Proceedings Article | 15 October 2015
KEYWORDS: Satellites, Image compression, Image transmission, Image quality, Telecommunications, Image restoration, Discrete wavelet transforms, Solitons, Computer programming, Satellite imaging
The use of images from earth observation satellites is spread over different applications, such as a car navigation systems and a disaster monitoring. In general, those images are captured by on board imaging devices and must be transmitted to the Earth using a communication system. Even though a high resolution image can produce a better Quality of Service, it leads to transmitters with high bit rate which require a large bandwidth and expend a large amount of energy. Therefore, it is very important to design efficient communication systems. From communication theory, it is well known that a source encoder is crucial in an efficient system. In a remote sensing satellite image transmission, this efficiency is achieved by using an image compressor, to reduce the amount of data which must be transmitted. The Consultative Committee for Space Data Systems (CCSDS), a multinational forum for the development of communications and data system standards for space flight, establishes a recommended standard for a data compression algorithm for images from space systems. Unfortunately, in the satellite communication channel, the transmitted signal is corrupted by the presence of noise, interference signals, etc. Therefore, the receiver of a digital communication system may fail to recover the transmitted bit. Actually, a channel code can be used to reduce the effect of this failure. In 2002, the Luby Transform code (LT-code) was introduced and it was shown that it was very efficient when the binary erasure channel model was used. Since the effect of the bit recovery failure depends on the position of the bit in the compressed image stream, in the last decade many e
orts have been made to develop LT-code with unequal error protection. In 2012, Arslan et al. showed improvements when LT-codes with unequal error protection were used in images compressed by SPIHT algorithm. The techniques presented by Arslan et al. can be adapted to work with the algorithm for image compression recommended by CCSDS. In fact, to design a LT-code with an unequal error protection, the bit stream produced by the algorithm recommended by CCSDS must be partitioned in M disjoint sets of bits. Using the weighted approach, the LT-code produces M different failure probabilities for each set of bits, p1, ..., pM leading to a total probability of failure, p which is an average of p1, ..., pM. In general, the parameters of the LT-code with unequal error protection is chosen using a heuristic procedure. In this work, we analyze the problem of choosing the LT-code parameters to optimize two figure of merits: (a) the probability of achieving a minimum acceptable PSNR, and (b) the mean of PSNR, given that the minimum acceptable PSNR has been achieved. Given the rate-distortion curve achieved by CCSDS recommended algorithm, this work establishes a closed form of the mean of PSNR (given that the minimum acceptable PSNR has been achieved) as a function of p1, ..., pM. The main contribution of this work is the study of a criteria to select the parameters p1, ..., pM to optimize the performance of image transmission.
