Image stabilisation – improving camera usability

June 2015 CCTV, Surveillance & Remote Monitoring, Editor's Choice

Gusts of wind tearing at a surveillance camera can make it shake or vibrate enough to make images come out as useless blur. A heavy truck, or a train, passing close by can have similar consequences.

A number of different technical solutions have been developed to cope with the problem, with varying degrees of success. However, the introduction of efficient gyroscopes in combination with cutting-edge software programming has accelerated the process towards robust, real-time image stabilisation.

Vibration impact on video output

Improvements in video quality have made the problem with blurry images more apparent. Increasing pixel density, higher resolution and more powerful zooms have not only made cameras more sensitive to vibrations, but have also made viewers more susceptible and prone to noticing them.

Naturally, operators and integrators are aware of these challenges and are trying to address them. For example, vibration can be reduced by choosing sturdier mounts or less exposed locations for the installation.

Image stabilisation makes the entire video surveillance system more versatile and cost efficient by making better use of each camera’s potential, for example by maintaining image quality in zoom shots when vibrations otherwise may have affected the video quality.

Image stabilisation techniques

Image stabilisation techniques are used in consumer products such as digital still cameras and video cameras. Today, there are two methods to tackle the problem – optical image stabilisation and electronic image stabilisation.

Optical image stabilisation

An optical image stabilisation system usually relies on gyroscopes or accelerometers to detect and measure camera vibrations. The readings, typically limited to pan and tilt, are then relayed to actuators that move a lens in the optical chain to compensate for the camera motion. In some designs, the favoured solution is instead to move the image sensor, for example using small linear motors.

Either method is able to compensate the shaking of camera and lens, so that light can strike the image sensor in the same fashion as if the camera was not vibrating. Optical image stabilisation is particularly useful when using long focal lengths and also works well in low light conditions.

The main disadvantage of an optical solution is the price.

Electronic image stabilisation</i>

Electronic image stabilisation, also known as digital image stabilisation, has primarily been developed for video cameras.

Figures 1 and 2. Left image, a close-up without electronic image stabilisation, showing both horizontal and vertical motion blur. Right image, a snapshot from the vibrating camera with electronic image stabilisation activated.
Figures 1 and 2. Left image, a close-up without electronic image stabilisation, showing both horizontal and vertical motion blur. Right image, a snapshot from the vibrating camera with electronic image stabilisation activated.

Electronic image stabilisation relies on different algorithms for modelling camera motion, which then are used to correct the images. Pixels outside the border of the visible image are used as a buffer for motion and the information on these pixels can then be used to shift the electronic image from frame to frame, enough to counterbalance the motion and create a stream of stable video.

Although the technique is cost efficient, mainly because there is no need for moving parts, it has one shortcoming which is its dependence on the input from the image sensor. For instance, the system can have difficulties in distinguishing perceived motion caused by an object passing quickly in front of the camera from physical motion induced by vibrations.

Rolling shutter distortion

Many video cameras, especially cameras with CMOS sensors, come with a rolling shutter. Unlike a global shutter, which exposes all pixels at the same time in a single snapshot, the rolling shutter catches the image by scanning across the frame, line by line. In other words, all parts of the image are not captured at the same time, but each line is exposed during a slightly different time window. Shakes or vibrations of the camera will therefore result in each exposed line being slightly moved in relation to the other lines, causing a warped or wobbled image. Fast moving objects may also appear distorted in a similar way.

Figure. 3. Shows the principle of global shutter distortion.
Figure. 3. Shows the principle of global shutter distortion.

Rolling shutter distortion induced by vibrations can be avoided with optic stabilisation, which instantaneously compensates for the motion. Electronic stabilisation methods have a slight disadvantage in this case. The rolling shutter must first scan at least one line before the digital processing to stabilise the image can begin. Nevertheless, this method works very well and the technology is improving rapidly.

An outstanding combination

The development of affordable gyroscopes together with more efficient algorithms for modelling camera motion has made stabilisation techniques more available.

It has also enabled the creation of hybrid systems that use gyroscope measurements, not to move the lens, but to process the images digitally according to those gyroscopic signals. Axis has chosen this combined method because of its versatility. The solution is designed to cover a wide band of frequencies as well as coping with high and low amplitudes. Advanced gyroscopes together with optimised algorithms make a robust and reliable system. Even in poor lighting environments the system performs very well since it is relying on gyroscopic information, rather than video content, for motion calculations. For the same reason, the system can always distinguish between perceived motion caused by passing objects and physically induced vibrations.

Benefits and applications in video surveillance

A surveillance camera mounted in an exposed location such as on a high pole or a street sign near a busy road, can be shaken by winds or passing traffic, which will blur the video. This is especially true when a powerful telescopic zoom is used. When zooming in on a distant object, the field of view becomes narrower and any shake or tremble will be amplified in the camera – and the amplitude of the shake will increase proportionally to the amount of zoom used.

Therefore, image stabilisation should be regarded as a prerequisite for cameras with zoom lenses, so they can be used optimally also in windy weather or other unfavourable circumstances. Having cameras that are less sensitive to vibrations also makes installation more flexible and allows for multiple mounting options. In the end, fewer cameras may be needed to satisfy surveillance requirements.

A perhaps less obvious advantage of image stabilisation is that privacy masking can be made more precise. On a camera without any stabilisation system, the effects of possible shakes and vibrations would have to be compensated by increasing the masked off area in the image.

Finally, stabilised images will save bandwidth use and storage space. Advanced video compression formats, such as H.264, are based on motion compensation. In short, this method uses the image of a single frame as a baseline and then only saves information about changes in the picture. A well stabilised image will contain comparatively less movement and thus require less bandwidth and storage.

Conclusion

Hardware and software development are making efficient video stabilisation techniques affordable for an ever-increasing range of network cameras. This progress not only secures smooth, comfortable video monitoring in real time. It also enhances image usability, improves camera operability, makes installation more flexible and, finally, improves the overall cost efficiency of a network camera surveillance system.

For more information contact Axis Communications, +27 (0)11 548 6780, sasha.bonheim@axis.com, www.axis.com



Credit(s)




Share this article:
Share via emailShare via LinkedInPrint this page



Further reading:

Reinventing network camera security
Issue 1 2020, Axis Communications SA , CCTV, Surveillance & Remote Monitoring
Now in its seventh generation and celebrating its 20th anniversary, the Axis ARTPEC chip was launched in 1999 designed to optimise network video.

Read more...
Cloud-based fleet and driver management
Issue 1 2020, Graphic Image Technologies , CCTV, Surveillance & Remote Monitoring
Graphic Image Technologies (GIT) has announced the availability of a cloud-based dashcam designed to improve on-the-road behaviour and assist in improving fleet management.

Read more...
Axis gives a brighter future to children
Issue 1 2020, Axis Communications SA , Editor's Choice
Fully networked camera solution provides visibility and accountability, letting orphanage focus on what’s important – its children.

Read more...
Cathexis specialises in integration
Issue 1 2020, Cathexis Technologies , CCTV, Surveillance & Remote Monitoring
The integration of multiple systems is intrinsic and essential to the goal of creating an effective and efficient operational environment.

Read more...
Do wireless networks meet modern surveillance demands?
Issue 1 2020, Duxbury Networking, RADWIN , CCTV, Surveillance & Remote Monitoring
It is predicted that video will account for 15,1 zettabytes (1 zettabyte = 1 trillion gigabytes) of data annually, which is more than any other IoT application.

Read more...
Traffic doesn’t have to be this way
Issue 1 2020, Dahua Technology South Africa, Axis Communications SA , CCTV, Surveillance & Remote Monitoring
More effective traffic management is something that would save us all a lot of frustration and wasted time, and it’s one of the areas where AI and big data can have a significant impact.

Read more...
Dahua launches Hunter Series
Issue 1 2020, Dahua Technology South Africa , CCTV, Surveillance & Remote Monitoring
Dahua launches a new dual-PTZ camera that enables flexible and multi-scene panoramic monitoring.

Read more...
8 MP fisheye camera
Issue 1 2020, Dallmeier Electronic Southern Africa , CCTV, Surveillance & Remote Monitoring
Dallmeier’s new 8 MP fisheye camera combines AI-supported object classification and H.265 in a compact design.

Read more...
Using ANPR to enhance security
Issue 1 2020, Duxbury Networking , CCTV, Surveillance & Remote Monitoring
Deep learning and AI-based algorithms enable ANPR cameras and their associated software to detect and recognise number plates with an extremely high level of accuracy.

Read more...
AI supercharges surveillance
Issue 1 2020 , CCTV, Surveillance & Remote Monitoring
The ability to analyse live video through AI techniques means that untapped footage from existing, passive cameras can be used to identify patterns, trends and anomalies.

Read more...