[Editor's Note: This is the second in a series of three articles addressing the growing technology of megapixel video surveillance cameras. Upcoming installments (to be published on SecurityInfoWatch.com during March 2007) will cover topics of the relationship between megapixel cameras and storage/bandwidth needs and digital zoom versus mechanical pan/tilt/zoom.]
In Part 1 of this series, we said we would discuss compression, so let's start there. While there are many different types of compression-some of the more familiar being H.264, MPEG4 and MJPEG-there are basically two types: frame-by-frame and Temporal.
A Short Note on Compression
MJPEG is the most popular frame-by-frame compression technique, compressing each image in its entirety. It is widely deployed and easy to integrate with. The advantage of this technique is that it enables you to recreate images accurately and bandwidth use is predictable. The drawback is that by handling each image in its entirety, it is not very efficient in terms of bandwidth when there is little motion or activity.
Temporal is represented by popular compression methodologies like H.263, H.264 and MPEG4. These techniques are widely deployed in applications where the available network bandwidth is limited and low quality images will suffice. Temporal takes an image, called a "key frame," compresses it in its entirety, then for the next few images, only compresses and transmits things that change in the image. Every few images, it takes another key frame and repeats the process. The advantage of this technique is that by sending only changes to the key frame, you can save a lot of bandwidth and storage when there is very little motion or activity. One drawback of this technique is that only the key frame is a true "legal" picture. Another drawback is that motion results in a significant increase in bandwidth consumption, thereby reducing the bandwidth advantage over frame-by-frame compression.
To Megapixel or Not to Megapixel
But in reality, compression isn't significant for our following analysis, because the examples below will hold true as long as you aren't mixing apples and oranges. This article is about comparing Megapixel cameras with low-resolution cameras to see if and when deploying Megapixel makes sense. In that sense, we are simply comparing different size apples. So, for our analysis we will assume the customer wants the highest quality images available and will, therefore, use a frame-by-frame compression like MJPEG.
When does megapixel make sense? In Part 1, we talked about pixels-per-foot, which helps make the megapixel decision fairly straightforward. Let's use the same example, but we'll now add depth of coverage as well: we want to cover a parking lot with forensic detail (40 pixels/foot - see part 1 for an explanation of the different video quality levels, but this is the resolution at which you can recognize faces and license plates) and the lot is 100 feet wide, but now let's add that we need to cover multiple rows of cars at a depth of 60 feet. To do the math, we multiply the 100 foot width by the 40 pixels/foot to come up with 4,000 pixels. Then we multiply the 60 foot depth of field by 40 pixels/foot to come up with 2,400 pixels. We then multiply those two values (2,400 and 4,000) to produce the total number of pixels needed. In this case, that number is 9.6 million pixels, or 9.6 megapixels.
Megapixel Coverage vs. Conventional
We know from our previous discussion that there are a number of camera options to achieve forensic detail on this scene as shown in the examples at right. Let's now determine the bandwidth required for each option.