A unified source coding method is highly desired for many systems that deal with images diversifying from 1 bit/pel bi-level documents to SHD (Super High Definition) images of 12 bit/pel for each color component, and progressive coding that allows images to be reconstructed with increasing pixel accuracy or spatial resolution is essential for many applications including World Wide Web, medical images archive, digital library, pre-press and quick look applications. In this paper, we propose a unified continuous-tone and bi-level image coding method with pyramidal and progressive transmission feature. Hierarchical structure is constructed by interlacing subsampling, and each hierarchy is encoded by DPCM combined with reduced Markov model. Simulation results show that the proposed method is a little inferior than JBIG for bi-level image coding but can achieve better lossless compression ratio for gray-level image coding than CREW, in which wavelet transform is exploited to construct hierarchical structure.

Reversible variable length codes (RVLCs), which make instantaneous decoding possible in both forward and backward directions, are exploited to code data stream in noisy enviroments. Because there is no redundancy in code words of RVLCs, RVLCs are suitable for very low bit-rate video coding. Golomb-Rice code, one of variable length code for infinite number of symbols, is widely used to encode exponentially distributed non-negative integers. We propose a reversible variable length code by modifying Golomb-Rice code, which is called parity check reversible Golomb-Rice code and abbreviated to P-RGR code. P-RGR code has the same code length distribution as GR code but can detect one-bit error in any arbitrary position of the code stream. The sets of P-RGR code words in both directions are identical so that they can be constructed by nearly the same algorithm. Furthermore, this paper also gives a general construction method for all instantaneously decodable RGR codes.

In this paper, we present a method to combine lapped transforms with various downsampling factors. The factor is changed depending on a local feature of a given signal, and it can be realized by using time-domain lapped transforms. In image coding application, our method maintains good image coding performance for a wide range of bitrates and fills the gap between undersampled and critically-/oversampled systems.