-conquer neural network approach that explicitly decomposes the deblurring task into two sub-problems, enhancing performance over existing methods.

Findings

Achieves state-of-the-art results on synthetic and real-world polarized images.

Improves polarization-based vision tasks like dehazing and reflection removal.

Demonstrates robustness in handling motion blur in polarization images.

Abstract

A polarization camera can capture four linear polarized images with different polarizer angles in a single shot, which is useful in polarization-based vision applications since the degree of linear polarization (DoLP) and the angle of linear polarization (AoLP) can be directly computed from the captured polarized images. However, since the on-chip micro-polarizers block part of the light so that the sensor often requires a longer exposure time, the captured polarized images are prone to motion blur caused by camera shakes, leading to noticeable degradation in the computed DoLP and AoLP. Deblurring methods for conventional images often show degraded performance when handling the polarized images since they only focus on deblurring without considering the polarization constraints. In this paper, we propose a polarized image deblurring pipeline to solve the problem in a polarization-aware manner by adopting a divide-and-conquer strategy to explicitly decompose the problem into two less ill-posed sub-problems, and design a two-stage neural network to handle the two sub-problems respectively. Experimental results show that our method achieves state-of-the-art performance on both synthetic and real-world images, and can improve the performance of polarization-based vision applications such as image dehazing and reflection removal.