Essex has developed the ImSyn processor, a sophisticated hybrid of optics and electronics. ImSyn calculates a discrete Fourier transform. The current production ImSyn is optimized for synthetic aperture radar processing, but has been used to process MRI, acoustic tomography, and synthetic aperture microscope data. The key feature of the production ImSyn is the ability to calculate images from non- rectilinearly gridded data. This data cannot be transformed with the FFT algorithm without interpolation or regridding. An alternative version of ImSyn is being developed for correlation applications. The correlator will be optimized for speed in performing rectilinear transforms.
The accuracy of digital and optical Hough transform (HT) processors is analyzed. New correction techniques to achieve improved accuracy are addressed. A new output format optical HT system using computer generated holograms (CGHs) is described and analyzed and its accuracy is found to be superior to that of digital HT processors. Its speed is much faster; the CGH space bandwidth product (SBWP) requirements are much less than for other methods; CGH error sources are addressed; and simple multiple binary exposure CGH fabrication is found to be sufficient.
Recently, the theory of the synthetic aperture microscope (SAM) was presented. A SAM is a three dimensional imaging system that makes use of the principles of synthetic aperture radar to obtain a high resolution, complex valued image at a large working distance. Theoretically, a SAM can achieve resolution of approximately (lambda) /4 in all three dimensions. A typical system consists of a holographic sensor head and a reconstruction processor. This implementation will use the Essex ImSyn<SUP>TM</SUP> optoelectronic discrete Fourier transform (DFT) processor to reconstruct the synthetic aperture image. Over the past year Essex has constructed a breadboard of the system and obtained initial results consisting of a single digital hologram and its computer-reconstructed image. The ability to collect complex valued image data opens the door to image processing and pattern recognition algorithms that are not applicable to intensity images, such as holographic interferometry for mapping strain fields. Applications include industrial inspection, robotics, and biological imaging.
This paper presents optical laboratory data on a number of new optical filter systems for: rank-order morphological filtering, morphological ternary phase amplitude filters, morphological hit-miss detection filters, Gabor detection filters and distortion-invariant detection filters. All filters and processing are performed on the same optical correlator architecture. This provides a general purpose multi-functional optical image processor for general scene analysis, capable of low-level vision, detection, and image enhancement operations.
We discuss our cascaded correlator-based optical numeric processor and its projected performance (our goal is a numeric processor and not a general-purpose optical processor). We use symbolic substitution (for parallelism on long words and arrays of words), the modified signed-digit number representation (for speed, i.e. reduced carries), and a new encoding and substitution architecture to improve performance.
We report on two new computer generated hologram (CGH) elements for optical processing. They are a one-to-many optical interconnection element (that allows analog weights, high efficiency, and is not restricted to a regularly spaced grid) and an element to provide separate 1-D collimation of the laser diodes in an array (with high efficiency). Error diffusion encoding and multilevel phase CGHs are used to achieve high accuracy and high efficiency. Simulations are used to show the advantage of error diffusion (ED) encoding. Optical laboratory data are included to show the feasibility of the elements and the validity of our simulator.