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Domestic manufacturer Stevie launches 0.7 μ m 52MP CMOS image sensor

2025-01-20 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > IT Information >

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CTOnews.com November 17, CMOS image sensor supplier Stevie (Shanghai) Electronic Technology Co., Ltd. (SmartSens) launched its new 0.7 μ m pixel size 52MP ultra-high resolution image sensor product SC520XS.

According to reports, as Stevie's first 0.7 μ m ultra-small pixel size chip, SC520XS uses advanced stack backlighting technology (Stacked BSI), equipped with Stevie's SFCPixel-SL technology in the field of small pixel size chips, and relies on superior technologies such as ultra-low noise peripheral reading circuits and cinema-level color visual effects to further improve highlight and shadow details in images. Bring high-quality night vision full-color images to high-end smartphone cameras such as master camera, front camera, ultra-wide-angle camera and telephoto camera.

At the same time, SC520XS is also the first 0.7 μ m chip in the industry to use AllPix ADAF technology on the 5000-megapixel track, achieving 100% full-pixel focus even in fast-moving scenes. In addition, the new product also has an upgraded ultra-low power design, which can provide strong battery life for smartphone camera AI recognition applications.

SC520XS is the first image sensor equipped with a new self-developed SFCPixel-SL technology, which is based on Stevie's innovative SFCPixel patented technology. Compared with products of the same specifications in the industry, the quantum efficiency of SC520XS is effectively increased by 13%, the sensitivity is greatly increased to 2 times, the full well of electrons is effectively increased by 20%, the maximum signal-to-noise ratio is up to 42dB, and the reading noise is greatly reduced by 64%, which well balances the full well and noise performance of the product. At the same time, it takes into account the excellent full-color imaging performance of night vision and richer details and layers during the day. In addition, with the built-in dual-gain conversion function of pixel brought by SFCPixel-SL technology, the dynamic range of SC520XS is significantly improved 10.5dB.

SC520XS also carries Stevie's ultra-low noise peripheral reading circuit and cinema-level color visual effects and other superior technologies, which can present excellent night-shooting images with full color and fine picture quality, and can bring film-level night-shooting image texture to the mobile phone camera system.

In addition, the SC520XS, the first 0.7 μ m chip in the industry's 5000-megapixel track that uses 100% full-pixel focusing, is equipped with Stevie's newly developed AllPix ADAF all-phase pixel focusing technology, which enables 100% full-pixel focusing in a combination of horizontal and vertical orientation, even in dynamic and dark scenes.

At the same time, SC520XS can also choose Sparse PD mode according to different application scenarios to achieve partial focus and output clear images with higher frame rate, thus further reducing the power consumption of mobile phone CIS chips. In addition, SC520XS also supports two data flow modes: output phase value (TYPE 1) and PD raw data (TYPE 2), providing customers with more choices.

SC520XS can output 52MP resolution images, and it can also realize four-in-one Binning through QCell technology to output 13MP resolution images with high frame rate.

CTOnews.com learned that SC520XS has also made an upgraded ultra-low-power design at the chip architecture level. When identification requirements appear, it first uses ALS (photoelectric mode) to identify environmental changes, and then triggers ULP (ultra-low power mode) startup, thus greatly reducing sensor power consumption. According to official tests, the power consumption of SC520XS can be as low as 1.4mW in ALS photoelectric mode and as low as 3.5mW in ultra-low power ULP mode. At the same time, with the camera back-end algorithm, the smartphone camera system can perform complex AI recognition functions such as gesture recognition, face recognition and environment recognition.

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