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Journals / Mühendislik Bilimleri ve Araştırmaları Dergisi / 2023 / Cilt: 5 Sayı: 1

A New High Quality Focus Measurement Operator Based on Nonsubsampled Shearlet Transform for 3D Shape Reconstruction

3B Şekil Oluşturmak için Alt Örneklemesiz Shearlet Dönüşümüne Dayalı Yeni ve Yüksek Kaliteli Odaklama Ölçüm Operatörü

Hülya DOĞAN
Ramazan Özgür DOĞAN
Pages
9–19
Publication Date
2023-04-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Subjective and objective results show that the proposed focus measure operator achieves better performance

📌 3 Key Takeaways

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Objective & Hypothesis:Shape From Focus (SFF), which does not require any additional hardware in the 3D shape creation process, is one of the most preferred strategies.
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Key Findings & Data:The SFF strategy uses a series of 2D images with different focusing on the process of creating 3D shapes of objects and consists of three basic steps: (1) Obtaining a 2D image series with different focus, (2) Calculating the focus values of image pixels, and (3) Selection of maximum focused pixel.
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Conclusion & Impact:Subjective and objective results show that the proposed focus measure operator achieves better performance
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Odaklama Ölçüm Operatörü · Odaktan Şekil · 3B Şekil Oluşturma

Abstract

Shape From Focus (SFF), which does not require any additional hardware in the 3D shape creation process, is one of the most preferred strategies. The SFF strategy uses a series of 2D images with different focusing on the process of creating 3D shapes of objects and consists of three basic steps: (1) Obtaining a 2D image series with different focus, (2) Calculating the focus values of image pixels, and (3) Selection of maximum focused pixel. In order to create 3D shapes with high accuracy and lower noise, researchers often develop a pre- or post-processing algorithms instead of proposing new focus measurement operators in the second stage of SFF. In this study, a new and high-quality focusing measurement operator based on Nonsubsampled Shearlet Transform is proposed, which does not require any pre- or post-processing. Proposed focus measurement operator is analyzed under different conditions. Subjective and objective results show that the proposed focus measure operator achieves better performance

Özet

3B şekil oluşturulma sürecinde herhangi ek donanım gerektirmeyen Odaktan Şekil (Shape From Focus - SFF) en çok tercih edilen stratejilerdendir. SFF stratejisi, 3B şekil oluşturma sürecinde farklı odaklı 2B görüntü serisi kullanmakta ve üç temel aşamadan oluşmaktadır: (1) Farklı odaklı 2B görüntü serisinin elde edilmesi, (2) Görüntü piksellerinin odaklama değerlerinin hesaplanması ve (3) Maksimum odaklı pikselin seçilmesi. Yüksek doğruluk ve daha düşük gürültü ile 3B şekil oluşturmak için, araştırmacılar SFF'nin ikinci aşamasında yeni odaklama ölçüm operatörü önermek yerine genellikle bir ön veya son işlem algoritmaları geliştirmektedirler. Literatür çalışmalarının aksine, bu çalışmada herhangi bir ön veya son işlem gerektirmeyen Alt Örneklemesiz Shearlet Dönüşümü'ne dayalı yeni ve yüksek kaliteli odaklama ölçüm operatörü önerilmektedir. Önerilen odaklama ölçüm operatörünün etkinliği sentetik görüntü serileri kullanılarak pencere boyutu ve gürültü seviyesi gibi farklı koşullar altında analiz edilmektedir. Elde edilen öznel ve nesnel sonuçlar önerilen odaklama ölçüm operatörünün daha iyi performans sağladığını göstermektedir.

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Cite This Article

DOĞAN, H., DOĞAN, R. Ö. (2023). A New High Quality Focus Measurement Operator Based on Nonsubsampled Shearlet Transform for 3D Shape Reconstruction. Mühendislik Bilimleri ve Araştırmaları Dergisi, Cilt: 5 Sayı: 1, 9–19. https://ajindex.com/articles/911597

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