A Novel Image Compression Algorithm for High Resolution 3D Reconstruction

This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. Structured light images contain a pattern of light and shadows projected on the surface of the object, which are captured by the sensor at very high resolutions. Our algorithm...

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Published in3D research Vol. 5; no. 2
Main Authors Siddeq, M. M., Rodrigues, M. A.
Format Journal Article
LanguageEnglish
Published Heidelberg 3D Display Research Center 01.06.2014
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ISSN2092-6731
2092-6731
DOI10.1007/s13319-014-0007-6

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Abstract This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. Structured light images contain a pattern of light and shadows projected on the surface of the object, which are captured by the sensor at very high resolutions. Our algorithm is concerned with compressing such images to a high degree with minimum loss without adversely affecting 3D reconstruction. The Compression Algorithm starts with a single level discrete wavelet transform (DWT) for decomposing an image into four sub-bands. The sub-band LL is transformed by DCT yielding a DC-matrix and an AC-matrix. The Minimize-Matrix-Size Algorithm is used to compress the AC-matrix while a DWT is applied again to the DC-matrix resulting in LL 2 , HL 2 , LH 2 and HH 2 sub-bands. The LL 2 sub-band is transformed by DCT, while the Minimize-Matrix-Size Algorithm is applied to the other sub-bands. The proposed algorithm has been tested with images of different sizes within a 3D reconstruction scenario. The algorithm is demonstrated to be more effective than JPEG2000 and JPEG concerning higher compression rates with equivalent perceived quality and the ability to more accurately reconstruct the 3D models.
AbstractList This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. Structured light images contain a pattern of light and shadows projected on the surface of the object, which are captured by the sensor at very high resolutions. Our algorithm is concerned with compressing such images to a high degree with minimum loss without adversely affecting 3D reconstruction. The Compression Algorithm starts with a single level discrete wavelet transform (DWT) for decomposing an image into four sub-bands. The sub-band LL is transformed by DCT yielding a DC-matrix and an AC-matrix. The Minimize-Matrix-Size Algorithm is used to compress the AC-matrix while a DWT is applied again to the DC-matrix resulting in LL 2 , HL 2 , LH 2 and HH 2 sub-bands. The LL 2 sub-band is transformed by DCT, while the Minimize-Matrix-Size Algorithm is applied to the other sub-bands. The proposed algorithm has been tested with images of different sizes within a 3D reconstruction scenario. The algorithm is demonstrated to be more effective than JPEG2000 and JPEG concerning higher compression rates with equivalent perceived quality and the ability to more accurately reconstruct the 3D models.
ArticleNumber 7
Author Siddeq, M. M.
Rodrigues, M. A.
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Cites_doi 10.1002/0470847832
10.1109/97.863146
10.3844/jcssp.2007.740.746
10.1002/0471745790.ch17
10.1109/T-C.1974.223784
10.1109/83.136597
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Issue 2
Keywords DWT
Minimize-Matrix-Size
3D reconstruction
DCT
LSS-Algorithm
Language English
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SubjectTerms 3DR Express
Computer Imaging
Engineering
Lasers
Optical Devices
Optics
Pattern Recognition and Graphics
Photonics
Signal,Image and Speech Processing
Vision
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