Optimum design of vector-quantized subband codecs

This paper focuses on subband coding schemes based on critically decimated paraunitary filter banks. An additional network with matrix A is introduced on the decoder side. We show here how to optimize its coefficients jointly with the quantization steps in order to reduce the reconstruction mean square error (MSE) on the output signal due to quantization and filtering. This optimization is performed under bit-rate constraint. Of course, the resulting overall MMSE filter bank (including A ≠ I m ) does not allow perfect reconstruction (PR), but the signal-to-noise ratio (SNR) is remarkably better than for the PR solutions. The main advantage of such an approach is to preserve the original structure of the filter bank while improving the SNR. Here, we apply the method to modulated filters which can be implemented at very low cost. Solutions are given by comparing rate-distortion curves for various forms of A, several paraunitary modulated filter banks, and two bit-rate measures.

In many source and data compression schemes, information relating to positions of high-energy samples or areas of importance often needs to be relayed to the decoder. The error resilient positional code (ERPC) is an efficient fixed-rate coding scheme for encoding such positional information, or, equivalently, sparse binary data patterns. It has also been designed with good channel error robustness properties, such that the decoded data quality degrades gracefully with worsening channel conditions, without the possibility of catastrophic breakdown or loss of sync. In this work, the coding efficiency of the ERPC is compared to a few other standard schemes. It is found to be efficient and its error extension in terms of the expected number of samples corrupted per bit error is reported and shown to be low and noncatastrophic. The ERPC is applied to an image coding example based on subband coding and vector quantization. It results in an efficient adaptive codec capable of operating in harsh channel conditions, without the aid of error correction or detection techniques. >

Transform image coding using scalar quantization, pyramid vector quantization (PVQ), and generalized Lloyd algorithm vector quantization (VQ) and subband image coding using scalar quantization and pyramid vector quantization are considered. In a simulation study at low bit rates (0.5 bit/pel) the transform VQ coder generally provided the largest peak-signal-to-noise ratio (PSNR), although the PVQ subband coder was superior for some images. At larger encoding rates (for which, because of complexity, the generalized Lloyd algorithm VQ was not considered) the scalar-quantizer subband coder generally yielded larger PSNR than did the scalar-quantizer transform coder. The PVQ transform and subband coders provided similar values of PSNR, but the subband coded image had less blockiness than the transform-coded image. >

We discuss a method of signal analysis — empirical mode decomposition, and also its modification — complementary ensemble empirical mode decomposition. Both methods are used to research the reconstruction of a speech signal by the means of intrinsic mode functions that were received during the decomposition. Researches were performed using two English databases of speech signals which contain speech sentences. Sentences are pronounced by male and female speakers. We utilized next objective indexes for our investigations: relative power and root mean square error of reconstruction, quality index PESQ and intelligibility index SNRloss. Results of a computational experiment are given. These results demonstrate a high quality of the signal reconstruction at its full restoration, and also advantages of the complementary decomposition in comparison with the customary decomposition.

Filter banks based on recursive filters have recently been applied with success in subband coding of still images [1, 2]. Their main feature, low computational complexity, make these filter banks extremely attractive for video coding applications. In. this paper we demonstrate the suitability of these filter banks in low bit rate image sequence coders operating in the 64 —200 Kbps range. In particular we compare the performance of two types of recursive filter banks with that of a more traditional one based on quadrature mirror FIR filters (QMF). It is shown that the performance of our hR based systems is comparable to that of the more complex FIR based systems. Also, we show that the encoding strategy of CCITT's reference model no. 7 can be adapted successfully to fit into our subband coding scheme. Finally we discuss alternative approaches to motion estimation in hybrid image sequence coders and show preliminary results in the context our video subband coder.

We propose a reconstruction method for coherence holography using deep neural networks. cGAN and U-NET models were developed to reconstruct 3D complex objects from recorded interferograms. Our proposed methods, dubbed deep coherence holography (DCH), predict the non-diffracted fields or the sub-objects included in the 3D object from the captured interferograms, yielding better reconstructed objects than the traditional analytical imaging methods in terms of accuracy, resolution, and time. The DCH needs one image per sub-object as opposed to N images for the traditional sin-fit algorithm, and hence the total reconstruction time is reduced by N×. Furthermore, with noisy interferograms the DCH amplitude mean square reconstruction error (MSE) is 5×104× and 104× and phase MSE is 102× and 3×103× better than Fourier fringe and sin-fit algorithms, respectively. The amplitude peak signal to noise ratio (PSNR) is 3× and 2× and phase PSNR is 5× and 3× better than Fourier fringe and sin-fit algorithms, respectively. The reconstruction resolution is the same as sin-fit but 2× better than the Fourier fringe analysis technique.

After a short review of IIR-based subband coders, we describe the features of a software implementation of an efficient image subband coder (SBC). The efficiency of an SBC is heavily dependent upon the filter bank implementation. Experience has shown that at least 90% of the execution time of SBCs is spent in the filter bank. First, we present our implementation based on extremely simple multiplier-free IIR filters. Subsequently, we discuss the implementation task from a programmer's point of view, emphasizing the algorithm implementation using only integer arithmetic. The experiments show that our IIR SBC's execution time is ten times faster than that of an efficient SBC based on FIR filter banks. Furthermore, our codes is twice as fast as the July 91 release of the Free Software Foundation's JPEG implementation, while maintaining comparable performance; our SBC- coded images had somewhat higher signal to noise ratio than those coded with JPEG at the same bit rate. The subjective quality was found to be comparable.

Single-Cell Map of Childhood Acute Myeloid Leukaemia Using Variational Auto-Encoders

Results of psychophysical experiments on human vision conducted in the last three decades indicate that the eye performs a multichannel decomposition of the incident images. The paper presents a subband vector quantization algorithm that employs hexagonal filter banks. The hexagonal filter bank provides an image decomposition similar to what the eye is believed to do. Consequently, the image coder is able to make use of the properties of the human visual system and produce compressed images of high quality at low bit rates. A systematic approach is presented for optimal allocation of available bits among the subbands and also for the selection of the size of the vectors in each of the subbands. >

A new lattice structure is described. It is capable of implementing all paraunitary two-channel filter banks where the filters have complex coefficients and yield symmetric wavelet bases. This lattice structure, while being a general design method, can also be used to actually design the filter bank. These filter banks are, in fact, a special case of multifilter banks and can also be related to Golay-Rudin-Shapiro complementary polynomial pairs. The applications of such filter banks are to be found in subband coding and communications systems.

Reduction of transients during lifting based spatial switching of two-channel filter banks

We present a practical video coding algorithm for use at very low bit rates. For efficient coding at very low bit rates, it is important to intelligently allocate bits within a frame, and so a powerful variable-rate algorithm is required. We use vector quantization to encode the motion-compensated residue signal in an H.263-like framework. For a given complexity, it is well understood that structured vector quantizers perform better than unstructured and unconstrained vector quantizers. A combination of structured vector quantizers is used in our work to encode the video sequences. The proposed codec is a multistage residual vector quantizer, with transform vector quantizers in the initial stages. The transform-VQ captures the low-frequency information, using only a small portion of the bit budget, while the later stage residual VQ captures the high-frequency information, using the remaining bits. We used a strategy to adaptively refine only areas of high activity, using recursive decomposition and selective refinement in the later stages. An entropy constraint was used to modify the codebooks to allow better entropy coding of the indexes. We evaluate the performance of the proposed codec, and compare this data with the performance of the H.263-based codec. Experimental results show that the proposed codec delivered significantly better perceptual quality along with better quantitative performance.

The modified DFT (MDFT) filter bank is a highly efficient pseudo-QMF filter bank with almost perfect reconstruction. It has been shown that the MDFT filter bank provides a computational efficiency which is comparable with or in some cases even higher than that of the well-known cosine modulated filter bank. Additionally, the MDFT filter bank opens new applications as subband coding or as a transmultiplexer filter bank. The paper shows how almost perfect reconstruction is achieved in the MDFT filter bank, i.e. how adjacent-spectrum aliasing is cancelled, how nonadjacent-spectrum is suppressed, and how amplitude distortions are minimized. >

In positron emission tomography (PET) imaging, the whole body reconstruction is not required if the region of interest (ROI) is only a part of the object. This paper researched a local image reconstruction algorithm based on the PI-lines, and proposed the derivative-backprojection-Hilbert (DBH) algorithm which can use the incomplete PET projection data to achieve accurate reconstruction of ROI. We designed simulation experiments to evaluate the performance of the DBH algorithm with thorax model as the object of PET image reconstruction, and compared root mean square error (RMSE) of DBH reconstruction and RMSE of filtered backprojection (FBP) reconstruction from simulations data sets with and without noise. The result shows that DBH algorithm has advantages over traditional FBP algorithm, the RMSE decreases by 49.07% and 51.19% with the coincidence events number of 20 million and 40 million, respectively. Compared with traditional maximum-likelihood expectation-maximization (ML-EM), the local iteration algorithm which uses DBH reconstruction as the initial image produces a better reconstructed image at fewer iterations with the coincidence events number of 60 million. DBH algorithm is expected to be applied to fast two-dimensional local image reconstruction and optimize the local iterative reconstruction algorithm in clinical diagnosis.

Using filter bank property to simplify the calculations of Empirical Mode Decomposition