Second Generation Small Pixel Technology Using Hybrid Bond Stacking

Image Quality Assessment for Realistic Zoom Photos

New CMOS imaging sensor (CIS) techniques in smartphones have helped user-generated content dominate our lives over traditional DSLRs. However, tiny sensor sizes and fixed focal lengths also lead to more grainy details, especially for zoom photos. Moreover, multi-frame stacking and post-sharpening algorithms would produce zigzag textures and over-sharpened appearances, for which traditional image-quality metrics may over-estimate. To solve this problem, a real-world zoom photo database is first constructed in this paper, which includes 900 tele-photos from 20 different mobile sensors and ISPs. Then we propose a novel no-reference zoom quality metric which incorporates the traditional estimation of sharpness and the concept of image naturalness. More specifically, for the measurement of image sharpness, we are the first to combine the total energy of the predicted gradient image with the entropy of the residual term under the framework of free-energy theory. To further compensate for the influence of over-sharpening effect and other artifacts, a set of model parameters of mean subtracted contrast normalized (MSCN) coefficients are utilized as the natural statistics representatives. Finally, these two measures are combined linearly. Experimental results on the zoom photo database demonstrate that our quality metric can achieve SROCC and PLCC over 0.91, while the performance of single sharpness or naturalness index is around 0.85. Moreover, compared with the best tested general-purpose and sharpness models, our zoom metric outperforms them by 0.072 and 0.064 in SROCC, respectively.

Design of a CMOS image sensor pixel with embedded polysilicon nano-grating for near-infrared imaging enhancement

Complementary metal-oxide semiconductor (CMOS) image sensor sensitivity in the near-infrared spectrum is limited by the absorption length in silicon. To deal with that limitation, we evaluate the implementation of a polysilicon nano-grating inside a pixel, at the transistor gate level of a 90 nm standard CMOS process, through opto-electrical simulations. The studied pixel structure involves a polysilicon nano-grating, designed with the fabrication layer of the transistor gate, which does not require any modifications in the process flow. The diffraction effect of the nano-grating increases the length of the light path in the photosensitive area and thus increases the photoelectric conversion efficiency. The nano-grating is integrated in combination with deep trench isolations to reduce cross talk between pixels. Coupled optical and electrical simulations report 33% external quantum efficiency improvement and 7% cross talk reduction at 850 nm.

Deep Trench Isolation and Inverted Pyramid Array Structures Used to Enhance Optical Efficiency of Photodiode in CMOS Image Sensor via Simulations

The photodiode in the backside-illuminated CMOS sensor is modeled to analyze the optical performances in a range of wavelengths (300-1100 nm). The effects of changing in the deep trench isolation depth (DTI) and pitch size (d) of the inverted pyramid array (IPA) on the peak value (OE_max.) of optical efficiency (OE) and its wavelength region are identified first. Then, the growth ratio (GR) is defined for the OE change in these wavelength ranges to highlight the effectiveness of various DTI and d combinations on the OEs and evaluate the OE difference between the pixel arrays with and without the DTI + IPA structures. Increasing DTI can bring in monotonous OE_max. increases in the entire wavelength region. For a fixed DTI, the maximum OE_max. is formed as the flat plane (d = 0 nm) is chosen for the top surface of Si photodiode in the RGB pixels operating at the visible light wavelengths; whereas different nonzero value is needed to obtain the maximum OE_max. for the RGB pixels operating in the near-infrared (NIR) region. The optimum choice in d for each color pixel and DTI depth can elevate the maximum GR value in the NIR region up to 82.2%.

Proximity Gettering Design of Hydrocarbon⁻Molecular⁻Ion⁻Implanted Silicon Wafers Using Dark Current Spectroscopy for CMOS Image Sensors

We developed silicon epitaxial wafers with high gettering capability by using hydrocarbon-molecular-ion implantation. These wafers also have the effect of hydrogen passivation on process-induced defects and a barrier to out-diffusion of oxygen of the Czochralski silicon (CZ) substrate bulk during Complementary metal-oxide-semiconductor (CMOS) device fabrication processes. We evaluated the electrical device performance of CMOS image sensor fabricated on this type of wafer by using dark current spectroscopy. We found fewer white spot defects compared with those of intrinsic gettering (IG) silicon wafers. We believe that these hydrocarbon-molecular-ion-implanted silicon epitaxial wafers will improve the device performance of CMOS image sensors.

Front-Inner Lens for High Sensitivity of CMOS Image Sensors

Due to the continuing improvements in camera technology, a high-resolution CMOS image sensor is required. However, a high-resolution camera requires that the pixel pitch is smaller than 1.0 μm in the limited sensor area. Accordingly, the optical performance of the pixel deteriorates with the aspect ratio. If the pixel depth is shallow, the aspect ratio is enhanced. Also, optical performance can improve if the sensitivity in the long wavelengths is guaranteed. In this current work, we propose a front-inner lens structure that enhances the sensitivity to the small pixel size and the shallow pixel depth. The front-inner lens was located on the front side of the backside illuminated pixel for enhancement of the absorption. The proposed structures in the 1.0 μm pixel pitch were investigated with 3D optical simulation. The pixel depths were 3.0, 2.0, and 1.0 μm. The materials of the front-inner lens were varied, including air and magnesium fluoride (MgF₂). For analysis of the sensitivity enhancement, we compared the typical pixel with the suggested pixel and confirmed that the absorption rate of the suggested pixel was improved by a maximum of 7.27%, 10.47%, and 29.28% for 3.0, 2.0, and 1.0 μm pixel depths, respectively.