2D/3D Digital Noise Reduction On CCTV Explanation
To protect your security on your premise, you wouldn’t want too much unwanted noise in the background of your footage. You will want a CCTV with a noise reduction feature to reduce the noise.
CCTV is just like other recording equipment. They gather the data from the environment around them. They are not invulnerable to noise in the background. As the CCTV captures the picture around them, the data may have errors and may be corrupted because of the noise. The data may also be overridden.
It is difficult to control the CCTV to capture the footage without any noise. It will need to depend on the CCTV sensor. But several techniques may help to reduce the noise that has been captured. These techniques are called “Digital Noise Reduction”. We will be discussing it in this article.
Noise Reduction #1: What Exactly Is Noise In CCTV?
Noise is unwanted data in CCTV footage, but any electronic will inevitably generate noise as it transmits or receives a signal. Noise can affect the footage or even destroy the information in a frame.
The sensors in the CCTV is not perfect device, and it is unavoidable that there will be noise in the image. Usually, CCTV with higher resolution is more susceptible to noise. This is because the image sensor is smaller and collects less light.
There will be noise in the CCTV due to the drawbacks of the CCTV light sensor. CCTV will need to rely on the environment to collect enough light. The more light it contains, the better the picture will be. When the CCTV is in low-light conditions, there will be a certain amount of noise in the footage.
Noise Reduction #2: What Is 2D DNR?
One of the most basic methods to eliminate noise in CCTV is 2D Digital Noise Reduction. Although it can eliminate the noise in the footage, it will affect the quality of the footage. It will affect the resolution of the footage, especially when there is a lot of motion around.
2D DNR can be considered a “Temporal Noise Reduction” technique. So what is 2D DNR? In this technique, each pixel on the frame will be compared to the pixels in other frames. Comparing the date of each of these pixels can detect a pattern that can be categorized as “noise.”
When these unwanted patterns have been discovered, the system will try to eliminate the noise by assigning an intensity color to a pixel that it considers noise-free. It might work for an environment with no movement but will cause motion blur as the system tries to figure out which intensity is the most natural for the pixel.
Noise Reduction #3: What Is 3D DNR?
3D DNR can be a bit different. It is a “Spatial Noise Reduction” technique. It compares and processes pixels in the image in three dimensions. The first two dimensions will be in an image, and the third dimension will be comparing pixels with other frames.
The difference between 3D DNR and 2D DNR is the algorithms that allow 3D DNR to process much faster. This algorithm can be performed with a larger resolution. The system will compare the pixels in a single frame during the process.
Techniques such as “median filters” and “averaging filters will be used in 3D DNR to eliminate the grainy nature and the noise from the single frame. Later, it will compare the pixels frame by frame to pick up motions in the footage.
Noise Reduction #4: Impact of Brightness on Image Noise
The brightness of an environment can affect the noise in the footage. Noise can be easier captured into the footage in a dimly-lit environment.
CCTV is much more advanced nowadays, but they are not always perfect. The measurements that are used are always an approximation of the real world. Every CCTV footage will have some noise and tries to gather more information to overcome the noise, such as getting a higher SNR.
The brightness of the CCTV helps to play a role in eliminating the noise in the footage. A more well-lit environment will allow the CCTV to collect the light to produce a better image. When there isn’t enough light, the CCTV doesn’t have enough data to process and will cause the noise to accumulate.
Although the help of 2D and 3D DNR can help to reduce the noise to a certain extent, improving the lighting condition of the environment is another option.
Noise Reduction #5: Impact On Storage
The noise won’t directly affect the storage but will affect the file size when the user tries to change the resolution of the image files.
The DNR algorithms can be complex as the processing power of some CCTV systems can’t compute the algorithms in real-time. To reduce the noise, some systems will choose a lower resolution of the footage.
Lower resolutions mean there will be fewer pixels to process. The system will be able to compute the DNR algorithms faster, and less storage space will be taken up. It isn’t necessary to adjust the resolution for the picture unless the user thinks it is necessary.
Noise Reduction #6 — Impact on Motion Detection
The noise in the footage can affect the motion detection algorithms. For the 2D DNR algorithm, it does not take kindly to constant motion in the final footage.
Luckily, motion blur does not affect motion detection. As long as the motion blur effect isn’t blended in with the environment, the system will still pick up the motion. But the blurry image will make it difficult to distinguish important data, such as number plates and blurry nature.
To minimize the motion blur effect, using the 3D DNR method or other similar processing techniques is better. This is to ensure that you can gain better information from the footage.
You will want to have footage that has lesser noise, especially if you need it as evidence and there is a dialogue in between. Understanding this digital noise reduction can help you to get the right CCTV that suits your need.
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