Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm
, Francis Gracy Arockiaraj 2, Shivasubramanian Gopinath 3, Daniel Smith 4, Tauno Kahro 1, Sandhra-Mirella Valdma 1, Andrei Bleahu 1, Soon Hock Ng 4, Andra Naresh Kumar Reddy 5,6, Tomas Katkus 4, Aravind Simon John Francis Rajeswary 1, Rashid A. Ganeev 5,7, Siim Pikker 1, Kaupo Kukli 1, Aile Tamm 1, Saulius Juodkazis 4,8 and Vijayakumar Anand 1,4,*
Round 1
Reviewer 1 Report
In this paper, the authors implement the deconvolution of blurred object image in a refractive lens system using Lucy-Richardson-Rosen Algorithm (LRRA). Experimental results are satisfactory. But the reviewer thinks this work lacks of novelty. The LRRA was previously proposed by other researchers and the authors of this paper adopts an existing method. In addition, the reviewer has the following concerns:
(1)3D imaging is frequently mentioned in the paper. But the reviewer thinks only 2D object images at certain depth layers are tested in the experiment. No attempt on a 3D object scene consisting of multiple depth layers. In addition, in the introduction part, several major 3D imaging techniques such as structured light and time-of-flight (tof) are not reviewed.
(2)Some parts of the paper are not very well written. The notations of symbols are not very complete.
(3)The quality of reconstruction results with different methods may be further evaluated quantitatively.
Overall, the reviewer does not recommend the acceptance of this paper for publication in Photonics.
Author Response
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Reviewer 2 Report
The manuscript describes the deep deconvolution of object information of a refractive lens by utilizing Lucy-Richardson-Rosen algorithm (LRRA). The performance of the proposed approach is compared with other existing approaches. The manuscript is well organized and supported with simulation and experimental results. Some of the minor points in the manuscript are follows:
1. The manuscript demonstrates the simulation and experimental results with different objects. It will be more interesting if the authors were able to provide one set of simulation and experimental results with the same object.
2. On page 5, line 183: the figure number is wrongly cited in the text. It should be Figure 4.
3. The manuscript needs to include the scale bars and intensity map in the respective figures of simulation and experimental results.
Author Response
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Reviewer 3 Report
In this work, the authors numerically and experimentally showed that the proposed LRRA algorithm for reconstructing the intensity of an object from its image in incoherent light is more efficient than the well-known LRA and NLR algorithms. Therefore, the work can be published after the authors take into account the comments.
Comments
1. In equation (3), authors should define functions I with a wave and the notation F-1 before curly brackets.
2. In the equation after (3) there is a function I'(PSF) , which is complex conjugate to the function I(PSF). But it follows from equation (1) that the function I(PSF) is real.
3. In the same equation, there is a denominator I(R)xI(PSF). Authors should explain whether this denominator can reach zero.
4. For figures 6-8, their physical dimensions should be indicated.
5. Figure 10 shows SSIM, but there is no formula by which this index was calculated. The formula for calculating SSIM should be given.
Author Response
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Round 2
Reviewer 1 Report
The reviewers' concerns have been well addressed. This paper can be accepted for publication.
Author Response
We thank the reviewer for their valuable comments and acceptance.
