Journal of Imaging

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J. Imaging, Volume 6, Issue 1 (January 2020) – 3 articles

Cover Story (view full-size image): This paper proposes an effective and fast method to produce automatically holographic 3D images from low-cost stereo cameras without user intervention. The presented algorithm retrieves images from a stereo camera, evaluates correlations between left and right images (by using the DeepFlow algorithm), and produces intermediate lightfield views which output holographic displays for slanted lenticular monitors, such as the new Looking Glass Holoplay device. Some intermediate processing steps are necessary to get realistic 3D images: Holoplay per-device calibration, left–right correlation, intermediate views, quilt creation, and final “native” multiview image generation. In order to speed up these processes and to reduce run-time computation, some Lookup Tables are introduced as a first step towards achieving 2D to 3D conversion in real-time. View this paper

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3 pages, 205 KiB

Open AccessEditorial

Acknowledgement to Reviewers of Journal of Imaging in 2019

by Journal of Imaging Editorial Office

J. Imaging 2020, 6(1), 3; https://doi.org/10.3390/jimaging6010003 - 17 Jan 2020

Viewed by 2973

Abstract

Full article

13 pages, 1757 KiB

Open AccessArticle

Multiple Query Content-Based Image Retrieval Using Relevance Feature Weight Learning

by Abeer Al-Mohamade, Ouiem Bchir and Mohamed Maher Ben Ismail

J. Imaging 2020, 6(1), 2; https://doi.org/10.3390/jimaging6010002 - 17 Jan 2020

Cited by 18 | Viewed by 4286

Abstract

We propose a novel multiple query retrieval approach, named weight-learner, which relies on visual feature discrimination to estimate the distances between the query images and images in the database. For each query image, this discrimination consists of learning, in an unsupervised manner, the optimal relevance weight for each visual feature/descriptor. These feature relevance weights are designed to reduce the semantic gap between the extracted visual features and the user’s high-level semantics. We mathematically formulate the proposed solution through the minimization of some objective functions. This optimization aims to produce optimal feature relevance weights with respect to the user query. The proposed approach is assessed using an image collection from the Corel database. Full article

(This article belongs to the Special Issue Advances in Image Feature Extraction and Selection)

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9 pages, 2181 KiB

Open AccessArticle

Morphing a Stereogram into Hologram

by Enrique Canessa and Livio Tenze

J. Imaging 2020, 6(1), 1; https://doi.org/10.3390/jimaging6010001 - 02 Jan 2020

Cited by 4 | Viewed by 4670

Abstract

We developed a method to transform stereoscopic two-dimensional (2D) images into holograms via unsupervised morphing deformations between left (L) and right (R) input images. By using robust DeepFlow and light-field rendering algorithms, we established correlations between a 2D scene and its three-dimensional (3D) display on a Looking Glass HoloPlay monitor. The possibility of applying this method, together with a lookup table for multi-view glasses-free 3D streaming with a stereo webcam, was also analyzed. Full article

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J. Imaging, Volume 6, Issue 1 (January 2020) – 3 articles

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