Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form

What is to our knowledge a new scene-based algorithm for nonuniformity correction in infrared focal-plane array sensors has been developed. The technique is based on the inverse covariance form of the Kalman filter (KF), which has been reported previously and used in estimating the gain and bias of each detector in the array from scene data. The gain and the bias of each detector in the focal-plane array are assumed constant within a given sequence of frames, corresponding to a certain time and operational conditions, but they are allowed to randomly drift from one sequence to another following a discrete-time Gauss-Markov process. The inverse covariance form filter estimates the gain and the bias of each detector in the focal-plane array and optimally updates them as they drift in time. The estimation is performed with considerably higher computational efficiency than the equivalent KF. The ability of the algorithm in compensating for fixed-pattern noise in infrared imagery and in reducing the computational complexity is demonstrated by use of both simulated and real data

Non Uniformity Correction Algorithm for Large Format Shortwave Infrared Imaging Array

Preprocessing is an important field of research in optoelectronics where raw images captured from infrared (IR) imaging array are tuned by applying various algorithms. Common image preprocessing in infrared imaging are: i) Non-Uniformity Correction (NUC), ii) Bad Pixel Replacement (BPR). Non-Uniformity (NU) arises because of each individual pixel in large format detector array has unequal photo-response from its adjacent pixel even if the both pixels are illuminated by equal luminance. This NU can be corrected by applying different NU Correction algorithms. In this paper, Two Pont NUC algorithm is designed in LabVIEW tool to reduce spatial noise or Fixed Pattern Noise. This algorithm has been tested on raw data acquired from Shortwave Infrared (SWIR) linear detector which has 6000 pixel elements. The result shows that pixel’s non-uniformity reduces after applying two-point correction algorithm. DOI: 10.17762/ijritcc2321-8169.15053

Interferometric Optical Readout System for a MEMS Infrared Imaging Detector

MEMS technology has led to the development of new uncooled infrared imaging detectors. One type of these MEMS detectors consist of arrays of bi-metallic photomechanical pixels that tilt as a function of temperature associated with infrared radiation from the scene. The main advantage of these detectors is the optical readout system that measures the tilt of the beams based on the intensity of the reflected light. This removes the need for electronic readout at each of the sensing elements and reduces the fabrication cost and complexity of sensor design, as well as eliminates the electronic noise at the detector. The optical readout accuracy is sensitive to the uniformity of individual pixels on the array. The hypothesis of the present research is that direct measurements of the height change corresponding to tilt through holographic interferometry will reduce the need for high pixel uniformity. Measurements of displacements for a vacuum packaged detector with nominal responsivity of 2.4nm/K are made with a Linnik interferometer employing the four phase step technique. The interferometer can measure real-time, full-field height variations across the array. In double-exposure mode, the current height map is subtracted from a reference image so that the change in deflection is measured. A software algorithm locates each mirror on the array, extracts the measured deflection at the tip of a mirror, and uses that measurement to form a pixel of a thermogram in real-time. A blackbody target projector with temperature controllable to 0.001K is used to test the thermal resolution of the imaging system. The achieved minimum temperature resolution is better than 0.25K. The double exposure technique removes mirror non-uniformity as a source of noise. A lower than nominal measured responsivity of around 1.5nm/K combined with noise from the measurements made with the interferometric optical readout system limit the potential minimum temperature resolution. Improvements need to be made both in the holographic setup and in the MEMS detector to achieve the target temperature resolution of 0.10K

Real Time Non uniformity Correction Algorithm and Implementation in Reconfigurable Architecture for Infra red Imaging Systems

 In modern electro-optical systems, infra-red (IR) imaging system is an essential sensor used for day and night surveillance. In recent years, advancements in IR sensor technology resulted the detectors having smaller pitch, better thermal sensitivity with large format like 640.512, 1024.768 and 1280.1024. Large format IR detectors enables realisation of high resolution compact thermal imager having wide field-of view coverage. However, the performance of these infrared imaging systems gets limited by non uniformity produced by sensing element, which is temporal in nature and present in spatial domain. This non uniformity results the fixed pattern noise, which arises due to variation in gain and offset components of the each pixel of the sensor even when exposed to a uniform scene. This fixed pattern noise limits the temperature resolution capability of the IR imaging system thereby causing the degradation in system performance. Therefore, it is necessary to correct the non-uniformities in real time. In this paper, non uniformity correction algorithm and its implementation in reconfigurable architectures have been presented and results on real time data have been described

Algorithms for the enhancement of dynamic range and colour constancy of digital images & video

One of the main objectives in digital imaging is to mimic the capabilities of the human eye, and perhaps, go beyond in certain aspects. However, the human visual system is so versatile, complex, and only partially understood that no up-to-date imaging technology has been able to accurately reproduce the capabilities of the it. The extraordinary capabilities of the human eye have become a crucial shortcoming in digital imaging, since digital photography, video recording, and computer vision applications have continued to demand more realistic and accurate imaging reproduction and analytic capabilities. Over decades, researchers have tried to solve the colour constancy problem, as well as extending the dynamic range of digital imaging devices by proposing a number of algorithms and instrumentation approaches. Nevertheless, no unique solution has been identified; this is partially due to the wide range of computer vision applications that require colour constancy and high dynamic range imaging, and the complexity of the human visual system to achieve effective colour constancy and dynamic range capabilities. The aim of the research presented in this thesis is to enhance the overall image quality within an image signal processor of digital cameras by achieving colour constancy and extending dynamic range capabilities. This is achieved by developing a set of advanced image-processing algorithms that are robust to a number of practical challenges and feasible to be implemented within an image signal processor used in consumer electronics imaging devises. The experiments conducted in this research show that the proposed algorithms supersede state-of-the-art methods in the fields of dynamic range and colour constancy. Moreover, this unique set of image processing algorithms show that if they are used within an image signal processor, they enable digital camera devices to mimic the human visual system s dynamic range and colour constancy capabilities; the ultimate goal of any state-of-the-art technique, or commercial imaging device

A Method to Achieve High Dynamic Range in a CMOS Image Sensor Using Interleaved Row Readout

©2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/We present a readout scheme for CMOS image sensors that can be used to achieve arbitrarily high dynamic range (HDR) in principle. The linear full well capacity (LFWC) in high signal regions was extended 50 times from 20 to 984 ke − via an interlaced row-wise readout order, while the noise floor remained unchanged in low signal regions, resulting in a 34-dB increase in DR. The peak signal-to-noise ratio (PSNR) is increased in a continuous fashion from 43 to 60 dB. This was achieved by summing user-selected rows that were read out multiple times. Centroiding uncertainties were lowered when template-fitting a projected pattern, compared to the standard readout scheme. Example applications are aimed at scientific imaging due to the linearity and PSNR increase.Peer reviewe

Simulation and Analysis of Uncooled Microbolometer for Serial Readout Architecture

A detailed thermal behavior and theoretical analysis of uncooled resistive microbolometer is presented along with the proposed thermal imager simulator. An accurate model of a thermal detector is required to design a readout circuit that can compensate for the noise due to process variability and self-heating. This paper presents a realistic simulation model of microbolometer that addresses the fixed pattern noise, Johnson noise, and self-heating. Different simulations were performed to study the impact of infrared power and bias power on the performance of microbolometers. The microbolometers were biased with different bias currents along with different thermal parameters of the reference microbolometer to analyze the impact of self-heating on the thermal image. The proposed thermal imager simulator is used as a tool to visually analyze the impact of noise on the quality of a thermal image. This simulator not only helps in compensating the noise prior to the implementation in Analog Design Environment, but also can be used as a platform to explore different readout architectures. In this work, serial readout architecture was simulated with a row of blind microbolometers that served as a reference. Moreover, the algorithm for the proposed thermal imager simulator is presented

Study of scene-based nonuniformity compensation in infrared focal plane arrays

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 77-79).by Laura S. Juliano.M.Eng

CMOS Approach to Compressed-domain Image Acquisition

A hardware implementation of a real-time compressed-domain image acquisition system is demonstrated. The system performs front-end computational imaging, whereby the inner product between an image and an arbitrarily-specified mask is implemented in silicon. The acquisition system is based on an intelligent readout integrated circuit (iROIC) that is capable of providing independent bias voltages to individual detectors, which enables implementation of spatial multiplication with any prescribed mask through a bias-controlled response-modulation mechanism. The modulated pixels are summed up in the image grabber to generate the compressed samples, namely aperture-coded coefficients, of an image. A rigorous bias-selection algorithm is presented to the readout circuit, which exploits the bias-dependent nature of the imager’s responsivity. Proven functionality of the hardware in transform coding compressed image acquisition, silicon-level compressive sampling, in pixel nonuniformity correction and hardware-level implementation of region-based enhancement is demonstrated