CPDDNet: Color-Polarization Denoising and Demosaicking Network

Project Summary

Color-polarization filter array (CPFA) sensors capture color texture and polarization information in a single shot. In this project, we aim at developing a high-quality denoising and demosaicking method for color-polarization cameras.

Paper Abstract

Color-polarization filter array (CPFA) sensors capture color texture and polarization information in a single shot, but the raw mosaic data suffer from both noise and missing samples. Existing pipelines usually solve denoising (DN) and demosaicking (DM) separately, which can propagate noise or oversmooth structures needed for polarization recovery. In this work, we propose CPDDNet, a color-polarization denoising and demosaicking network for CPFA sensors. CPDDNet follows a DN-to-DM design and introduces a feature fusion module to retain raw CPFA information through both stages. This improves reconstructed color-polarization images and polarization parameters under severe noise. We further build a real-world paired polarized image dataset to support model training and evaluation. Experiments show that CPDDNet outperforms existing DM-only, DM-to-DN, and DN-to-DM baselines on the high-noise color-polarization dataset.

Proposed Method Overview

Download Materials

Interactive Visual Comparison

Select a scene, polarization angle, and the image shown on the left side of the slider. The right side is fixed to CPDDNet.

IGRI-2

CPDDNet (Ours)

Publication

CPDDNet: Color-Polarization Denoising and Demosaicking Network [PDF]

Qihang Zhang, Yusuke Monno, Masayuki Tanaka, and Masatoshi Okutomi

IEEE International Conference on Image Processing (ICIP), 2026.

BibTeX

Coming soon.