2019 iPhone XI to use super wide-angle and TOF lens

iphone se2 xe

In the past, Apple takes the lead in the smartphone market and other Chinese OEMs copy its work. This can not be said to be true for recent times. In the past two years, some Chinese brands like Huawei have become innovative and its mobile phone camera image quality leads the DxOmark ranking for some time now. It’s interesting to see that Chinese brands are becoming more innovative and this will increase the competition for Apple to do better. Overall, Apple still ranks above all Chinese OEMs and the company will come up with this year’s iPhone XI model.

The biggest innovation of the iPhone XI is the super wide-angle and the rear TOF lenses. This is not a new feature. Many Chinese OEMs like Xiaomi and Huawei have smartphones with super wide-angle lenses and these cameras can shoot really good landscape images. However, it is expected that Apple will come up with a unique super wide angle lens if it wants to make an impact.

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Apple iPhone XI rear lens consists of three main lenses which include a normal wide-angle lens (main lens), a 2x zoom telescope sensor and a super wide-angle lens. As a result, the iPhone XI’s rear lens position cannot be as vertical as the iPhone X, but instead, it has been changed to a square structure. TOF cameras have the following advantages over structured optical sensors.

— The TOF sensor component is simpler. In theory, only one emitter (lens) is required, and at least three structured lights are required (one floodlight + one infrared recognition lens + one infrared mapping point projector)

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— TOF is the calculation of the return time, so the interference against ambient light is significantly stronger than the structured light technology that needs to identify the image, and the accuracy is higher.

— TOF calculates the return time, no need to image the object, so the effective ranging distance is much farther than the structured light.

— TOF can directly get the return time, and the structured light needs to be photographed and then compared to calculate the distance. Therefore, TOF will save CPU resources and greatly shorten the recognition time.

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