Godkända
Hårdvarueffektiv förlustfri bildkompression i realtid
Axel Jonsson (2013) och Måns Åhlander (2013)
Start
2018-01-15
Presentation
2018-05-18 11:15
Plats:
E:2349
Avslutat:
2018-05-31
Examensrapport:
Sammanfattning
When transmitting data it is often desired to lower the bitrate in the transmission. In cameras with a high resolution and high capturing rate the bitrate in the transmission is high and it is desired to lower this bitrate. Some constraints were put on the compression techniques, no information could be lost in the compression, the compression should not introduce more delay than it takes to capture a frame and that the compression techniques should have as small hardware requirements as possible. Due to these limitations the compression techniques were limited to use one frame at a time for the compression. One exception of this was done where it was tested to see if the compression ratio would be improved when compressing a frame using information from the frame before. How the transmission in a single directional transmission link with compressed data could be done in a safe way has also been investigated during this thesis. The compression techniques in this paper are two-step based compression techniques called linear prediction coding. The first step in the techniques is to predict the pixel values in the image, the second step is to encode the prediction error. In order to recover the image, these codes need to be decoded to recover the prediction error which can then be used to reconstruct the image. This is an efficient compression technique due to that there are much redundant information in an image and instead of encoding each pixel value it is more efficient to encode the differences between pixels. The difference contains the same information but may be encoded using shorter codewords. The average resulting compressing ratios for the techniques presented in this paper achieves a compression ratio close to 40% when compression raw image data. It was noted that the compression techniques performed better when compressing images with less visual structure. If simple noise reduction techniques are applied to the image to compress, the compression techniques may improve their compression ratio with over 10%. Another way to improve the compression is presented in this paper and it is done by measuring the noise in the image and then allowing some quantization error based on this measurement. A solution of how to transmit data in packets in a safe way from the encoder to the decoder have been suggested. Each packet contains a header field and a data field. The prediction errors are encoded in the data field and the number of symbols encoded in the data field are represented in the header field. These two got a fixed number of bytes.
Handledare: Imran Iqbal (Axis) och Stefan Höst (EIT)
Examinator: Maria Kihl (EIT)