Special Issue "Photometric Stereo"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 5089

Special Issue Editor

Dr. Daisuke Miyazaki
E-Mail Website
Guest Editor
Image Media Engineering and Computer Graphics Laboratory, Dept. of Intelligent Systems, Graduate School of Information Sciences, Hiroshima City University, Hiroshima Prefecture 731-3194, Japan 
Interests: computer vision; polarization; multispectral imaging; shape estimation
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Special Issue Information

Dear Colleagues,

Photometric stereo is a well-known technique which estimates the normal surface of objects. Recent trends in 3D printers have widened the range of uses of commercial sensors that measure the 3D coordinates of object surfaces; however, commercial sensors which can measure the normal surface of an object using a photometric stereo are still rare. Photometric stereo is still a hot topic in this field, and various research papers are published on it each year. Recent techniques such as deep learning have also affected the progress of photometric stereo research. This Special Issue aims to collect a wide variety of photometric stereo works and helps the progress of this field.

The objective of this Special Issue is to provide opportunities to share new insights with researchers in various fields that will contribute to a future roadmap of photometric stereo. Papers must be original research with novel results or a suitable review of the current state of the art.

Dr. Daisuke Miyazaki
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • photometric stereo and its applications
  • shape-from-shading and related techniques
  • photometric stereo using CNN
  • uncalibrated photometric stereo
  • example-based photometric stereo
  • color photometric stereo
  • photometric stereo under natural illumination
  • photometric stereo of uncommon lights such as multispectral light, infrared light, or fluorescent light
  • photometric stereo in hazy weather or underwater
  • photometric stereo for metals and arbitrary BRDFs
  • photometric linearization and sparse regression
  • photometric stereo with multiple cameras
  • sensor fusion using shading information and other sensors
  • photometric stereo for various fields such as computer graphics, medical science, or the industrial field

Published Papers (3 papers)

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Research

Article
Atmospheric Correction for High-Resolution Shape from Shading on Mars
J. Imaging 2022, 8(6), 158; https://doi.org/10.3390/jimaging8060158 - 01 Jun 2022
Viewed by 1145
Abstract
Digital Elevation Models (DEMs) of planet Mars are crucial for many remote sensing applications and for landing site characterization of rover missions. Shape from Shading (SfS) is known to work well as a complementary method to greatly enhance the quality of photogrammetrically obtained [...] Read more.
Digital Elevation Models (DEMs) of planet Mars are crucial for many remote sensing applications and for landing site characterization of rover missions. Shape from Shading (SfS) is known to work well as a complementary method to greatly enhance the quality of photogrammetrically obtained DEMs of planetary surfaces with respect to the effective resolution and the overall accuracy. In this work, we extend our previous lunar shape and albedo from shading framework by embedding the Hapke photometric reflectance model in an atmospheric model such that it is applicable to Mars. Compared to previous approaches, the proposed method is capable of directly estimating the atmospheric parameters from a given scene without the need for external data, and assumes a spatially varying albedo. The DEMs are generated from imagery of the Context Camera (CTX) onboard the Mars Reconnaissance Orbiter (MRO) and are validated for clear and opaque atmospheric conditions. We analyze the necessity of using atmospheric compensation depending on the atmospheric conditions. For low optical depths, the Hapke model without an atmospheric component is still applicable to the Martian surface. For higher optical depths, atmospheric compensation is required to obtain good quality DEMs. Full article
(This article belongs to the Special Issue Photometric Stereo)
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Article
Example-Based Multispectral Photometric Stereo for Multi-Colored Surfaces
J. Imaging 2022, 8(4), 107; https://doi.org/10.3390/jimaging8040107 - 11 Apr 2022
Viewed by 1391
Abstract
A photometric stereo needs three images taken under three different light directions lit one by one, while a color photometric stereo needs only one image taken under three different lights lit at the same time with different light directions and different colors. As [...] Read more.
A photometric stereo needs three images taken under three different light directions lit one by one, while a color photometric stereo needs only one image taken under three different lights lit at the same time with different light directions and different colors. As a result, a color photometric stereo can obtain the surface normal of a dynamically moving object from a single image. However, the conventional color photometric stereo cannot estimate a multicolored object due to the colored illumination. This paper uses an example-based photometric stereo to solve the problem of the color photometric stereo. The example-based photometric stereo searches the surface normal from the database of the images of known shapes. Color photometric stereos suffer from mathematical difficulty, and they add many assumptions and constraints; however, the example-based photometric stereo is free from such mathematical problems. The process of our method is pixelwise; thus, the estimated surface normal is not oversmoothed, unlike existing methods that use smoothness constraints. To demonstrate the effectiveness of this study, a measurement device that can realize the multispectral photometric stereo method with sixteen colors is employed instead of the classic color photometric stereo method with three colors. Full article
(This article belongs to the Special Issue Photometric Stereo)
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Article
DRM-Based Colour Photometric Stereo Using Diffuse-Specular Separation for Non-Lambertian Surfaces
J. Imaging 2022, 8(2), 40; https://doi.org/10.3390/jimaging8020040 - 08 Feb 2022
Cited by 3 | Viewed by 1505
Abstract
This paper presents a photometric stereo (PS) method based on the dichromatic reflectance model (DRM) using colour images. The proposed method estimates surface orientations for surfaces with non-Lambertian reflectance using diffuse-specular separation and contains two steps. The first step, referred to as diffuse-specular [...] Read more.
This paper presents a photometric stereo (PS) method based on the dichromatic reflectance model (DRM) using colour images. The proposed method estimates surface orientations for surfaces with non-Lambertian reflectance using diffuse-specular separation and contains two steps. The first step, referred to as diffuse-specular separation, initialises surface orientations in a specular invariant colour subspace and further separates the diffuse and specular components in the RGB space. In the second step, the surface orientations are refined by first initialising specular parameters via solving a log-linear regression problem owing to the separation and then fitting the DRM using Levenburg-Marquardt algorithm. Since reliable information from diffuse reflection free from specularities is adopted in the initialisations, the proposed method is robust and feasible with less observations. At pixels where dense non-Lambertian reflectances appear, signals from specularities are exploited to refine the surface orientations and the additionally acquired specular parameters are potentially valuable for more applications, such as digital relighting. The effectiveness of the newly proposed surface normal refinement step was evaluated and the accuracy in estimating surface orientations was enhanced around 30% on average by including this step. The proposed method was also proven effective in an experiment using synthetic input images comprised of twenty-four different reflectances of dielectric materals. A comparison with nine other PS methods on five representative datasets further prove the validity of the proposed method. Full article
(This article belongs to the Special Issue Photometric Stereo)
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