Hardware-based smart camera for recovering high dynamic range video from multiple exposures

International audienceIn many applications such as video surveillance or defect detection, the perception of information related to a scene is limited in areas with strong contrasts. The high dynamic range (HDR) capture technique can deal with these limitations. The proposed method has the advantage of automatically selecting multiple exposure times to make outputs more visible than fixed exposure ones. A real-time hardware implementation of the HDR technique that shows more details both in dark and bright areas of a scene is an important line of research. For this purpose, we built a dedicated smart camera that performs both capturing and HDR video processing from three exposures. What is new in our work is shown through the following points: HDR video capture through multiple exposure control, HDR memory management, HDR frame generation, and rep- resentation under a hardware context. Our camera achieves a real-time HDR video output at 60 fps at 1.3 mega- pixels and demonstrates the efficiency of our technique through an experimental result. Applications of this HDR smart camera include the movie industry, the mass-consumer market, military, automotive industry, and sur- veillanc

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

International audienceMultispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

HDR-ARtiSt: A 1280x1024-pixel Adaptive Real-time Smart camera for High Dynamic Range video

International audienceStandard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight.The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex 6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 × 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture from the sensor with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams

High Dynamic Range Adaptive Real-time Smart Camera: an overview of the HDR-ARTiST project

International audienceStandard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor

High Dynamic Range Spectral Imaging Pipeline For Multispectral Filter Array Cameras

Spectral filter arrays imaging exhibits a strong similarity with color filter arrays. This permits us to embed this technology in practical vision systems with little adaptation of the existing solutions. In this communication, we define an imaging pipeline that permits high dynamic range (HDR)-spectral imaging, which is extended from color filter arrays. We propose an implementation of this pipeline on a prototype sensor and evaluate the quality of our implementation results on real data with objective metrics and visual examples. We demonstrate that we reduce noise, and, in particular we solve the problem of noise generated by the lack o

Nouvelle génération de systèmes de vision temps réel à grande dynamique

Cette thèse s intègre dans le cadre du projet européen EUREKA "High Dynamic Range - Low NoiseCMOS imagers", qui a pour but de développer de nouvelles approches de fabrication de capteursd images CMOS à haute performance. L objectif de la thèse est la conception d un système de visiontemps réel à grande gamme dynamique (HDR). L axe principal sera la reconstruction, en temps réelet à la cadence du capteur (60 images/sec), d une vidéo à grande dynamique sur une architecturede calcul embarquée.La plupart des capteurs actuels produisent une image numérique qui n est pas capable de reproduireles vraies échelles d intensités lumineuses du monde réel. De la même manière, les écrans, impri-mantes et afficheurs courants ne permettent pas la restitution effective d une gamme tonale étendue.L approche envisagée dans cette thèse est la capture multiple d images acquises avec des tempsd exposition différents permettant de palier les limites des dispositifs actuels.Afin de concevoir un système capable de s adapter temporellement aux conditions lumineuses,l étude d algorithmes dédiés à la grande dynamique, tels que les techniques d auto exposition, dereproduction de tons, en passant par la génération de cartes de radiances est réalisée. Le nouveausystème matériel de type "smart caméra" est capable de capturer, générer et restituer du contenu àgrande dynamique dans un contexte de parallélisation et de traitement des flux vidéos en temps réelThis thesis is a part of the EUREKA European project called "High Dynamic Range - Low NoiseCMOS imagers", which developped new approaches to design high performance CMOS sensors.The purpose of this thesis is to design a real-time high dynamic range (HDR) vision system. Themain focus will be the real-time video reconstruction at 60 frames/sec in an embedded architecture.Most of the sensors produce a digital image that is not able to reproduce the real world light inten-sities. Similarly, monitors, printers and current displays do not recover of a wide tonal range. Theapproach proposed in this thesis is multiple acquisitions, taken with different exposure times, to over-come the limitations of the standard devices.To temporally adapt the light conditions, the study of algorithms dedicated to the high dynamic rangetechniques is performed. Our new smart camera system is able to capture, generate and showcontent in a highly parallelizable context for a real time processingDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

Overview of ghost correction for HDR video stream generation

International audienceMost digital cameras use low dynamic range image sensors, these LDR sensors can capture only a limited luminance dynamic range of the scene[1], to about two orders of magnitude (about 256 to 1024 levels). However, the dynamic range of real-world scenes varies over several orders of magnitude (10.000 levels). To overcome this limitation, several methods exist for creating high dynamic range (HDR) image (expensive method uses dedicated HDR image sensor and low-cost solutions using a conventional LDR image sensor). Large number of low-cost solutions applies a temporal exposure bracketing. The HDR image may be constructed with a HDR standard method (an additional step called tone mapping is required to display the HDR image on conventional system), or by fusing LDR images in different exposures time directly, providing HDR-like[2] images which can be handled directly by LDR image monitors. Temporal exposure bracketing solution is used for static scenes but it cannot be applied directly for dynamic scenes or HDR videos since camera or object motion in bracketed exposures creates artifacts called ghost[3], in HDR image. There are a several technics allowing the detection and removing ghost artifacts (Variance based ghost detection, Entropy based ghost detection, Bitmap based ghost detection, Graph-Cuts based ghost detection …) [4], nevertheless most of these methods are expensive in calculating time and they cannot be considered for real-time implementations. The originality and the final goal of our work are to upgrade our current smart camera allowing HDR video stream generation with a sensor full-resolution (1280x1024) at 60 fps [5]. The HDR stream is performed using exposure bracketing techniques (obtained with conventional LDR image sensor) combined with a tone mapping algorithm. In this paper, we propose an overview of the different methods to correct ghost artifacts which are available in the state of art. The selection of algorithms is done concerning our final goal which is real-time hardware implementation of the ghost detection and removing phases.

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

Multispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

Energy balance in Spectral Filter Array camera design

Multispectral imaging permits to capture more spectral information on object surface properties than color imaging. This is useful for machine vision applications. Transmittance spectral filter arrays combined with a solid state sensor form an emerging technology used for snapshot acquisition. In spectral filter arrays technology, the sensitivities of the camera have critical consequences, not only on applications, but also in the viability of the system. We discuss how to balance the energy of each channel in single exposure multispectral imaging