Enhancing LTW image encoder with perceptual coding and GPU-optimized 2D-DWT transform

TLDR: This work proposes an optimization of the E_LTW encoder with the aim to increase its R/D performance through perceptual encoding techniques and reduce the encoding time by means of a graphics processing unit-optimized version of the two-dimensional discrete wavelet transform.

Abstract: When optimizing a wavelet image coder, the two main targets are to (1) improve its rate-distortion (R/D) performance and (2) reduce the coding times. In general, the encoding engine is mainly responsible for achieving R/D performance. It is usually more complex than the decoding part. A large number of works about R/D or complexity optimizations can be found, but only a few tackle the problem of increasing R/D performance while reducing the computational cost at the same time, like Kakadu, an optimized version of JPEG2000. In this work we propose an optimization of the E_LTW encoder with the aim to increase its R/D performance through perceptual encoding techniques and reduce the encoding time by means of a graphics processing unit-optimized version of the two-dimensional discrete wavelet transform. The results show that in both performance dimensions, our enhanced encoder achieves good results compared with Kakadu and SPIHT encoders, achieving speedups of 6 times with respect to the original E_LTW encoder.