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A Block-Matching and 3-D Filtering Algorithm for Gaussian Noise in DoFP Polarization Images | IEEE Journals & Magazine | IEEE Xplore

A Block-Matching and 3-D Filtering Algorithm for Gaussian Noise in DoFP Polarization Images


Abstract:

In this paper, we present a block-matching and 3-D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization images. This algorithm based on...Show More

Abstract:

In this paper, we present a block-matching and 3-D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization images. This algorithm based on a non-local collaborative filtering method is capable of exploiting all the different polarization channels simultaneously. Compared with the previously reported implementations for DoFP sensors, the proposed algorithm attenuates Gaussian noise in the transform domain by stacking similar 2-D image patches to form a 3-D block. According to our extensive experimental results, the proposed algorithm outperforms all the existing denoising algorithms for DoFP images including the state-of-the-art principle component analysis in terms of peak-signal-to-noise-ratio and structural similarity index. Moreover, the comparison is further extended to visual comparison, it is indicated that the image details are well-preserved by the proposed BM3D algorithm.
Published in: IEEE Sensors Journal ( Volume: 18, Issue: 18, 15 September 2018)
Page(s): 7429 - 7435
Date of Publication: 30 July 2018

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I. Introduction

Light has four main physical characteristics: intensity, wavelength, coherence, and polarization [1]. The human visual system is able to capture intensity and wavelength as brightness and color, respectively. However, it is oblivious to the polarization property of light. As a result, the mainstream image sensing systems are designed to mimic the human visual system by capturing only the intensity and wavelength property of light. It is known that the polarization property of light provides a lot of valuable information which is not available with the intensity/color imaging [2]. And the corresponding polarization image sensing systems have been demonstrated in various applications including biomedical imaging [3], [4], 3D shape reconstruction [5] and material classification [6], [7]. The recent advancements in the field of nanotechnology and nanofabrication have also made possible the capture of light’s polarization information, using a specific type of polarization sensor known as division of focal plane (DoFP) polarization image sensors. These sensors are highly compact by integrating metal nanowires offset by 45° as polarization grating, which is also named as micro-polarizer array [8]–[14]. These polarization sensors are arranged in a periodic pattern, namely a super-pixel, which despite having one more polarization channel, very well mimics the Bayer color filter array (CFA) with three wavelength channels (i.e. RGB) [15], as shown in Fig. 1.

Mainstream micro-polarizer array pattern of DoFP polarization image sensor.

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