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Image Sensor Selection Criteria for Surveillance Cameras

12 Jan 2011

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Traditionally, the surveillance camera market has been dominated by close circuit television (CCTV) systems that utilized charged coupled device (CCD) image sensors coupled with an image signal processor (ISP) , and a proprietary application-specific integrated circuit (ASIC). However, as a result of new technologies and changing design requirements, the surveillance camera market is seeing growth in popularity of Internet Protocol (IP) or network cameras. Increasingly, complimentary metal-oxide semiconductor (CMOS) sensors can increasingly be found in both CCTV and IP camera systems due to their ability to provided equal or better image performance, lower cost, lower power consumption and faster frame rates. In addition to the performance gap between CCD and CMOS narrowing, total system cost has also been reduced due to the high level of integration CMOS sensors offer. In a CCD-based camera, system components require a CCD imager, a timing generator, a signal amplifier, an ISP, and a NTSC/PAL encoder. On the other hand, all these components are integrated in a single-chip CMOS sensor system-on-chip (SOC) design for system cost saving and power reduction.

The trend from CCTV to IP cameras brings several benefits. Benefits include a removal of constraints by a NTSC/PAL resolution standard and the increase in adoption of megapixel image sensors in IP camera designs. Typical components needed for an IP camera include an image sensor, an ISP, a codec (compression/decompression) processor, and networking processor. Today, many processors and ASICs already contain integrated features like ISP, H.264 codec, system management, and Ethernet MAC interface. Examples of image sensors used in an IP design include Aptina's megapixel imagers which offer high performance and fast frame rates of 720P and 1080P at 60 frames per second (fps). Low-light sensitivity can also reach below half a lux at standard video frame rate. Although the standard video frame rate is 30 fps, 60 fps gives camera manufacturers the flexibility to adapt different shutter width to capture fast moving objects within the scene. Furthermore, markets like casino gaming require video monitoring with high video frame rates to capture the evidence necessary to convict law breakers. Another key trend in IP camera development is the adoption of wide dynamic range (WDR). Without WDR, images can be either overexposed or underexposed, resulting in an unusable image. WDR technology enables the camera to be placed almost anywhere as it resolves the challenges associated with trying to capture images in environments with both very dark and very bright regions.

Video analytics are also becoming an increasingly valued element of the IP camera solution. This is a family of intelligent video technologies for a group of either rule-based or heuristic-based video processing algorithms used to analyze live video stream in order to detect particular events. A major development within video analytics is the change from running on a server to more cost-effective embedded solutions within the camera. As the processing power of digital signal processors (DSPs) and field-programmable gate arrays (FPGAs) have grown, the algorithms once run on a server are being incorporated into the camera system either in software running on a processor, DSP, or in an FPGA as a special IP core.

KEY CONSIDERATIONS IN IMAGE SENSOR SELECTION
Real-world surveillance cameras often encounter both very bright scenes and very dark scenes. To capture these scenes, image sensors are typically optimized for one extreme (bright or dark) at the price of degraded performance for the other. The challenge is how to design an image sensor to work optimally in all scene conditions. For the image sensor within these cameras that must capture bright and dark scenes, this specifically translates into requirements for larger full-well (FW) capacities as well as increased sensitivity. However, increasing sensitivity directly impacts the FW capacity, the maximum achievable signal-to-noise ratio (SNR), and the total dynamic range (DR) of the sensor.

Pixels greater than two microns often have their FW capacity defined by the photodiode's charge holding capacity, rather than the pixel's voltage swing, due to its larger photosensitive area. To increase the charge handling capacity of this pixel, it is common to connect a physical capacitor to the floating diffusion (FD) node. However, this typically results in lower conversion gain (CG). This, in turn, means reduced sensitivity and increased input-referred read noise, thereby compromising low-light sensitivity and reducing the sensor's DR even though the sensor is capable of measuring larger signals.

There are many approaches to increasing DR that focus and on achieving high intra-scene dynamic range; however, these WDR techniques do not improve or fully address low-light sensitivity or reduce noise to improve low-light image captures. As a result, a different approach has emerged to improve inter-scene DR and sensor performance through the addition of a high-sensitivity mode to the sensor's operation. Two modes are combined into one pixel designlow conversion gain (LCG) for large charge handling capacity in bright scenes and a high conversion gain (HCG) mode with increased sensitivity and low read noise for low-light scenes, providing tremendous benefit for surveillance cameras where image sensors are expected to capture images/video in extreme low-light conditions without sacrificing the performance in high-light conditions to do so.

Although picture resolution is increasing in today's camera systems, the DR of pixels continues to decrease as pixel sizes shrink, thereby limiting the ability to produce natural images with both highlights and shadows preserved. As a result, various pixel schemes have been proposed for achieving WDR including logarithmic pixels, lateral overflow, frame multiexposure (ME) and intra-frame multiexposure (IFME), among others.

These methods of achieving WDR are aimed at achieving high intra-scene DR, which means that dark and bright areas within one scene can be properly exposed. This is commonly achieved either by combining multiple exposure times or frame captures into one image using the multiframe approach or by reducing the pixels' responsivity at higher exposures using a nonlinear signal approach. These techniques can typically achieve very high DR of >100dB within one image, which is very useful in many applications, such as a surveillance camera properly exposing a criminal's face while sunlight or glare is dominating the rest of the scene.

High intra-scene DR has some drawbacks as well. Nonlinear pixels may have poor color reproduction and low-light sensitivity, as well as higher fixed pattern noise (FPN). ME techniques not only require extra memory and post processing, but they can have reduced SNR near exposure transition points and motion artifacts caused by exposures captured in a time sequence, thus requiring extra motion compenzation and very high frame rates to be useful in video applications.

But, most importantly, what these WDR techniques do not do is improve low-light sensitivity or reduce noise to improve low-light image captures. As a result, a different approach, while not a competitor to WDR technologies, has emerged. This approach, focused on inter-scene DR, adds a separate high sensitivity mode to a pixel that already has a large charge handling capacity, called Dynamic Response Pixel technology, or Aptina DR-Pix technology, entails controlled switching on and off of a capacitor connected to the pixel's FD node. To perform this switching, one transistor, called the dual conversion gain (DCG) switch, is added to the pixel.

When imaging in high light conditions, the DCG switch is turned on, connecting the physical capacitor to the FD node. In this way, the large capacitance of the FD node is used to enable an LCG mode, which can handle a large amount of signal charge. In low-light conditions, the DCG signal is turned off, disconnecting the cap from the FD, and enabling an HCG mode, which can be used as an extra analog gain, inside the pixel. In this case, the FD capacitance is only due to the parasitic capacitance of the FD's pn junction diffusion and metal coupling, which is much smaller due to the physical cap structure. The much lower FD capacitance results in much higher conversion gain, higher sensitivity, and reduced read noise, at the expense of lower maximum charge handling capacity.

This scheme allows very high inter-scene DR by providing high sensitivity and low read noise for dark scenes, and large charge handling capacity for well-lit scenesall inside of one pixel design. In this approach, the DR of one scene is not increased, but the range of illumination over which the sensor may be used is extended at the low-light end by the addition of the HCG mode. For surveillance applications that must capture video often in dimly lit conditions, this is also a tremendous benefit.

APTINA IMAGE SENSOR ADVATANGES
Capturing high quality 60 fps HD video in all lighting conditions ranging from very high contrast to very dark scene is extremely challenging work. In the past, a megapixel sensor could either provide high dynamic range or excellent low light sensitivity, but not both. Aptina's new HD megapixel sensors, designed with Aptina DR-Pix technology and multiexposure wide dynamic range imaging technique brings the two worlds together. This technology allows programmable conversion gain adjustment globally across all pixels to match the overall light level in the scene. This technique, coupled with true correlated double sampling, enables Aptina's MT9M003 HD imager with the means to achieve an amazingly low, <2e- rms, read noise and leading edge quantum efficiency of more than 60 percent.

To attain exceptionally >100db wide dynamic range imaging for this imager, a multiexposure method technique was implemented. In contrast to the conventional lateral overflow method where full well is divided into multiple parts, Aptina's multiexposure system fully utilizes 100 percent of each pixel's FW capacity thus making the multiexposure method a superior method for controlling blooming. To further perfect Aptina's multiexposure WDR system, special readout and processing schemes were added to alleviate typical high dynamic range motion artifacts created by fast moving objects in the scene. Aptina HD sensors incorporate Aptina DR-Pix technology to render HD video at 60fps, these speeds give camera manufacturers the flexibility to adapt different shutter width to capture fast moving objects within the scene. Using this technology, camera designers no longer need to compromise between speed, power, high dynamic range, and low-light performance to create a true HD camera.

FUTURE TRENDS IN IMAGE SENSOR TECHNOLOGY
While WDR technology enables the camera to be placed almost anywhere and resolves the challenges associated with trying to capture images in environments with both very dark and very bright regions in challenging lighting environments, surveillance cameras must also address the issue of the camera's shutter to reduce or remove image lag. The earliest image sensing technologies utilized an electronic shutter mechanism known as a rolling shutter to conform to early TV system architectures and other mediums that transmitted data serially. With a long history of using column-parallel readout architectures, in which pixels of the same row are readout simultaneously, rolling shutter is a natural choice for performing shutter operations within CMOS image sensors.

The global shutter pixel technology typically found on CCD image sensors can offer significant benefits, such as the elimination of rolling shutter artifacts through simultaneous image capture of the entire frame. However, the use of global shutter pixel requires the addition of a pixel-level memory one of the barriers to widespread global shutter adoption. Today, CMOS image sensor providers are closing the performance gap between rolling and global shutter alternatives by addressing several technical areasfill factor/quantum efficiency (QE), global shutter efficiency (GSE) and dark current. In solving for these issues, CMOS image sensor vendors can deliver global shutter pixel technology with smaller pixel size, larger fill factor, higher GSE, lower dark current and lower noise, better positioning CMOS image sensors to replace CCD at a more rapid rate.

CONCLUSION
As image sensor technology evolves, companies like Aptina are continually working on meeting the challenges related to providing cost-effective, high performance imaging solutions for the surveillance market. CMOS is playing an increasingly larger role in meeting the requirements for the surveillance camera market and offer features and flexibility to camera designers like WDR and Aptina's DR-Pix technology.




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