Decoding complexity constrained rate-distortion optimization for the compression of concentric mosaics

In this paper, a quantitative measure of decoding complexity for compressed image based scene representations is defined and is used to optimize the rate-distortion trade off during encoding subject to a decoding complexity constraint. The image-based representation used in this work is the concentric mosaic. Due to the huge amount of image data to be managed and the demands on just-in-time decoding and rendering of the compressed bit-stream, challenges arise in using concentric mosaics on low-end devices and for streaming applications over the Internet or other low bit-rate networks. Our approach allows for maximizing quality with respect to the available computational resources at the decoder and the bit rate.