First functionality tests of a 64 x 64 pixel DSSC sensor module connected to the complete ladder readout

The European X-ray Free Electron Laser (XFEL.EU) will provide every 0.1 s a train of 2700 spatially coherent ultrashort X-ray pulses at 4.5 MHz repetition rate. The Small Quantum Systems (SQS) instrument and the Spectroscopy and Coherent Scattering instrument (SCS) operate with soft X-rays between 0.5 keV - 6keV. The DEPFET Sensor with Signal Compression (DSSC) detector is being developed to meet the requirements set by these two XFEL.EU instruments. The DSSC imager is a 1 mega-pixel camera able to store up to 800 single-pulse images per train. The so-called ladder is the basic unit of the DSSC detector. It is the single unit out of sixteen identical-units composing the DSSC-megapixel camera, containing all representative electronic components of the full-size system and allows testing the full electronic chain. Each DSSC ladder has a focal plane sensor with 128 x 512 pixels. The read-out ASIC provides full-parallel readout of the sensor pixels. Every read-out channel contains an amplifier and an analog filter, an up-to 9 bit ADC and the digital memory. The ASIC amplifier have a double front-end to allow one to use either DEPFET sensors or Mini-SDD sensors. In the first case, the signal compression is a characteristic intrinsic of the sensor; in the second case, the compression is implemented at the first amplification stage. The goal of signal compression is to meet the requirement of single-photon detection capability and wide dynamic range. We present the first results of measurements obtained using a 64 x 64 pixel DEPFET sensor attached to the full final electronic and data-acquisition chain.Comment: Preprint proceeding for IWORID 2016, 18th International Workshop on Radiation Imaging Detectors, 3rd-7th July 2016, Barcelona, Spai

A versatile sensor interface for programmable vision systems-on-chip

This paper describes an optical sensor interface designed for a programmable mixed-signal vision chip. This chip has been designed and manufactured in a standard 0.35μm n-well CMOS technology with one poly layer and five metal layers. It contains a digital shell for control and data interchange, and a central array of 128 × 128 identical cells, each cell corresponding to a pixel. Die size is 11.885 × 12.230mm2 and cell size is 75.7μm × 73.3μm. Each cell contains 198 transistors dedicated to functions like processing, storage, and sensing. The system is oriented to real-time, single-chip image acquisition and processing. Since each pixel performs the basic functions of sensing, processing and storage, data transferences are fully parallel (image-wide). The programmability of the processing functions enables the realization of complex image processing functions based on the sequential application of simpler operations. This paper provides a general overview of the system architecture and functionality, with special emphasis on the optical interface.European Commission IST-1999-19007Office of Naval Research (USA) N00014021088

High resolution, high frame rate video technology development plan and the near-term system conceptual design

The objective of the High Resolution, High Frame Rate Video Technology (HHVT) development effort is to provide technology advancements to remove constraints on the amount of high speed, detailed optical data recorded and transmitted for microgravity science and application experiments. These advancements will enable the development of video systems capable of high resolution, high frame rate video data recording, processing, and transmission. Techniques such as multichannel image scan, video parameter tradeoff, and the use of dual recording media were identified as methods of making the most efficient use of the near-term technology

Color-decoupled photo response non-uniformity for digital image forensics

The last few years have seen the use of photo response non-uniformity noise (PRNU), a unique fingerprint of imaging sensors, in various digital forensic applications such as source device identification, content integrity verification and authentication. However, the use of a colour filter array for capturing only one of the three colour components per pixel introduces colour interpolation noise, while the existing methods for extracting PRNU provide no effective means for addressing this issue. Because the artificial colours obtained through the colour interpolation process is not directly acquired from the scene by physical hardware, we expect that the PRNU extracted from the physical components, which are free from interpolation noise, should be more reliable than that from the artificial channels, which carry interpolation noise. Based on this assumption we propose a Couple-Decoupled PRNU (CD-PRNU) extraction method, which first decomposes each colour channel into 4 sub-images and then extracts the PRNU noise from each sub-image. The PRNU noise patterns of the sub-images are then assembled to get the CD-PRNU. This new method can prevent the interpolation noise from propagating into the physical components, thus improving the accuracy of device identification and image content integrity verification

CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression

Lossy image compression algorithms are pervasively used to reduce the size of images transmitted over the web and recorded on data storage media. However, we pay for their high compression rate with visual artifacts degrading the user experience. Deep convolutional neural networks have become a widespread tool to address high-level computer vision tasks very successfully. Recently, they have found their way into the areas of low-level computer vision and image processing to solve regression problems mostly with relatively shallow networks. We present a novel 12-layer deep convolutional network for image compression artifact suppression with hierarchical skip connections and a multi-scale loss function. We achieve a boost of up to 1.79 dB in PSNR over ordinary JPEG and an improvement of up to 0.36 dB over the best previous ConvNet result. We show that a network trained for a specific quality factor (QF) is resilient to the QF used to compress the input image - a single network trained for QF 60 provides a PSNR gain of more than 1.5 dB over the wide QF range from 40 to 76.Comment: 8 page

Random on-board pixel sampling (ROPS) X-ray Camera

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.Comment: 9 pages, 6 figures, Presented in 19th iWoRI

Sun Sensor Based on a Luminance Spiking Pixel Array

We present a novel sun sensor concept. It is the very first sun sensor built with an address event representation spiking pixel matrix. Its pixels spike with a frequency proportional to illumination. It offers remarkable advantages over conventional digital sun sensors based on active pixel sensor (APS) pixels. Its output data flow is quite reduced. It is possible to resolve the sun position just receiving one single event operating in time-to-first-spike mode. It operates with a latency in the order of milliseconds. It has higher dynamic range than APS image sensors (higher than 100 dB). A custom algorithm to compute the centroid of the illuminated pixels is presented. Experimental results are provided.Universidad de Cádiz PR2016-072Ministerio de Economía y Competitividad TEC2015-66878-C3-1-RJunta de Andalucía TIC 2012- 2338Office of Naval Research (USA) N00014141035