Abstract
Image quality metrics are a critical element in the iterative Fourier transform algorithms (IFTAs) for the computer generation of phase-only holograms. Conventional image quality metrics such as root-mean-squared error (RMSE) are sensitive to image content and unable to reflect the perceived image quality accurately. This would have a significant impact on the calculation speed and the quality of the generated hologram. In this work, the structure similarity (SSIM) was proposed as an image quality metric in IFTAs due to its ability to predict the perceived image quality in the presence of the white Gaussian noise and its independence on the image content. This would enable IFTAs to terminate when further iterations would no longer lead to improvement in the perceived image quality. As a result, up to 75% of unnecessary iterations were eliminated by the use of SSIM as the image quality metric.
Highlights
Phase-only holograms can be used for 2-D [1,2,3,4] or 3-D image projection [5,6], free space optical switches [7,8,9,10,11] and optical tweezers [12,13]
This work aims to further study the noise characteristics in the images reconstructed from the phase-only holograms that are calculated by iterative Fourier transform algorithms (IFTAs)
This work has identified that the main distortion in the images reconstructed from the phase-only holograms calculated by IFTAs is the white Gaussian noise
Summary
Phase-only holograms can be used for 2-D [1,2,3,4] or 3-D image projection [5,6], free space optical switches [7,8,9,10,11] and optical tweezers [12,13]. Fourier transform algorithms (IFTAs) [15] including Gerchberg–Saxton (GS) [16], Fienup [17], and ‘Fienup with don’t-care’ (FiDOC) [18,19], are able to accelerate the calculation significantly by using the fast Fourier transform (FFT) In these algorithms, the errors in the image reconstructed from the computer-generated phase-only hologram are evaluated based on certain key image quality metrics at the end of each iteration. This work aims to further study the noise characteristics in the images reconstructed from the phase-only holograms that are calculated by IFTAs. At present, the root-mean-squared error (RMSE) [22,23] is the most widely used image quality metric in IFTAs. Gerchberg et al proved that the RMSE would always converge towards a lower value as the iteration moved forward in IFTAs. The speed of convergence is usually quicker in Fienup algorithm than in the standard GS algorithm. To authors’ knowledge, it is the first time that the perceived image quality is used in the IFTAs for the phase-only hologram generation
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
