``Texture-plus-depth'' has become a popular coding format for multiview image compression, where a decoder can synthesize images at intermediate viewpoints using encoded texture and depth maps of closest captured view locations via depth-image-based rendering (DIBR). As in other resource-constrained scenarios, limited available bits must be optimally distributed among captured texture and depth maps to minimize the expected signal distortion at the decoder. A specific challenge of multiview image compression for DIBR is that the encoder must allocate bits without the knowledge of how many and which specific virtual views will be synthesized at the decoder for viewing. In this work, we derive a cubic synthesized view distortion model to describe the visual quality of an interpolated view as a function of the view's location. Given the model, one can easily find the virtual view location between two coded views where the maximum synthesized distortion occurs. Using a multiview image codec based on a shape-adaptive wavelet transform, we show how optimal bit allocation can be performed to minimize the upper bound of the view synthesis distortion at any intermediate viewpoint. Our experimental results show that the optimal bit allocation can outperform a common uniform bit allocation scheme by up to a 1.0 dB gain in coding performance, while simultaneously being competitive to a state-of-the-art H.264 codec.