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Seafloor image compression using hybrid wavelets and directional filter banks

We present an efficient compression method based on the hybrid wavelets and directional filter banks (HWD), to achieve high compression efficiency while keeping visually pleasing reconstruction quality for underwater images. According to the characteristics of underwater images and the human vision system (HVS), an improved just noticeable distortion (JND) model is initially employed to adaptively remove the visual redundancy of underwater images in the HWD domain. The low-frequency coefficients are then quantized in the fixed length and encoded losslessly. The high-frequency coefficients are quantized by variable precision and fixed length method, and are coded by the difference reduction algorithm based on HWD trees. The experimental results show that the proposed compression algorithm provides both high coding efficiency and satisfactory reconstruction quality, which is highly desired for the transmission of underwater images at very low-bit rates.