Method, apparatus and computer readable medium for encoding an image

Abstract

A method, apparatus and a computer readable storage medium for processing an image decomposed into a plurality of bands having additional neural network based lifting steps compared to the conventional wavelet transform. The additional lifting steps improve coding efficiency by reducing residual redundancy (aliasing information) amongst the wavelet subbands and improve visual quality for reconstructed images at reduced resolutions. The proposed approach involves two neural network steps, a high-to-low step followed by a low-to-high step. The high-to-low step suppresses aliasing in the low-pass band by using the detail bands at the same resolution, while the low-to-high step aims to further remove redundant information from the detail bands so as to achieve higher energy compaction. The networks are applied uniformly for all levels in the decomposition and to all the bit-rates of interest, leading to a fully scalable system with relatively low complexity. By selectively including an aliasing suppression term during training, the visual quality of the LL bands at different resolutions can be enhanced while achieving improved coding efficiency.

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