Curved CMOS image sensors for enhanced imaging systems: focus on smartphone camera lens

图像传感器 镜头(地质) 光学(聚焦) 计算机科学 计算机视觉 摄像头模块 CMOS传感器 光圈(计算机存储器) 人工智能 视野 焦距 光学 物理 声学
作者
Wilfried Jahn,Tahar Mehri
标识
DOI:10.1117/12.2651198
摘要

Curved imaging sensors bring significant size, weight and cost reduction to imaging systems while mitigating off-axis optical aberrations, as opposed to current flat sensors. Unlocking these key features has captured the interest of major players over the last two decades. SILINA has been developing a CMOS Image Sensor (CIS) curving process, which adapts to various sensor characteristics. This enables to maximize the optical performance of every single imaging system. We have demonstrated the manufacturing of curved CMOS Front-Side Illuminated (FSI) and Back Side Illuminated (BSI), opening a new area of compact, fast, wide-angle and high-resolution optical lenses. This new degree of freedom offered to optical designer can significantly simplify optical systems through a significant improvement of the optical performance while simplifying the system architecture in many different ways. The field of view (FOV), the contrast, the aperture can be increased while optical aberrations can be minimized. At the end, the different costs related to manufacturing, metrology, integration, and alignment are reduced. This is of great importance for applications requiring compact and high resolution lens, notably in low-light environment. To quantify the gain brought by curved image sensor for smartphone camera lens, we are performing several comparative optical lens designs. We compare traditional flat-image sensor based camera lens to camera lens optimized specifically with a curved image sensor. In this paper, we present the result obtained on wide-angle smartphone camera lens design considering a spherical concave image sensor. We compare the optical characteristics and performance with a reference optical design using a flat image sensor. We discuss the various benefits in terms of optical performance and Z-stack reduction.
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