Standard coherent optical image processing employs a Fourier plane in a 4−f system[
Chinese Optics Letters, Volume. 20, Issue 2, 021101(2022)
Optical image processing using acousto-optic modulators as programmable volume holograms: a review [Invited]
Bragg processing using a volume hologram offers an alternative in optical image processing in contrast to Fourier-plane processing. By placing a volume hologram near the object in an optical imaging setup, we achieve Bragg processing. In this review, we discuss various image processing methods achievable with acousto-optic modulators as dynamic and programmable volume holograms. In particular, we concentrate on the discussion of various differentiation operations leading to edge extraction capabilities.
1. Introduction
Standard coherent optical image processing employs a Fourier plane in a 4−f system[
To have a self-contained review, in Section 2, we discuss some of the fundamentals of acousto-optics, introducing some important parameters of the AOM, and, in Section 3, we summarize the Korpel–Poon multiple plane-wave theory. The presentation in these two sections closely follows the book by Poon and Kim[
2. Fundamentals of Acousto-Optics
In acousto-optics, we deal with the interaction between sound and light. An AOM consists of a transparent acoustic medium, such as dense glass. A piezoelectric transducer is bonded to the acoustic medium to provide propagating sound waves into it. When a sound wave of wavelength propagates into the acoustic medium, it causes perturbations in the index of refraction, which in turn modulates the laser beam traversing the acoustic medium. Figure 1 shows the physical situation of the interaction between sound and light.
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Figure 1.AOM illustrating diffraction of light by sound.
There are a variety ways to explain the interaction between sound and light. When we consider the interaction of plane waves of light and sound, we assume that the length of the transducer is being sufficiently wide so as to produce straight wavefronts as a plane wave of sound. Because plane waves have well-defined momenta, we consider the plane-wave interaction of sound and light as a collision of photon and phonon particles. The laws of conservation of energy and momentum are among the most fundamental laws of physics in the process of collision. Denoting the wavevectors of the incident light, diffracted plane waves of light and sound by , , and , respectively, and assuming the sound wavefronts are approaching the incident light, the law of conservation of momentum gives us
The corresponding law of conservation of energy gives us (after division by )
Figure 2.Upshifted Bragg diffraction: (a) wavevector diagram and (b) experimental configuration. Adapted from Ref. [28].
The two conservation laws can be employed again to give two equations similar to Eqs. (2) and (3) if we exchange the directions of incident and diffracted light. With the so-called downshifted interaction in acousto-optics and corresponding to Eqs. (2) and (3), we have
Figure 3.Downshifted Bragg diffraction: (a) wavevector diagram and (b) experimental configuration. Adapted from Ref. [28].
From Figs. 2(a) and 3(a), we note that the wavevector diagrams are closed for both cases of the interaction. As a result, there can only be one critical incident angle, i.e., the Bragg angle, such that plane waves of sound and light can interact. By inspecting either Fig. 2(a) or 3(a), we find the Bragg angle as
Figure 4.Multiple diffraction. Adapted from Ref. [28].
In addition to the Bragg angle of the AOM, there is another important parameter called the Klein–Cook parameter , which is defined as[
If [
3. Korpel–Poon Multiple Plane-Wave Scattering Theory
In the previous section, we used the simple particle approach to describe the necessary conditions for Bragg diffraction to occur. Often, we are interested in knowing how the acousto-optic interaction process affects the amplitude distribution among the different diffracted beams. We shall adopt the Korpel–Poon multiple plane-wave theory to understand this aspect, which is summarized as follows[
Figure 5.AOM modeled by a column of sound of width L. Adapted from Ref. [28].
For a given value of and , the solution to the infinite coupled differential equation in Eq. (8) represents the contributions to the th-order plane wave of light, , owing to the incident plane wave at .
4. Transfer Functions and Acousto-Optic Spatial Filtering
For many decades, the use of acousto-optics has been extensively confined to signal processing. The reason is that AOMs are one-dimensional (1D) devices, and the interaction between light and sound is confined on a plane defined by the wavevectors of sound and light. The use of AOMs operating in the Bragg regime for 2D image processing was pioneered by Xia et al.[
We consider upshifted Bragg diffraction with off-Bragg angle incidence and limit to two diffracted orders. Hence, we let , where represents the deviation of the incident plane wave away from the exact Bragg angle. Equation (8) becomes
These solutions represent the plane-wave solutions that are due to oblique incidence and have been used for thick hologram gratings[
Equation (11) motivated Poon and Chatterjee[
These transfer functions show angular selectivity, and they depend on the angle of incidence of the light incident on the AOM. The transfer functions can be written as a function of spatial frequency if we inspect the interaction geometry shown in Fig. 6.
Figure 6.Diffraction geometry for upshifted Bragg operation. Adapted from Ref. [28].
, , and are the incident beam, zeroth-order diffracted beam, and first-order diffracted beam, respectively. For instance, the incident beam can be decomposed into multiple plane waves with different amplitudes propagating in directions defined by . The different amplitudes are simply given by Eq. (13a). Since the spectrum of is
A similar expression exists for the first-order diffracted beam:
Figure 7.Characteristics of |H0(kx′)| and |H1(kx′′)| as a function of Q and α. (a) and (b) Transfer function for the zeroth-order beam and the first-order beam at Λ = 0.01 mm with Q = 14, respectively; (c) and (d) transfer function for the zeroth-order beam and the first-order beam at Λ = 0.01 mm with Q = 28, respectively.
Acousto-optic spatial filtering to the incident beam as an input image is computed according to Eq. (17). Indeed, the conversion from a Gaussian laser beam into flattop profiles has been investigated using the transfer function of the first-order beam, which has many important applications such as laser fusion, laser printing, and optical data processing[
Figure 8.Flaptop beams obtained by the fine tuning of Q or α (alpha) through H1(kx′′Λ/π). Input laser beam is of the profile e−x2/2σ2. Reprinted with permission from Ref. [16] © The Optical Society.
The transfer function of the zeroth-order beam has been used for the investigation of image processing. We place an AOM near the object in an optical imaging setup, as shown in Fig. 9. The object is placed on the input plane, and the output plane is the image plane. The AOM is rotated by the Bragg angle, i.e., for upshifted interaction configuration. When the AOM is turned off, i.e., , point A is imaged onto point B. With AOM turned on, the first diffracted order appears, and point B' is formed. In the experiment reported, the size of each of the letter is about . The focal length of the lens is 195 mm. and are used for the AOM.
Figure 9.Diffraction by AOM and image formation by lens.
Figure 10 displays the first experimental results using an AOM for image processing.
Figure 10.Experimental results on the output plane: (a) image of the object on the output plane when the AOM is turned off; (b) images of the zeroth-order (left) and the first-order (right) beams. Reprinted from Ref. [8]. Note that the figures presented here are the actual images from the original printed article. The PDF version of the figures provided by the publisher has been smeared.
5. Illustrative Examples
In this section, we illustrate that AOMs can perform some of the optical computing operations such as the important differentiation operations.
5.1. First–order partial derivative
Let us assume that , where is the maximum frequency of the input image, so Eq. (16a) becomes
Assuming the incident beam is of two transverse dimensions, i.e., Eq. (17a) now gives
Note that we can only process the image in one dimension. If we choose the correct value for , such as , we can make . Under this condition, Eq. (20) becomes
Figure 11.(a) Input square object, (b) magnitude spectrum of (a), and (c) intensity of the zeroth-order light.
5.2 Higher–order partial derivative
To obtain higher derivative operations, we can, for example, have two AOMs cascaded. The situation is shown in Fig. 12(a). We use the zeroth-order light output of the first modulator as the input to the second modulator. We then track the zeroth-order light of the second modulator as a final output. Mathematically, the output after the first AOM, from Eq. (20), is
Figure 12.(a) Cascaded AOM system and (b) intensity of the zeroth-order light |ψ0(2)(x′, y′)|2 at the exit of the cascade AOM system illustrating second-order differentiation operation.
Similarly, the zeroth-order light after the second AOM is
Note that if and are designed to be zero, we perform a second-order partial derivative of the incident profile. Figure 12(b) illustrates the result of taking the second-order derivative operation, where the input image is the same as that shown in Fig. 11(a) with parameters , , and in used for the two AOMs.
5.3 Mixed partial derivative
The acousto-optic interaction is confined to two dimensions, i.e., in the plane, as shown in Fig. 6. This limitation restricts its applications to 1D image processing. We can extend the technique to 2D image processing by orienting the second AOM in Fig. 12(a) at an angle with respect to the first AOM. For example, the two AOMs can be aligned orthogonally to each other. If the first AOM is confined in the plane with sound propagating along the direction, the second AOM can be confined in the xy plane with the direction of propagating sound along the direction. Therefore, the zeroth-order light after the second AOM is given by
Figure 13.Intensity of the zeroth-order light |ψ0(2)(x′, y′)|2 at the exit of the cascade AOM system.
Depending on applications, the first derivative gives a maximum at the edge location in image processing, and the second derivative gives a zero at the edge location. The mixed derivative provides corner detection commonly used in computer vision to extract certain kinds of features and infer the contents of an image. In addition, corner detection is often used in image registration and image recognition.
6. State-of-the-Art Considerations
In the previous section, we found that the use of AOMs effectively perform a variety of partial derivatives. In this section, we discuss a couple of the latest considerations that would enhance the capability of using AOM(s) for image processing applications.
6.1 AOMs within a Mach–Zehnder interferometer
We consider two AOMs to be used within a Mach–Zehnder interferometer, as shown in Fig. 14. In principle, the two AOMs can be rotated arbitrarily along the xy plane. Irises 1 and 2 are used to select the different diffracted orders for display. The upper arm and the lower arm of the interferometry can perform different processing, depending on the orientation of each of the AOMs in the arm. The shutter has control if we have processing operations by a single arm or by both arms of the interferometer. Beamsplitter BS2 would then sum the contributions from each arm. For example, by aligning one AOM along the direction on the upper arm of the interferometer and another AOM along the direction on the lower arm, we accomplish the sum of two first derivative operations:
Figure 14.Dual AOMs in a Mach–Zehnder interferometer.
Figure 15(a) shows the original input image. With the shutter being on and AOM1 oriented at the angle of 135° in the second quadrant in the xy plane, we see that the first-order differentiation operation is performed along the 135° angle, as shown in Fig. 15(b). At the angle of 45° in the first quadrant, processing is missed. The physical reason is that sound waves propagate along the 135° angle, and hence the 2D image is only processed along this direction. Now, with the operation realized by Eq. (28), where one AOM is along the direction and the other along the direction, we have isotropic filtering, and a full circle appears, as shown in Fig. 15(c). The configuration in Fig. 14 is quite general in that we can perform anisotropic edge extraction by blocking off one of the arms of the interferometer or perform isotropic edge extraction if the full interferometer is employed.
Figure 15.(a) Input, (b) image processing by a single AOM, and (c) image processing by dual AOMs in a Mach–Zehnder interferometer realizing the computing operation given by Eq. (
6.2 Off-Bragg angle incidence
We consider the angular misalignment of the AOM by letting , where represents the amount of deviation from the exact Bragg angle incidence. We call this angular deviation the tilt angle, . In other words, when , the input image is incident exactly at the Bragg angle. With given above, the zeroth-order transfer function, from Eq. (16a), becomes
The highpass characteristic of the zeroth-order transfer function shown in Figs. 7(a) and 7(c) has become a single-sided notch filter with the center frequency given by Eq. (30). The amount of shift depends on the tilt angle. Figure 16(a) shows the image of a 1D chirp grating , and Fig. 16(b) shows a normalized intensity of the line trace across the red line in Fig. 16(a).
Figure 16.(a) Image of a 1D chirp grating and (b) line trace across the red line in (a).
For , i.e., the tilt angle is away from the exact Bragg angle incident, Fig. 17(a) shows the spectrum of the chirp grating and the shifted zeroth-order transfer function for with and . Figure 17(b) shows the processed chirp grating. Note that the part of the image that has been processed shows a dark and blurry area compared to the rest of unprocessed area. Figure 17(c) shows a line trace across the red line of Fig. 17(b).
Figure 17.(a) Spectrum of the chirp grating and shifted zeroth-order transfer function for Δδ = 0.15, (b) processed chirp grating, and (c) line trace across (b).
Figures 18(a) and 18(c) show the processed chirp grating for and , respectively, and, in Figs. 18(b) and 18(d), we show the line trace across Figs. 18(a) and 18(c), respectively. In general, by comparing Figs. 17(b), 18(a), and 18(c), we observe that the “dark band” moves to the right of the image as we increase the tilt angle.
Figure 18.Processed images for (a), (b) Δδ = 0.2 and (c), (d) Δδ = 0.25.
While single-sided notch filtering has been previously investigated[
7. Concluding Remarks
We have reviewed Bragg processing using AOMs for real-time programmable spatial filtering. In the review, we have discussed the fundamentals of acousto-optics, which is followed by the summary of the multiple plane-wave theory. From the theory, we have discussed the concept of the acousto-optic transfer function, leading to the applications of spatial filtering. We have then given some illustrative examples on how to implement some of the optical computing operations. Finally, we have mentioned a couple of state-of-the-art considerations that would enhance the processing capabilities of Bragg processing. The first consideration is the use of AOMs within a Mach–Zehnder interferometer to perform the summation of two partial differentiation operations. Conceptually, the Mach–Zehnder interferometer system is elegant. However, practical implementation of the idea is quite challenging, as we need to carefully align the two images for summation. In the second consideration, we have looked at the situation when the incident angle is not exactly at the Bragg angle, thereby introducing the tilt angle. The tilt angle gives rise to single-sided notch filtering or half-plane filtering[
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Yaping Zhang, Houxin Fan, Ting-Chung Poon, "Optical image processing using acousto-optic modulators as programmable volume holograms: a review [Invited]," Chin. Opt. Lett. 20, 021101 (2022)
Category: Imaging Systems and Image Processing
Received: Aug. 14, 2021
Accepted: Nov. 10, 2021
Published Online: Dec. 13, 2021
The Author Email: Yaping Zhang (yaping.zhang@gmail.com)