We present a high-speed CMOS active pixel sensor (APS) image sensor with focal plane histogram computation. The 128×128 4-transistor active pixel sensor array produces cumulative intensity histograms, at the focal-plane, with speeds in excess of 10,000 frames per second for low-latency, realtime control applications without the need for pixel digitization of external processing. In addition, an on-chip 10-bit column parallel analog-to-digital converter with a read noise of 0.6LSB and negligible fixed pattern noise facilitates conventional imaging operations and data acquisition. Each pixel occupies 19.5μm×19.5μm with a fill factor of 43%. Power consumption is 1.5mW during imaging mode and 4.6mW in high-speed histogram mode. Applications include real-time adaptive optics control for laser communications.

A dynamic procedure for selective information fusion from multiple image frames is derived from robust error estimation theory. The fusion rate is driven by the anisotropic gain function, defined to be the difference between the Gaussian smoothed-edge maps of a given input frame and of an evolving synthetic output frame. The gain function achieves both selection and rapid fusion of relatively sharper features from each input frame compared to the synthetic frame. Effective applications are demonstrated for image sharpening in imaging through atmospheric turbulence, for multispectral fusion of the RGB spectral components of a scene, for removal of blurred visual obstructions from in front of a distant focused scene, and for high-resolution two-dimensional display of three-dimensional objects in microscopy.

A multiframe selective information fusion technique, based on a time evolution equation with anisotropic gain, is applied to the spatio-temporal processing of a video captured from behind visual obstructions, achieving as final output a synthetic frame of unobstructed field of view, as though 'looking straight through the woods' at a distant scene.

In this paper we consider an application of a WTA dynamics developed from artificial neural networks to the concept of a large array of optoelectronic feedback circuits. The merging of the winner take all (WTA) dynamics with optical implementation could potentially provide improved systems for high resolution image processing. The time required for digital image processing grows dramatically with the increase in image frame resolution, which complicates segmentation, detection, and tracking of objects within an image. This approach could address the challenges found in high resolution image processing. Examples of simulation results based on this approach are presented.

Phase distortion in wavefront propagation is one of the key problems in optical imaging and laser optics applications. We present a hybrid VLSI and optical system for real-time adaptive phase distortion compensation. The system operates "model-free", independent of the specifics of the distorting optical medium and the compensation control elements. Our VLSI system implements stochastic parallel perturbative gradient descent/ascent so that we achieve fast optimization of the chosen performance metric to achieve real-time compensation. We include experimental results of the hybrid VLSI-optical system demonstrating successful operation for a laser-beam focusing/defocusing task.