Low-bit-rate coding of underwater video using wavelet-based compression algorithms

Recent advances in autonomous underwater vehicle (AUV) and underwater communication technology have promoted a surge of research activity within the area of signal and information processing. A new application is proposed herein for capturing and processing underwater video onboard an untethered AW, then transmitting it to a remote platform using acoustic telemetry. Since video communication requires a considerably larger bandwidth than that provided by an underwater acoustic channel, the data must be massively compressed prior to transmission from the AUV. Past research has shown that the low contrast and low-detailed nature of underwater imagery allows for low-bit-rate coding of the data by wavelet-based image-coding algorithms. In this work, these findings have been extended to the design of a wavelet-based hybrid video encoder which employs entropy-constrained vector quantization (ECVQ) with overlapped block-based motion compensation. The ECVQ codebooks were designed from a statistical source model which describes the distribution of high subband wavelet coefficients in both intraframe and prediction error images. Results indicate that good visual quality can be achieved for very low bit-rate coding of underwater video with our algorithm.