Clustering noise reduction device and method, chip, event imaging device and electronic equipment

Abstract

The invention discloses a clustering noise reduction device and method, a chip, an event imaging device and electronic equipment. In order to solve the technical problem that there is noise in the event imaging process, a noise reduction scheme as follows is adopted that the method comprises the steps of receiving a new event in real time, and continuously storing the new event in an address corresponding to a storage space, the storage space being dynamically changed and updated in real time; and determining a clustering range in the storage space, judging whether the new event forms an effective clustering relationship with other events in the storage space, and judging whether the event belongs to a noise event or an effective event according to the clustering relationship. Through the technical means, the noise reduction scheme disclosed by the invention not only can filter common noise, but also can filter special noise, effective events can be reserved to the greatest extent while the noise is filtered, the killing of the effective events is small, and the noise reduction method has the technical effects of high response speed, low time delay, low power consumption and the like.

Description

technical field [0001] The invention relates to a cluster noise reduction device, method, chip and electronic equipment, in particular to a device, method, chip and electronic equipment for performing cluster noise filtering on pulse events output by an event imaging device. Background technique [0002] Event imaging does not capture images at a fixed rate, but asynchronously measures the brightness change of each pixel and outputs a series of events. Compared with traditional cameras, event cameras provide attractive characteristics: low power consumption, real-time Strong, large dynamic range, high resolution, etc. A common event imaging device is the dynamic visual sensor DVS, which is a visual sensor suitable for neuromorphic and brain-like computing. However, limited by the current technology and technology, the actual output of DVS has various noises. Researchers from various countries have also done a lot of research work in this frontier field, but most filtering t...

AI Technical Summary

Problems solved by technology

The two steps of this method have a high dependence on the value of the spatial range. If the spatial range is too large, noise events will be missed and the filtering effect will be poor; if the spatial range is too small, valid events will be misjudged and effective events will be filtered. In addition, affect the image quality

At the same time, this method is complex and time-consuming, and it does not deal with special noise (such as black block noise), so its practical value is relatively insufficient

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