Listless set partitioning embedded block (LSK) and set partitioning embedded block (SPECK) are known for their low complexity and simple implementation. However, the drawback is that these block-based algorithms encode each insignificant subband by a zero. This generates many zeros at earlier passes because the number of significant coefficients at higher bitplanes is likely to be very few in a transformed image. An improved LSK (ILSK) algorithm that codes a single zero to several insignificant subbands is proposed. This reduces the length of the output bit string, encoding/decoding time and dynamic memory requirement at early passes. Furthermore, ILSK algorithm is coupled with discrete Tchebichef transform (DTT). This gives rise to a novel coder named as hierarchical listless DTT (HLDTT). The proposed HLDTT has desirable attributes like full embeddedness for progressive transmission, precise rate control for constant bit rate traffic and low complexity for low power applications. The performance of HLDTT is assessed using peak-signal-to-noise-ratio (PSNR) and structural-similarity-index-metric (SSIM). Extensive simulation conducted on various standard test images shows that HLDTT exhibits significant improvement in PSNR values from lower to medium bit rates. At the same time, HLDTT shows improvement in SSIM values on all bit rates.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2012.0295

Reduced memory, low complexity embedded image compression algorithm using hierarchical listless discrete tchebichef transform

In wavelet image compression using embedded quantization, visual quality can be improved by limiting the number of bits used to refine each significant coefficient to some maximum which is different for each sub-band. At a fixed bit rate, the bits saved are used to augment the number of coefficients coded. In this work, a refinement strategy for just noticeable degradation is obtained experimentally for a 5-scale wavelet decomposition, giving a specification for visually lossless quantization. For a range of higher compression ratios, psychovisual experimentation to determine viewer preferences produces a scheme for the allocation of refinement bits at low bit rates. The results are consistent between subjects and across a range of standard test images. The work is a step towards wavelet image coding in which the data stream is fully embedded for optimum visual quality.

Visual embedding of wavelet transform coefficients

This paper presents a listless implementation of wavelet based block tree coding (WBTC) algorithm of varying root block sizes. WBTC algorithm improves the image compression performance of set partitioning in hierarchical trees (SPIHT) at lower rates by efficiently encoding both inter and intra scale correlation using block trees. Though WBTC lowers the memory requirement by using block trees compared to SPIHT, it makes use of three ordered auxiliary lists. This feature makes WBTC undesirable for hardware implementation; as it needs a lot of memory management when the list nodes grow exponentially on each pass. The proposed listless implementation of WBTC algorithm uses special markers instead of lists. This reduces dynamic memory requirement by 88% with respect to WBTC and 89% with respect to SPIHT. The proposed algorithm is combined with discrete cosine transform (DCT) and discrete wavelet transform (DWT) to show its superiority over DCT and DWT based embedded coders, including JPEG 2000 at lower rates. The compression performance on most of the standard test images is nearly same as WBTC, and outperforms SPIHT by a wide margin particularly at lower bit rates.

Listless block-tree set partitioning algorithm for very low bit rate embedded image compression

In this paper, we propose a low bit rate video coding procedure in the discrete cosine transform (DCT) domain that is based in an embedded zerotree algorithm and uses decimation and interpolation. Theory for decimation/interpolation in the DCT domain is presented, and its implementation with fast algorithms is shown. Motivated by the compositing of several video sources in multipoint video conferencing, we propose a new method for single streams that uses the proposed DCT-decimation in the encoder and the corresponding DCT-interpolation in the decoder. Decimated video frames are encoded using an embedded zerotree and an adaptive arithmetic coder to improve the quality of the decoded videos. Zerotree coding is a progressive coding method that quantizes amplitudes of DCT coefficients of video frames into bit streams with increasing precision. Embedded coding scheme depends on coding a symbol by an adaptive arithmetic encoder as soon as the symbol is obtained by the zerotree coding. Zerotree coder gives flexibility of controlling the bit rate precisely at given target bit rate. Compared to conventional coding our proposed algorithm achieves peak signal-to-noise ratio improvements at low bit rate video coding.

Low Bit Rate Video Coding Using DCT-Based Fast Decimation/Interpolation and Embedded Zerotree Coding

This paper proposes an ECG signal compressor based on optimum quantization of discrete cosine transform (DCT) coefficients and Golomb-Rice coding. The ECG to be compressed is initially partitioned in blocks, and each DCT block is quantized using a quantization step size vector and a zeroing threshold vector. These vectors are defined so that the estimated entropy is minimized for a target distortion in the reconstructed signal or, alternatively, the distortion is minimized for a target entropy. The final step of the compressor is based on Golomb-Rice coding. To assess the performance of the compressor, records of the MIT-BIH Arrhythmia Database were compressed at various distortion levels, measured by the percent root-mean-square difference (PRD), and compression ratios (CR) were computed. An average CR of 10.4:1 was achieved for PRD equal to 2.5%.

Compression of ECG signals based on optimum quantization of discrete cosine transform coefficients and Golomb-Rice coding

We show that an efficient quantizer originally developed for wavelet compression can be applied to DCT coding with excellent results. We have implemented a system for block-based, embedded, progressive, DCT image compression which makes use of the embedded zerotree wavelet (EZW) algorithm of Shapiro (1993). The image is partitioned into a number of distinct square blocks and the DCT applied to each of these individually. The coefficients are then rearranged into a sub-band structure which outwardly resembles a wavelet transformed image, with the number of sub-bands being related to the size of the DCT used. The zerotree coding algorithm is then employed to quantize the coefficients. The system outperforms the embedded zerotree wavelet scheme in a rate-distortion sense, with good performance from lossless (to the fixed point DCT precision) to high compression. The system gives the best trade between accuracy and high frequency ringing with a DCT block size of 16/spl times/16, corresponding to four sub-band scales.

Zerotree coding of DCT coefficients

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Zerotree coding of DCT coefficients