A 148dB focal-plane tone-mapping QCIF imager

http://digital.csic.es/handle/10261/84304This paper presents a QCIF HDR imager where visual information is simultaneously captured and adaptively compressed by an in-pixel tone-mapping scheme [1]. The tone mapping curve (TMC) is calculated from the histogram of an auxiliary previous image, which serves as a probability indicator of the distribution of illuminations within the current frame. The chip maps 148dB scenes onto 7-bit/pixel coding, containing illuminations from 2.2mlux (SNR10) to 55.33klux -with extreme values captured at 8s and 2.34µs, respectively. Pixels use an Nwell-Psubstrate photodiode and autozeroing for establishing the reset voltage. Measured sensitivity is 5.79 V over lux·s. Dark current effects in the final image are attenuated by an automatic programming of the DAC levels. The chip has been fabricated in the 0.35µm OPTO technology from AMS

Exploring information retrieval using image sparse representations:from circuit designs and acquisition processes to specific reconstruction algorithms

New advances in the field of image sensors (especially in CMOS technology) tend to question the conventional methods used to acquire the image. Compressive Sensing (CS) plays a major role in this, especially to unclog the Analog to Digital Converters which are generally representing the bottleneck of this type of sensors. In addition, CS eliminates traditional compression processing stages that are performed by embedded digital signal processors dedicated to this purpose. The interest is twofold because it allows both to consistently reduce the amount of data to be converted but also to suppress digital processing performed out of the sensor chip. For the moment, regarding the use of CS in image sensors, the main route of exploration as well as the intended applications aims at reducing power consumption related to these components (i.e. ADC & DSP represent 99% of the total power consumption). More broadly, the paradigm of CS allows to question or at least to extend the Nyquist-Shannon sampling theory. This thesis shows developments in the field of image sensors demonstrating that is possible to consider alternative applications linked to CS. Indeed, advances are presented in the fields of hyperspectral imaging, super-resolution, high dynamic range, high speed and non-uniform sampling. In particular, three research axes have been deepened, aiming to design proper architectures and acquisition processes with their associated reconstruction techniques taking advantage of image sparse representations. How the on-chip implementation of Compressed Sensing can relax sensor constraints, improving the acquisition characteristics (speed, dynamic range, power consumption) ? How CS can be combined with simple analysis to provide useful image features for high level applications (adding semantic information) and improve the reconstructed image quality at a certain compression ratio ? Finally, how CS can improve physical limitations (i.e. spectral sensitivity and pixel pitch) of imaging systems without a major impact neither on the sensing strategy nor on the optical elements involved ? A CMOS image sensor has been developed and manufactured during this Ph.D. to validate concepts such as the High Dynamic Range - CS. A new design approach was employed resulting in innovative solutions for pixels addressing and conversion to perform specific acquisition in a compressed mode. On the other hand, the principle of adaptive CS combined with the non-uniform sampling has been developed. Possible implementations of this type of acquisition are proposed. Finally, preliminary works are exhibited on the use of Liquid Crystal Devices to allow hyperspectral imaging combined with spatial super-resolution. The conclusion of this study can be summarized as follows: CS must now be considered as a toolbox for defining more easily compromises between the different characteristics of the sensors: integration time, converters speed, dynamic range, resolution and digital processing resources. However, if CS relaxes some material constraints at the sensor level, it is possible that the collected data are difficult to interpret and process at the decoder side, involving massive computational resources compared to so-called conventional techniques. The application field is wide, implying that for a targeted application, an accurate characterization of the constraints concerning both the sensor (encoder), but also the decoder need to be defined

A 148dB focal-plane tone-mapping QCIF imager

Comunicación presentada al "ISCAS 2012" celebrado en Seúl (Corea del Sur) del 20 al 23 de Mayo del 2012.This paper presents a QCIF HDR imager where visual information is simultaneously captured and adaptively compressed by an in-pixel tone-mapping scheme [1]. The tone mapping curve (TMC) is calculated from the histogram of an auxiliary previous image, which serves as a probability indicator of the distribution of illuminations within the current frame. The chip maps 148dB scenes onto 7-bit/pixel coding, containing illuminations from 2.2mlux (SNR10) to 55.33klux -with extreme values captured at 8s and 2.34µs, respectively. Pixels use an Nwell-Psubstrate photodiode and autozeroing for establishing the reset voltage. Measured sensitivity is 5.79 V over lux·s. Dark current effects in the final image are attenuated by an automatic programming of the DAC levels. The chip has been fabricated in the 0.35µm OPTO technology from AMS.This work is partially funded by TEC2009-11812, CENIT ADAPTA, ONR Grant N000141110312, FEDER 2007-2013, WiVisNet and IMPACTO.Peer Reviewe