Optical signal and image processing: from analog systems to digital pipeline smart pixels

In this paper, we consider a class of N-th order lattice filter with gains as an extension to the traditional lattice filter structures and develop analysis and synthesis of such filters. In the analysis-synthesis parts, we present recursive methods to derive the input-output transfer function of the filter in terms of parameters of the lattice structure such as the time delay, gains, transmission and reflection coefficients and vice versa. Stability of the filter is analyzed and an algorithm to test the stability is proposed. This class of MIMO lattice filters with adjustable gains models integrated photonic devices under development in our labs for optical communication and high speed signal processing applications. Our signal processing approach to characterizing this type of lattice structures can also be used in filter realization by VLSI, FPGA, or programmable processors for acoustic or speech applications

Even in this digital age, SAW and Optical devices remain indispensable analogue signal processing technologies whose operation and success derive from common wave propagation phenomena. In this review I hope to explain why this is so, and will remain so for the foreseeable future. Historically, the development and exploitation of these technologies arose during the Cold War primarily from the military need for an unsurpassed signal processing capability, although both are now widely exploited in civil applications as well. Following the Introduction, this paper briefly reviews the construction, operation, attractions, and selected applications of the SAW devices developed since the invention of the Interdigital Transducer (IDT) in 1965. These devices include delay lines, bandpass filters, and the first SAW device used in anger, the dispersive delay line which was vital to the realisation of pulse compression radar. I shall also review the attractions of SAW oscillators, which I believe still enjoy an opportunity to contribute to the insatiable military need for improved overall stability. Following this I introduce some components and techniques devised by the optics community for signal and image processing since the invention of the laser in 1960, beginning with techniques for pattern recognition and the ingenious technique devised to realise real-time Synthetic Aperture Radar, (SAR) image formation. More recently, the invention and development of laser diodes and fibre optics by the telecommunications industry has led to the realisation of optical signal processing techniques whose functionality is in many respects complementary to that of SAW devices. In particular, optical techniques are now useful for the generation, delay, sampling, and distribution of signals at higher rf frequencies (and bandwidths) than SAW devices, ie at microwave and mm- wave frequencies and above, leading to the modern field of activity known as Microwave Photonics. Some current research topics in this field are described, including stable microwave generation, phased array antenna beamforming, and A/D conversion, each being relevant to future military and civil systems.

Besides optical fibers are excellent communication media, they are attractive for real time, high speed signal processing on the ground of that they possess very nice merits such as low-loss, large bandwidth-delay product, light weight, and immunity to electromagnetical interferences. A typical optical fiber signal processing device is composed of light sources, delay lines, attenuators, directional couplers, and photodetectors. Many various functions such as frequency filtering, convolution, pulse compression, high speed pulse generation, encoding, and decoding for the incoherent optical fiber signal processing devices are reported in the literature. Recently the lattice optical fiber structures are investigated intensively due to convenience for mathematical formulation and implementation. Although the optical fiber signal processing devices have many attractive features, they have inherent constraints owing to positive system properties, i.e. nonnegative quantities of signals(optical intensities), attenuations, and coupling coefficients. The constraints of the finite impulse response (FIR) optical fiber filters were presented. In this paper, we establish the constraints of the infinite impulse response (IIR) optical fiber filters by means of investigating the possibility of designing the filters with the desirable properties such as maximally flat or equiripple responses. In addition, the characteristics and design principles of the optical fiber filters can be clearly understood from the processes. The mathematical derivation makes use of the state-variable analysis technique to approach this problem. This technology is suitable to describe for both cases: FIR and IIR. Hence the confirmed constraints can be directly applied to the FIR case.

As digital circuits are approaching the limits of Moore’s law, a great deal of effort has been directed to alternative computing approaches. Among them, the old concept of optical signal processing (OSP) has attracted attention, revisited in the light of metamaterials and nano-photonics. This approach has been successful in realizing basic mathematical operations, such as derivatives and integrals, but it is difficult to be applied to more complex ones. Here, inspired by digital filters, we propose a radically new OSP approach, able to realize arbitrary mathematical operations over a nano-photonic platform. Our concept consists in first sampling an optical signal in space through an array of optical antennas and then realizing the desired mathematical operation in discrete space through a network with a discrete number of input and output ports. The design of such network boils down to the design of a structure with a given scattering matrix, which for arbitrarily complex operations can be accomplished through inverse design algorithms. We demonstrate this concept for the case of spatial differentiation through a heuristic design based on a waveguide with periodic arrays of input/output channels at its opposite walls. Our approach combines the robustness and generality of traditional Fourier-based OSP with the compactness of nano-photonics and has the potential of transforming the design of OSP systems with applications in image processing and analog computing.

This paper reviews opportunities of optical signal form conversion as typified by time-space conversion in optical signal processing. Several examples of typical ultra-fast optical signal processing using optical signal form conversion are described and their applications are introduced in respect to photonic networks, ultra-fast measurement, and so on.

Optical interferometry provides high-precision displacement and angle measurement solutions for a wide range of cutting-edge industrial applications. One of the key factors to achieve such precision lies in highly accurate optical encoder signal processing, as well as the calibration and compensation techniques customized for specific measurement principles. Optical interferometric techniques, including laser interferometry and grating interferometry, are usually classified into homodyne and heterodyne systems according to their working principles. In homodyne interferometry, the displacement is determined by analyzing the phase variation of amplitude-modulated signals, and common demodulation methods include error calibration methods and ellipse parameter estimation methods. Heterodyne interferometry obtains displacement information through the phase variation of beat-frequency signals generated by the interference of two light beams with shifted frequencies, and its demodulation techniques include pulse-counting methods, quadrature phase-locked methods, and Kalman filtering. This paper comprehensively reviews the widely used signal processing techniques in optical interferometric measurements over the past two decades and conducts a comparative analysis based on the characteristics of different methods to highlight their respective advantages and limitations. Finally, the hardware platforms commonly used for optical interference signal processing are introduced.

In the last few years, a considerable effort has been expended on the development of a number of both active and passive guided-wave devices, such as laser diodes, electrooptic modulators, acoustooptic transducers, photodetectors and microlens arrays, for optical signal processing applications including optical computing 1-3. Many simple optical devices can be easily fabricated by using mature and reproducible technologies. The interest in optical processors involving simple devices is mainly due to a lower power consumption, reduced size, cost and weight and high throughput with respect to the corresponding electronic processors. A number of guided-wave optical circuits for communications, signal processing and optical computing have been demonstrated using the acoustooptic, magnetooptic and electrooptic effects 4. Moreover, fields of application of particular interest are synthetic aperture radar (SAR), remote sensing and beam forming of linear array antennas, which are all well suited for optics-based processing because of the parallel processing allowed by optical architectures. Therefore, guided-wave optical processors can be successfully applied to the optical control of microwaves, to the reconstruction of two-dimensional images using both spatial and time integration, to data classification and identification in satellite applications and for performing a number of signal processing and optical computing functions.

Potential areas of development in optically based adaptive signal processing are considered together with an assessment of current technological directions. The rapid adoption of superhigh‐throughput lightwave communications media and systems suggests that fully optical signal processing would be very desirable to take advantage of the speed. The broad conclusion of this analysis is that at present it is not feasible to implement fully optical adaptive signal processors but that in time it might be so. ‘Not yet’ is our surmise. A brief literature survey and description of existing prototype optoelectronic adaptive systems is also provided.

We present a summary of our recent work on using lattice-form Mach-Zehnder interferometers implemented using silica-based planar lightwave circuit technology for optical signal processing. In particular, we demonstrate that the same device structure (either based on 6 taps or 12 taps) can be used to perform various signal processing functions ranging from pulse repetition rate multiplication to arbitrary waveform generation.

"Optical Signal and Image Processing." Optica Acta: International Journal of Optics, 26(3), pp. 307–308

The issue of superresolving signal and image restoration appears in many areas, such as the restoration of diffraction-limited images, geophysical prospecting, radar and sonar signal processing, biomedical imaging, image and signal bandwidth compression, reconstruction of signals and images from partial and incomplete information, etc. There is a large repertoire of different techniques and procedures available to reconstruct such images. However, most of these techniques work well only in the absence of noise. Because this is an ill-posed problem, the actual reconstruction is sensitive to noise. Recently, new optical signal and image processing techniques have been suggested that are based on associative memory processing concepts. The purpose of this paper is to explore various associative memory processor concepts applied to the superresolving image restoration problem. Results of computer simulation will be presented.

A foundry-available platform that integrates both photonics and electronics has showcased the immense potential of silicon photonic devices in groundbreaking applications like optical chaos communication, LiDAR, and optical signal processing. Recently developed photonic processors, specifically designed for optical signal processing, not only boast higher throughput data rates and lower energy consumption compared to traditional digital counterparts but also offer versatile functionalities such as image detection, parallel sensing, and dynamic signal reconstruction. These capabilities address the growing market demands effectively. In this study, we present the utilization of a silicon photonic (SiP) mesh as a photonic processor for a signal compensation algorithm. The experiment demonstrates the ability to recover optical chaos signals after their propagation through atmospheric turbulence. This breakthrough has significant implications for future free-space applications, including chaos LiDAR and chaos communications hence offering promising solutions in optical signal processing and communication in challenging environments

Photonic integration is a critical emerging trend in the development of photonic devices. Its significance parallels that of the microelectronic integrated circuits (IC) albeit it has developed slower due to its diversity and often contrasting requirements. Photonic integrated circuits (PIC) is basically made up of small but important building blocks combined to realize even more complex circuits so that it may perform wider range of functionalities on optical signals used in various applications, such as optical communication, instrumentation, sensing, and signal processing.

: Separate studies were performed on beam expansion and on Distributed Bragg Reflector (DBR) lasers preliminary to monolithic integration on GaAs substrates. These components are proposed for use in optical signal processing, for fiber optic sources and for high-brightness lasers. (Author)

Fibre optic technology lends yet another dimensions to the topic of optical signal processing complementing both Fourier plane and digital optical approaches. It is inevitable that eventually optical signal processing will combine all three of these basic concepts. However, in this paper we consider the possibilities offered by the fibre optic transmission medium in the context of signal processing. The unique features of the transmission medium imply that precise frequency domain filters may be readily realised. Furthermore, functions such as matrix-matrix multiplication and code recognition may also be programmed in the all optical fibre form. These processes are essentially linear but the addition of a simple non-linear element may yet further extend the capability of these basic concepts. This paper outlines the general principles underlying fibre optic signal processing and gives some indication of its performance potential.