The fractional calculus (FC) deals with integrals and derivatives of arbitrary (i.e., non-integer) order, and shares its origins with classical integral and differential calculus. The fractional Fourier transform (FRFT), which has been found having many applications in optics and other areas, is a generalization of the usual Fourier transform. The FC and the FRFT are two of the most interesting and useful fractional areas. In recent years, it appears many papers on the FC and FRFT, however, few of them discuss the connection of the two fractional areas. We study their relationship. The relational expression between them is deduced. The expectation of interdisciplinary cross fertilization is our motivation. For example, we can use the properties of the FC (non-locality, etc.) to solve the problem which is difficult to be solved by the FRFT in optical engineering; we can also through the physical meaning of the FRFT optical implementation to explain the physical meaning of the FC. The FC and FRFT approaches can be transposed each other in the two fractional areas. It makes that the success of the fractional methodology is unquestionable with a lot of applications, namely in nonlinear and complex system dynamics and image processing.
Newton’s rings pattern always blurs the scanned image when scanning a film using a film scanner. Such phenomenon is a kind of equal thickness interference, which is caused by the air layer between the film and the glass of the scanner. A lot of methods were proposed to prevent the interference, such as film holder, anti-Newton’s rings glass and emulsion direct imaging technology, etc. Those methods are expensive and lack of flexibility. In this paper, Newton’s rings pattern is proved to be a 2-D chirp signal. Then, the fractional Fourier transform, which can be understood as the chirp-based decomposition, is introduced to process Newton’s rings pattern. A digital filtering method in the fractional Fourier domain is proposed to reduce the Newton’s rings pattern. The effectiveness of the proposed method is verified by simulation. Compared with the traditional optical method, the proposed method is more flexible and low cost.
KEYWORDS: Quantization, Fringe analysis, Fourier transforms, Error analysis, Signal to noise ratio, Commercial off the shelf technology, Signal processing, Digital filtering, Image quality, Optical engineering
Newton’s rings fringe pattern is often encountered in optical measurement. The digital processing of the fringe pattern is widely used to enable automatic analysis and improve the accuracy and flexibility. Before digital processing, sampling and quantization are necessary, which introduce quantization errors in the fringe pattern. Quantization errors are always analyzed and suppressed in the Fourier transform (FT) domain. But Newton’s rings fringe pattern is demonstrated to be a two-dimensional chirp signal, and the traditional methods based on the FT domain are not efficient when suppressing quantization errors in such signals with large bandwidth as chirp signals. This paper proposes a method for suppressing quantization errors in the fractional Fourier transform (FRFT) domain, for chirp signals occupies little bandwidth in the FRFT domain. This method has better effect on reduction of quantization errors in the fringe pattern than traditional methods. As an example, a standard Newton’s rings fringe pattern is analyzed in the FRFT domain and then 8.5 dB of improvement in signal-to-quantization-noise ratio and about 1.4 bits of increase in accuracy are obtained compared to the case of the FT domain. Consequently, the image quality of Newton’s rings fringe pattern is improved, which is beneficial to optical metrology.