Quantization index modulation (QIM) is a computationally efficient method of informed watermarking. However, the original method is particularly sensitive to variations in the amplitude of the signal. Previously, we proposed using a modification of Watson's perceptual model to adaptively adjust the quantization index step size. This simultaneously improved both the robustness and fidelity of the watermarked image and, most importantly, provided invariance (to a large degree) to valumetric scaling. Contemporaneously, rational dither modulation was proposed as an alternative QIM with valumetric invariance. In this paper, we combine the two methods and compare the performance of the new algorithm with our previous results. Experimental results demonstrate that the new algorithm outperforms the previous algorithms over the entire range of valumetric scale factors, albeit at the expense of a small decrease in fidelity. However all algorithms have a superior performance and improved fidelity compared with QIM