Hikvision Advanced Image Processing - Noise Reduction

Hikvision Advanced Image Processing - Noise Reduction

The video image data produced by an image sensor or the scanner circuitry of a digital camera contain both the signal as well as the noise information. Noise is always present in an image, especially when the images are produced in a low light environment. The signal-to-noise ratio is used to compare the level of signal to the level of background noise. A higher ratio means better image quality. While the existence of noise is a critical factor in image quality, it also adds an extra burden to encoding process as well. It significantly increases the data size for transmission and storage, resulting in the waste of bandwidth and storage space. Accordingly, reducing the noise from an image is a critical function of video processing technology.

Distinguishing between the noise and the details of the image, the current noise reduction technology used in video surveillance products reduces the noise from an image via linear filtering and non-linear filtering. Based upon the signal and noise content of video data and the analysis of noise estimation and reduction requirements, noise reduction techniques can be classified into spatial filtering, temporal filtering, motion adaptive filtering and motion compensation filtering, etc.. All these technologies have been adopted in most surveillance products sold today.

Combining with the accurate noise intensity estimation algorithm, the production of Hikvision mainly adopts the motion adaptive filter and the motion compensation filter technologies. The image of the Hikvision cameras presents distinguished details in ideal illumination, and suppresses the noise to produce high-quality image in low illumination. Meanwhile, the perfect combination of the outstanding noise reduction technology and the advanced H.264 encoding technology decreases the data compression storage and network transmission bandwidth, massively saving resources.

What's inside?

  • The reasons and influences of the image noise
  • The theory and classification of noise reduction technologies
  • A comparison of noise reduction technologies
  • Conclusion
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