Implementation method of dual-conversion gain image sensor

Abstract

The invention provides an implementation method of a dual-conversion gain image sensor. The method comprises that: a pixel signal generated by an image sensor passes through a first blocking capacitorand then serves as a pixel input signal of a comparator, a slope signal generated by a slope generator passes through a second blocking capacitor and then serves as a slope input signal of the comparator, and the comparator compares the pixel input signal with the slope input signal and then outputs a digital signal; when a floating diffusion region of the image sensor is switched from a low conversion gain to a high conversion gain, extra charge injection is generated to the floating diffusion region, so that a pixel input signal shifts; and the slope input signal is compensated, the offsetof the pixel input signal is matched, and the accuracy of converting the pixel signal into the digital signal is improved. On the premise that the clock frequency and the signal processing time are not changed and the layout area is prevented from being increased, the influence on extra charge injection of the floating diffusion region in the gain switching process is eliminated, and the accuracyof converting the pixel signal into the digital signal is improved.

Description

technical field [0001] The invention relates to the field of image sensors, in particular to a method for realizing a dual conversion gain (Dual Conversion Gain) high dynamic range image sensor. Background technique [0002] Standard image sensors have a limited dynamic range of approximately 6OdB to 7OdB. However, real-world brightness has a much greater dynamic range. Natural scenes typically span the range of 90dB and above. To capture both bright light and shadows, high dynamic range technology has been used in image sensors to increase the captured dynamic range. The most common technique for increasing dynamic range is to combine multiple exposures captured with a standard (low dynamic range) image sensor into a single linear high dynamic range image that has a much larger dynamic range than a single exposure image scope. [0003] In the most common approach in HDR image sensor solutions, an image sensor can have multiple exposures into a single image sensor with d...

AI Technical Summary

Problems solved by technology

Because when the floating diffusion region 130 switches from low gain to high gain, that is, the process from low to high in the figure, due to the turning off of the control transistor 160, additional charge injection will be brought to the floating diffusion region 130, resulting in The voltage of the floating diffusion region 130 decreases, thereby causing the pixel signal PXD and the pixel input signal PXDin to decrease

That is to say, this will cause ref2 output by PXD to have a fixed deviation more than ref1. This deviation may exceed the range of ref2 on the ramp signal RAMP. The same deviation will also affect the quantization of sig, thereby affecting the pixel signal conversion. for digital signal accuracy

The easiest way to improve is to increase the width of ref2 and sig on the RAMP waveform. However, this method has the following disadvantages: 1. When the clock frequency remains unchanged, it will increase the signal processing time; 2. If you want to keep If the signal processing time remains unchanged, the clock frequency must be accelerated; 3. The increase in the width of Ref2 and sig may lead to an increase in the number of counters used to store the output results of the comparator in the column (column readout circuit), thereby increasing the layout. area

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