Evidence map›Paper›PMID 40346296›Full record

ArticleScientific reports2025

Improving PSNR and computational efficiency in orthogonal ghost imaging.

Kobra Hassanzadeh, Sohrab Ahmadi-Kandjani, Reza Kheradmand, Seyed Amir Mortazavi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kobra HassanzadehFaculty of Physics, University of Tabriz, Tabriz, Iran.
Sohrab Ahmadi-KandjaniFaculty of Physics, University of Tabriz, Tabriz, Iran. s_ahmadi@tabrizu.ac.ir.
Reza KheradmandFaculty of Physics, University of Tabriz, Tabriz, Iran.
Seyed Amir MortazaviFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we present an orthogonal ghost imaging (OGI) method based on two-dimensional discrete cosine transform (2D-DCT) patterns. Unlike traditional methods that are based on random or sinusoidal patterns, our method relies on structured orthogonal patterns to enhance both image quality and reconstruction speed, outperforming random and sinusoidal-based approaches in terms of reconstruction fidelity and computational efficiency. A new reconstruction formula is derived in our approach. In addition, using a phase-shift illumination pattern technique helps to effectively reduce environmental noise. Simulation and experimental results show that high-quality image reconstruction is achievable even with reduced sampling rates. For instance, using only 30% of the measurements is enough to meet the Peak Signal-to-Noise Ratio (PSNR) threshold predicted by Shannon entropy. Compared to differential and sinusoidal ghost imaging techniques, the proposed method consistently outperforms them in terms of signal-to-noise ratio (SNR) and reconstruction efficiency. These findings suggest that OGI offers a promising direction for efficient and low-cost ghost imaging systems.

Indexed as

Computational ghost imagingImage reconstructionOrthogonal ghost imaging (OGI)Shannon entropySignal-to-noise ratio

Identifiers

PMID40346296
PMCPMC12064693

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.