This paper studies a new method for wavelet-based image denoising which is translation invariant (TI) and rotation invariant (RI). These invariances are crucial in image denoising and, more generally, may play important roles in image modeling. In contrast to other approximately RI methods, like the steerable pyramid, our new method employs standard separable wavelet bases in conjunction with a pseudo-circular image rotation. This scheme does not involve interpolation and hence the observation model (likelihood function) is invariant under this rotation. The superiority of our new method with respect to existing TI (non-RI) techniques is supported by experiments.