Video Significance-Linked Connected Component Analysis
|MCVL Homepage||Department of Computer Engineering and Computer Science|
Department of Computer Engineering and Computer Science
University of Missouri-Columbia
Columbia, MO 65211
Video significance-linked connected component analysis (VSLCCA) is a very advanced video compression scheme developed at the Department of Computer Engineering and Computer Science at the University of Missouri-Columbia by Jozsef Vass, Bing-Bing Chai, and Xinhua Zhuang. It is based on our still image compression algorithm termed significance-linked connected component analysis (SLCCA) developed by Bing-Bing Chai, Jozsef Vass, and Xinhua Zhuang.
The main purpose of the file menu to load and save a new stream. It is possible to load a stream from the local disk, or from a remote location. In the letter case, the HTTP address of the stream should be specified.
There are few options that are available through options menu. The sequence can be displayed in doubled size, and can be played repeatedly. The sequence can also be stopped and the frame can be captured as a PPM image.
Download the original frames. Each of the 50 frames is 76032 bytes (144*176*3, where 144 is the number of rows, 176 is the number of pixels in each row and each frame has a red, green, and blue channel). When you are using a 28.8 kbps modem, to download the whole sequence might take approximately as long as 18 minutes. The display is a simple JAVA interface. To download the original sequence, click here
Here the performance of MPEG-1 and VSLCCA is compared. Two examples are given. In the first one, the frame rate is 5 frames-per-second (fps), and the required bit rate is 10k bit-per-second (bps). Thus the compression ratio is 152:1. In the second example, the frame rate is increased to 10 fps and the bit rate is increased to 24 kbps. This results in 129:1 compression ratio.
|5 fps, 10 kbps||MPEG-1||VSLCCA|| JAVA VSLCCA
|| 10 fps, 24 kbps || MPEG-1 || VSLCCA || JAVA VSLCCA
The VSLCCA algorithm is also very well suited for remote sensing data compression.
The JAVA version have been tested on the followings platforms:
The native version is currently running on SGI workstations (O2 running IRIX 6.3 and Octane running IRIX 6.4).
CECS Multimedia Communications and Visualization Laboratory