We present a wavelet-based near-lossless coder with L∞-error scalability. The method presented consists of a wavelet-based lossy layer encoder followed by multiple stages of residual refinements for L∞-error scalability. We introduce a successive refinement scheme in L∞-error sense for residual layers reminiscent of popular set-partitioning algorithms for embedded coding. The initial near-lossless error bound is attained by our previously proposed two-stage scheme which determines the bit-rate for the lossy layer 'on-the-fly' without any iteration. The resulting residual which is defined by the difference between the original and the initial near-lossless reconstruction is then further refined in L∞-error sense up to lossless reconstruction. This scheme provides a combination of L2-error embedded lossy reconstruction up to an automatically determined high-fidelity plus optional layers of scalable L∞-error. This may turn out to be particularly useful for scalable archival applications where the fidelity of reconstructions on the high-bit end needs to be strictly controlled.
We propose two approaches to scalable lossless coding of motion video. They achieve SNR-scalable bitstream up to lossless reconstruction based upon the subpixel-accurate MCTF-based wavelet video coding. The first approach is based upon a two-stage encoding strategy where a lossy reconstruction layer is augmented by a following residual layer in order to obtain (nearly) lossless reconstruction. The key advantages of our approach include an 'on-the-fly' determination of bit budget distribution between the lossy and the residual layers, freedom to use almost any progressive lossy video coding scheme as the first layer and an added feature of near-lossless compression. The second approach capitalizes on the fact that we can maintain the invertibility of MCTF with an arbitrary sub-pixel accuracy even in the presence of an extra truncation step for lossless reconstruction thanks to the lifting implementation. Experimental results show that the proposed schemes achieve compression ratios not obtainable by intra-frame coders such as Motion JPEG-2000 thanks to their inter-frame coding nature. Also they are shown to outperform the state-of-the-art non-scalable inter-frame coder H.264 (JM) lossless mode, with the added benefit of bitstream embeddedness.
We propose an integrated, wavelet based, two-stage coding scheme for lossy, near-lossless and lossless compression of medical volumetric data. The method presented determines the bit-rate while encoding for the lossy layer and without any iteration. It is in the spirit of "lossy plus residual coding" and consists of a wavelet-based lossy layer followed by an arithmetic coding of the quantized residual to guarantee a given pixel-wise maximum error bound. We focus on the selection of the optimum bit rate for the lossy coder to achieve the minimum total (lossy plus residual) bit rate in the near-lossless and the lossless cases. We propose a simple and practical method to estimate online the optimal bit rate and provide a theoretical justification for it. Experimental results show that the proposed scheme provides improved, embedded lossy, and lossless performance competitive with the best results published so far in the literature, with an added feature of near-lossless coding.