Entwurf und Modellierung von Multikanal-CMOS-Farbsensoren

Color image acquisition and image processing have become a key in modern data application. In order to provide high quality images, the field of accurate acquisition is most important in respect to all further processing steps. But a whole variety of current image sensors possess incorrect color rendition due to insufficient accuracy of optical sensor parameters. This is detrimental especially for color sensors, because in these cases specific color information will be incorrectly acquired. Further, traditional color correction methods do not use information on the specific sensor spectral sensitivity, thus losing substantial information for color correction. The problem is investigated by introducing an algorithmic correction method which is capable of correcting dysfunctional sensor properties. The correction method is based on an enhancement of the CIE color perception model. According to this, color perception is modelled as a special integral transformation, where the spectral sensitivities of the photo receptors represent the base functions of the transformation. It is shown that different sets of photo receptors show the same perception, when their spectral sensitivities are linear dependent. On the other hand, photo receptors with no linear dependency show different perception and there is no analytical transformation between them. Thus, a perfect color correction is only possible if photo sensor and human perception show a linear dependency. In case of dissentient sensor characteristics, the correction method of spectral reconstruction can determine an optimal solution using a least square error optimization. Applying sensors with more than three color channels, this correction method can show improved results due to a better approximation. For implementation of the color correction scheme, different sensor designs have been developed. Compared with currently dominating CCD (Charge Coupled Device) technology, a realisation of image sensors based on CMOS technology show a high potential. CMOS technology allow the integration of the sensor together with control and image processing on the same chip, thus enabling the design of sensor systems at low cost. But modern sub-100nm technologies show also substantial disadvantages, such as increased leakage currents. Special circuit designs have been developed to especially reduce the influence of leakage currents. For application of the color correction method, new multi-channel photo sensors using vertically stacked photo diodes have been developed. The work further shows different concepts of multi-channel sensors capable of high quality color rendition. This approach is demonstrated on several new CMOS sensor designs with examples, implemented in a 90nm Infineon technology

VLSI Implementation of a 2.8 Gevent/s Packet-Based AER Interface with Routing and Event Sorting Functionality

State-of-the-art large-scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an field programmable gate arrays (FPGA)-maintained environment. The ICs implement configurable axonal delays, as required for certain types of dynamic processing or for emulating spike-based learning among distant cortical areas. Measurements are presented which show the efficacy of these delays in influencing behavior of neuromorphic benchmarks. The specialized, dedicated address-event-representation communication in most current systems requires separate, low-bandwidth configuration channels. In contrast, the configuration of the waferscale neuromorphic system is also handled by the digital packet-based pulse channel, which transmits configuration data at the full bandwidth otherwise used for pulse transmission. The overall so-called pulse communication subgroup (ICs and FPGA) delivers a factor 25–50 more event transmission rate than other current neuromorphic communication infrastructures

Entwurf und Modellierung von Multikanal-CMOS-Farbsensoren

Color image acquisition and image processing have become a key in modern data application. In order to provide high quality images, the field of accurate acquisition is most important in respect to all further processing steps. But a whole variety of current image sensors possess incorrect color rendition due to insufficient accuracy of optical sensor parameters. This is detrimental especially for color sensors, because in these cases specific color information will be incorrectly acquired. Further, traditional color correction methods do not use information on the specific sensor spectral sensitivity, thus losing substantial information for color correction. The problem is investigated by introducing an algorithmic correction method which is capable of correcting dysfunctional sensor properties. The correction method is based on an enhancement of the CIE color perception model. According to this, color perception is modelled as a special integral transformation, where the spectral sensitivities of the photo receptors represent the base functions of the transformation. It is shown that different sets of photo receptors show the same perception, when their spectral sensitivities are linear dependent. On the other hand, photo receptors with no linear dependency show different perception and there is no analytical transformation between them. Thus, a perfect color correction is only possible if photo sensor and human perception show a linear dependency. In case of dissentient sensor characteristics, the correction method of spectral reconstruction can determine an optimal solution using a least square error optimization. Applying sensors with more than three color channels, this correction method can show improved results due to a better approximation. For implementation of the color correction scheme, different sensor designs have been developed. Compared with currently dominating CCD (Charge Coupled Device) technology, a realisation of image sensors based on CMOS technology show a high potential. CMOS technology allow the integration of the sensor together with control and image processing on the same chip, thus enabling the design of sensor systems at low cost. But modern sub-100nm technologies show also substantial disadvantages, such as increased leakage currents. Special circuit designs have been developed to especially reduce the influence of leakage currents. For application of the color correction method, new multi-channel photo sensors using vertically stacked photo diodes have been developed. The work further shows different concepts of multi-channel sensors capable of high quality color rendition. This approach is demonstrated on several new CMOS sensor designs with examples, implemented in a 90nm Infineon technology

Entwurf und Modellierung von Multikanal-CMOS-Farbsensoren

Color image acquisition and image processing have become a key in modern data application. In order to provide high quality images, the field of accurate acquisition is most important in respect to all further processing steps. But a whole variety of current image sensors possess incorrect color rendition due to insufficient accuracy of optical sensor parameters. This is detrimental especially for color sensors, because in these cases specific color information will be incorrectly acquired. Further, traditional color correction methods do not use information on the specific sensor spectral sensitivity, thus losing substantial information for color correction. The problem is investigated by introducing an algorithmic correction method which is capable of correcting dysfunctional sensor properties. The correction method is based on an enhancement of the CIE color perception model. According to this, color perception is modelled as a special integral transformation, where the spectral sensitivities of the photo receptors represent the base functions of the transformation. It is shown that different sets of photo receptors show the same perception, when their spectral sensitivities are linear dependent. On the other hand, photo receptors with no linear dependency show different perception and there is no analytical transformation between them. Thus, a perfect color correction is only possible if photo sensor and human perception show a linear dependency. In case of dissentient sensor characteristics, the correction method of spectral reconstruction can determine an optimal solution using a least square error optimization. Applying sensors with more than three color channels, this correction method can show improved results due to a better approximation. For implementation of the color correction scheme, different sensor designs have been developed. Compared with currently dominating CCD (Charge Coupled Device) technology, a realisation of image sensors based on CMOS technology show a high potential. CMOS technology allow the integration of the sensor together with control and image processing on the same chip, thus enabling the design of sensor systems at low cost. But modern sub-100nm technologies show also substantial disadvantages, such as increased leakage currents. Special circuit designs have been developed to especially reduce the influence of leakage currents. For application of the color correction method, new multi-channel photo sensors using vertically stacked photo diodes have been developed. The work further shows different concepts of multi-channel sensors capable of high quality color rendition. This approach is demonstrated on several new CMOS sensor designs with examples, implemented in a 90nm Infineon technology