R 47 Pixel continues to shrink ... . Small Pixels for Novel CMOS Image Sensors

This paper presents recent results of small pixel development for different applications and discusses optical and electrical characteristics of small pixels along with their respective images. Presented are basic optical and electrical characteristics of pixels with sizes in the range from 2.2μm to 1.1μm,. The paper provides a comparison of front side illumination (FSI) with back side illumination (BSI) technology and considers tradeoffs and applicability of each technology for different pixel sizes. Additional functionalities that can be added to pixel arrays with small pixel, in particular high dynamic range capabilities are also discussed. 1. FSI and BSI technology development Pixel shrinking is the common trend in image sensors for all areas of consumer electronics, including mobile imaging, digital still and video cameras, PC cameras, automotive, surveillance, and other applications. In mobile and digital still camera (DSC) applications, 1.75μm and 1.4μm pixels are widely used in production. Designers of image sensors are actively working on super-small 1.1μm and 0.9um pixels. In high-end DSC cameras with interchangeable lenses, pixel size reduces from the range of 5 – 6 μm to 3 – 4 μm, and even smaller. With very high requirements for angular pixel performance, this results in similar or even bigger challenges as for sub 1.4μm pixels. Altogether, pixel size reduction in all imaging areas has been the most powerful driving force for new technologies and innovations in pixel development. Aptina continues to develop FSI AptinaTM A-PixTM technology for pixel sizes of 1.4μm and bigger. Figures 1a and 1b illustrate a comparison of a regular pixel for a CMOS imager with Aptina’s A-Pix technology. Adding a light guide (LG) and extending the depth of the photodiode (PD) allow significant reduction of both optical and electrical crosstalk, thus significantly boosting pixel performance [1]. A-Pix technology has become a mature manufacturing process that provides high pixel performance with lower wafer cost compared to BSI technology. The latest efforts in developing A-Pix technology were focused on improving symmetry of the pixel, which resulted in extremely low optical cross-talk, reduced green imbalance and color shading. Improvements stem from improvements in the design and manufacturing of LG, along with the structure of Si PD. LG allows one to compensate for pixel asymmetry (at least its optical part) thus providing both optimal utilization of Si area, and minimal green imbalance / color shading. Figure 2 shows an example of green imbalance for 5Mpix sensors with 1.4μm pixels size designed for 27degree max CRA of the lens. Improvement of the LG design reduces green imbalance by more than 7x. BSI technology allows further reduction of pixel size to extremely small 1.1μm and 0.9μm, and more symmetrical pixel design for larger pixel nodes. Similar to A-Pix, the use of back side illumination in pixel design allows significant reduction of optical and electrical crosstalk, as illustrated in Figure 1c. Both BSI and Aptina Apix technology use the 90nm gate and 65nm pixel manufacturing process. Aptina’s BSI technology uses cost-effective P-EPI on P+ bulk silicon as starting wafers. The wafers receive normal FSI CMOS process with skipping some FSI p modules. Front side alignment marks are added for later backside alignments. The device wafers are bonded to BSI carrier wafers, and are thinned down to a few microns thick through wafer back side grinding, selective wet etch, and chemical-mechanical planarization process. The wafer thickness is matched to front side PD depth to reduce cross-talk. Finally, anti-reflective coatings are applied to backside silicon surface and micro-lens to increase pixel QE. Figure 3 shows normalized quantum efficiency spectral characteristics of 1.1μm BSI pixels. Pixels exhibit high QE for all 3 colors and small crosstalk that benefit overall image quality. Figure 4 presents luminance SNR plots for 1.4μm FSI and BSI pixels and 1.1μm BSI pixel. Due to advances of A-Pix technology, characteristics of FSI and BSI 1.4μm pixel are close, with the BSI pixel slightly outperforming FSI pixel, especially at very high CRA. However, the difference in performance is much smaller compared to conventional FSI pixel. For 1.1μm pixels, BSI technology definitely plays a key role in achieving high pixel performance. Major pixel photoelectrical characteristics are presented in Table 1. 2. Image quality of sensors with equal optical format Figure 5 presents SNR10 metrics for different pixel size inversely normalized per pixel area scene illumination at which luminance SNR is equal to 10x for specified lens conditions, integration time, and color correction matrix. As can be seen from the plot, the latest generation of pixels provides SNR10 performance that is scaled to the area, and as a result, provides the same image quality at the same optical format for the mid level of exposures. The latest generation of pixels with the size of (1.1μm – 2.2μm) in Figure 5 uses advances of A-pix technology to boost pixel performance. Many products for mobile and DSC applications use 1.4μm pixel; the latest generations of 1.75μm, 1.9μm, and 2.2μm are in mass production both for still shot and video-centric 2D and 3D applications. Bringing the latest technology to the large 5.6μm pixel has allowed us to significantly boost performance of that pixel (shown as a second bar of Figure 5 for 5.6μm pixel) for automotive applications. As was mentioned earlier, BSI technology furthers the extension of array size for the optical formats. The latest addition to the mainstream mobile cameras with 1⁄4‖ optical format is 8Mpix image sensor with 1.1μm pixels size. Figure 6 compares images from the previous 5Mpix sensor with 1⁄4‖ optical format with 1.4μm pixel size with images from the new 8Mpix sensor with 1.1μm pixel that fits into the same 1/4‖ optical format. Images were taken from the scene with ~100 lux illumination at 67ms integration time and typical f/2.8 lens for mobile applications. Zoomed fragments of the images with 100% zoom for 5Mpix sensor show very comparable quality of the images and confirm that similar image quality for a given optical format results when pixel performance that is scaled to the area continues to be the same. Figure 4 shows also the lowest achievable SNR10 for 1.4μm pixel at similar conditions for the ideal case of QE equal to 100% for all colors and no optical or electrical crosstalk – color overlaps are defined only by color filters. The shape of color filters is taken from large pixel sensor for high-end DSC application and assumes very good color reproduction. It is interesting to see that current 1.4μm pixel has only 40% lower SNR at conditions close to first acceptable image, SNR10 [2]. 3. Additional functionality for arrays with small pixels With the diffraction limits of imaging lenses, the minimum resolvable feature size (green light, Rayleigh limit) for an fnumber 2.8 lens is around 1.8 microns [3]. As pixel sizes continue to shrink below 1.8 microns, the image field produced from the optics is oversampled and system MTF does not continue to show scaled improvement based on increased frequency pixel sampling. How can we take advantage of increased frequency pixel sampling then? High Dynamic Range. Humans have the ability to gaze upon a fixed scene and clearly see very bright and dark objects simultaneously. The typical maximum brightness range visible by humans within a fixed scene is about 10,000 to 1 or 80dB [4]. Mobile and digital still cameras often struggle to match the intra-scene dynamic range of the human visual system and can’t capture high range scenes (50-80dB) primarily because the pixels in the camera’s sensors have a linear response and limited well capacities. HDR image capture technology can address the problem of limited dynamic range in today’s camera. However, a low cost technique that provides adequate performance for still and video applications is needed. Frame Multi-exposure HDR. The frame multi-exposure technique, otherwise known as exposure bracketing, is widely used in the industry to capture several photos of a scene and combine them into an HDR photo. Although this technique is simple, effective, and available to anyone with a camera with exposure control, the drawbacks relegate this technique to still scene photography and frame buffer-based post processing. If an HDR camera system is desired that doesn’t require frame memory and can reduce motion artifacts to a level where video capture is possible, the common image sensor architecture used in most cameras today must be changed. Can we use smaller pixels to provide multi-exposure HDR that doesn’t require frame memory for photos and reduces motion artifacts and allows video capture? Interleaved HDR Capture. With pixel size reduction there is an opportunity to take advantage of the diffraction limits of camera optical systems by spatially interleaving pixels with differing exposure time controls to achieve multi-exposure capture. Figure 7 shows an example of a dual exposure capture system using interleaved exposures within a standard Bayer pattern. This form of intra-frame multi-exposure HDR capture can be easily incorporated into standard CMOS sensors and doesn’t require the additional readout speed or large memories. The tradeoff of interleaving the exposures is that fewer pixels are available for each exposure image and can affect the overall captured image resolution. This is where the advantage of small pixels comes into play: as pixels shrink below the diffraction limit, the system approaches being oversampled such that the MTF doesn’t improve proportionally to pixel size. We propose that greater gain in overall image quality may be achieved by spatially sampling different exposures to capture higher scene quality rather than oversampling the image. In Figure 7, pairs of rows are used for each exposure to ens