Linear dynamic range enhancement in a CMOS imager

A CMOS imager with increased linear dynamic range but without degradation in noise, responsivity, linearity, fixed-pattern noise, or photometric calibration comprises a linear calibrated dual gain pixel in which the gain is reduced after a pre-defined threshold level by switching in an additional capacitance. The pixel may include a novel on-pixel latch circuit that is used to switch in the additional capacitance

Super resolution and dynamic range enhancement of image sequences

Camera producers try to increase the spatial resolution of a camera by reducing size of sites on sensor array. However, shot noise causes the signal to noise ratio drop as sensor sites get smaller. This fact motivates resolution enhancement to be performed through software. Super resolution (SR) image reconstruction aims to combine degraded images of a scene in order to form an image which has higher resolution than all observations. There is a demand for high resolution images in biomedical imaging, surveillance, aerial/satellite imaging and high-definition TV (HDTV) technology. Although extensive research has been conducted in SR, attention has not been given to increase the resolution of images under illumination changes. In this study, a unique framework is proposed to increase the spatial resolution and dynamic range of a video sequence using Bayesian and Projection onto Convex Sets (POCS) methods. Incorporating camera response function estimation into image reconstruction allows dynamic range enhancement along with spatial resolution improvement. Photometrically varying input images complicate process of projecting observations onto common grid by violating brightness constancy. A contrast invariant feature transform is proposed in this thesis to register input images with high illumination variation. Proposed algorithm increases the repeatability rate of detected features among frames of a video. Repeatability rate is increased by computing the autocorrelation matrix using the gradients of contrast stretched input images. Presented contrast invariant feature detection improves repeatability rate of Harris corner detector around %25 on average. Joint multi-frame demosaicking and resolution enhancement is also investigated in this thesis. Color constancy constraint set is devised and incorporated into POCS framework for increasing resolution of color-filter array sampled images. Proposed method provides fewer demosaicking artifacts compared to existing POCS method and a higher visual quality in final image

Dynamic Range Enhancement of High-Speed Electrical Signal Data via Non-Linear Compression

Systems and methods for high-speed compression of dynamic electrical signal waveforms to extend the measuring capabilities of conventional measuring devices such as oscilloscopes and high-speed data acquisition systems are discussed. Transfer function components and algorithmic transfer functions can be used to accurately measure signals that are within the frequency bandwidth but beyond the voltage range and voltage resolution capabilities of the measuring device

Dynamic Range Enhancement in Swept-Source Optical Coherence Tomography

The imaging penetration depth of an optical coherence tomography (OCT) system is limited by the dynamic range of the system. In a common case that signals exceed the dynamic range of a Fourier domain OCT (FDOCT) system, saturation artifacts degrade the image quality. In this chapter, we demonstrate some new cost-effective techniques to improve the dynamic range of a swept-source OCT (SSOCT) system. For example, one method is based on a dual-channel detection technique to enhance the dynamic range by reconstructing the saturated signals due to strong reflection of the sample surface. Another method utilizes a tunable high-pass filter to compensate the attenuation of light signal in deep tissue. It was demonstrated that these techniques can improve the dynamic range of an SSOCT system by more than 10 dB with a low bit-depth analog-to-digital converter