This paper proposes a Tone Mapping (TM) approach converting a High Dynamic Range (HDR) image into a Low Dynamic Range (LDR) image while preserving as much information of the HDR image as possible to ensure a good LDR image visual quality. This approach is based on a separable near optimal lifting scheme using an adaptive powerful prediction step. The latter relies on a linear weighted combination depending on the neighboring coefficients extracting then the relevant finest details in the HDR image at each resolution level. Moreover the approximation and detail coefficients are modified according to the entropy of each subband. The pixel's distribution of the coarse reconstructed LDR image is then adjusted according to a perceptual quantizer with respect to the human visual system using a piecewise linear function. Simulation results provide good results, both in terms of visual quality and TMQI metric, compared to existing competitive TM approaches.