Complex spatial filters for image deconvolution

The history and principles of image distortion correction by means of holographic spatial filtering are reviewed. Both predetection and postdetection filtering are considered. These and other principle applications of complex spatial filtering are assessed. The major problem areas are discussed, along with possible solutions.     

Efficient implementation of lifting-based discrete wavelettransform

A recursive architecture for implementing the lifting-based discrete wavelet transform is proposed. Processing of the transform stages is interleaved, improving the hardware utilisation and efficiency, by exploiting the wavelet decimation structure     

Complex, linear-phase filters for efficient image coding

With the exception of the Haar basis, real-valued orthogonal wavelet filter banks with compact support lack symmetry and therefore do not possess linear phase. This has led to the use of biorthogonal filters for coding of images and other multidimensional data. There are, however, complex solutions permitting the construction of compactly supported, orthogonal linear phase QMF filter banks. By explicitly seeking solutions in which the imaginary part of the filter coefficients is small enough to be approximated to zero, real symmetric filters can be obtained that achieve excellent compression performance     

On optimal analysis/synthesis filters for coding gain maximization

We consider the use of pre and postfilters in conjunction with M-channel, uniform-band paraunitary (orthonormal) filter banks. We show that given any orthonormal filter bank, the pre and postfilters that maximize the coding gain are determined entirely by the power spectrum of the input process regardless of the details of the orthonormal filter blank (which could be FIR, IIR, or even the ideal brickwall filter bank). The optimized coding gain, however, depends on the prefilter as well as the sandwiched orthonormal filter bank. The coding gain improvement due to pre and postfiltering is often significant as we demonstrate with numerical examples and comparisons. The validity of our results depends strongly on the orthonormality property of the filter bank in between the pre and postfilters. In the nonorthonormal case, most of these results are not true, as is demonstrated     

Two fast architectures for the direct 2-D discrete wavelettransform

We propose two architectures for the direct two-dimensional (2-D) discrete wavelet transform (DWT). The first one is based on a modified recursive pyramid algorithm (MRPA) and performs a “"nonstandard” decomposition (i.e., Mallat's (1989) tree) of an N×N image in approximately 2N²/3 clock cycles (ccs). This result consistently speeds up other known architectures that commonly need approximately N² ccs. Furthermore, the proposed architecture is simpler than others in terms of hardware complexity. Subsequently, we show how “symmetric”/“anti-symmetric” properties of linear-phase wavelet filter bases can be exploited in order to further reduce the VLSI area. This is used to design a second architecture that provides one processing unit for each level of decomposition (pipelined approach) and performs a decomposition in approximately N²/2 ccs. In many practical cases, even this architecture is simpler than general MRPA-based devices (having only one processing unit)     

DGT与DCT在图像编码中的性能比较

介绍了二维实值离散Gabor变换（RDGT）的快速算法,并着重探讨了二维实值离散Gabor变换与二维离散余弦变换在图像编码中的性能及差异。     

Jointly optimized spatial prediction and block transform for video and image coding

This paper proposes a novel approach to jointly optimize spatial prediction and the choice of the subsequent transform in video and image compression. Under the assumption of a separable first-order Gauss-Markov model for the image signal, it is shown that the optimal Karhunen-Loeve Transform, given available partial boundary information, is well approximated by a close relative of the discrete sine transform (DST), with basis vectors that tend to vanish at the known boundary and maximize energy at the unknown boundary. The overall intraframe coding scheme thus switches between this variant of the DST named asymmetric DST (ADST), and traditional discrete cosine transform (DCT), depending on prediction direction and boundary information. The ADST is first compared with DCT in terms of coding gain under ideal model conditions and is demonstrated to provide significantly improved compression efficiency. The proposed adaptive prediction and transform scheme is then implemented within the H.264/AVC intra-mode framework and is experimentally shown to significantly outperform the standard intra coding mode. As an added benefit, it achieves substantial reduction in blocking artifacts due to the fact that the transform now adapts to the statistics of block edges. An integer version of this ADST is also proposed.     

Pruned discrete Tchebichef transform for image coding in wireless multimedia sensor networks

After the successful development of the discrete cosine transform (DCT) especially in audio, image and video coding, many state-of-the-arts DCT-based fast algorithms have been developed. However, these algorithms are floating-point and are implemented with high algorithmic complexity and memory intensive. Therefore, they consume large system resources. In particular, those requirements pose a serious limitation on multimedia applications in resource-constrained systems, such as wireless multimedia sensor networks (WMSNs). In this paper we investigate an alternative to DCT transform which known as discrete Tchebichef transform (DTT). Despite its good energy compaction property, low algorithmic complexity and low memory requirements, the DTT is potentially unexploited in the literature. To further reduce its complexity and memory requirements, in this paper we propose a pruned version of DTT (P-DTT). Simulation results show that P-DTT requires a reduced number of arithmetic operations, energy consumption and memory. And it has at the same time competitive compression efficiency compared with Loeffler-DCT and exact DTT. The proposed P-DTT transform is a viable option for image compression and/or communication over WMSNs.     

A radar target discrimination scheme using the discrete wavelettransform for reduced data storage

A correlative radar target discrimination scheme using the transient scattered-field response is proposed. This scheme uses a one-dimensional discrete wavelet transform on the temporal response to reduce the amount of data that must be stored for each anticipated aspect angle. Experimental results show that a reduction in stored data of sixteen to one still allows accurate discrimination in adverse noise situations with signal-to-noise ratios as low as -5 dB     

Comparing orthonormal matrices for two-dimensional image transform coding by means of the gain distortion function

The gain distortion function is defined as a performance measure for the comparison of orthonormal transforms on the basis of the rate distortion theory. It estimates the number of bits per picture element that can be saved by transform coding. Gain distortion functions were computed for several transforms of the dimension 8 × 8.     

A comparison of the Hartley, Cas-Cas, Fourier, and discrete cosinetransforms for image coding

The coding method used for the comparison utilizes a marginal bit-allocation scheme and Lloyd-Max quantizer. Gamma, Laplacian, and Gaussian models are compared for the distribution of the transform coefficients. The discrete cosine transform outperforms the other three transforms based on the mean-square quantization error     

On the influence of the phase of conjugate quadrature filters insubband image coding

The influence of the phase of conjugate quadrature filters (CQFs) on the performances of a subband coding scheme is analyzed. When the filter length is short, the phase characteristic has virtually no influence on the peak signal-to-noise ratio (PSNR)/bit rate results and on the performance of postprocessing algorithms such as edge detection.     

Coding for intersymbol interference channels-combined coding andprecoding

This paper describes a new coding scheme for transmission over intersymbol interference (ISI) channels. This scheme, called ISI coding, combines trellis coding with precoding (used to combat ISI). Like the recently introduced precoding scheme of Laroia, Tretter, and Farvardin (LTF), the ISI coder makes it possible to achieve both shaping and coding gains over ISI channels. By combining coding and precoding, however, the ISI coder makes the “precoding loss” independent of the number of coset partitions used to generate the trellis code. At high rates (large signal-to-noise ratio (SNR)), this makes it possible to approach the Shannon capacity of an ISI channel. The V.34 (formerly V.fast) international modem standard for high-speed (up to 28.8 kb/s) communication over voice-band telephone lines uses the version of the ISI coder described in Section IV of this paper     

Regularization for uniform spatial resolution properties in penalized-likelihood image reconstruction

Traditional space-invariant regularization methods in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform spatial resolution properties. The local point spread functions that quantify the smoothing properties of such estimators are space-variant, asymmetric, and object-dependent even for space-invariant imaging systems. We propose a new quadratic regularization scheme for tomographic imaging systems that yields increased spatial uniformity and is motivated by the least-squares fitting of a parameterized local impulse response to a desired global response. We have developed computationally efficient methods for PET systems with shift-invariant geometric responses. We demonstrate the increased spatial uniformity of this new method versus conventional quadratic regularization schemes in simulated PET thorax scans.     

Computation of the coding gain for subband coders

A procedure to evaluate the coding gain for 2-D subband systems is explicitly presented. The technique operates in the signal domain and requires the knowledge of the input process auto-correlation function. Both the case of uniform subband and pyramid decomposition are considered. In the case of a separable input process spectrum, the evaluation can be performed by considering appropriately defined 1-D systems, thus, making the procedure very convenient in terms of computational complexity. Using a model that has been recently derived for difference images in motion-compensated image sequence coders, we compare the performance of several filter banks and transform coders in terms of coding gain and asymptotic rate-distortion figures. The results for intraframe and interframe coding show that uniform subband coders can have a performance superior to that of transform coders. Pyramidal schemes appear to have a slightly worse performance     

Iterative Wiener filters for image restoration

The iterative Wiener filter, which successively uses the Wiener-filtered signal as an improved prototype to update the covariance estimates, is investigated. The convergence properties of this iterative filter are analyzed. It has been shown that this iterative process converges to a signal which does not correspond to the minimum mean-squared-error solution. Based on the analysis, an alternate iterative filter is proposed to correct for the convergence error. The theoretical performance of the filter has been shown to give minimum mean-squared error. In practical implementation when there is unavoidable error in the covariance computation, the filter may still result in undesirable restoration. Its performance has been investigated and a number of experiments in a practical setting were conducted to demonstrate its effectiveness     

Context conditioning and run-length coding for hybrid, embeddedprogressive image coding

An analysis of spatial context conditioning and run-length coding in embedded progressive, wavelet-based image coding is presented. The analysis shows that run-length coding of certain context subsequences is superior to pure entropy coding, both in terms of coding performance and of execution speed. Based on these considerations, a novel, intuitive context conditioning scheme using a spatial distance model to describe the statistics of significant coefficients is proposed. The results for the proposed coding scheme are competitive to the best coding schemes found in the literature.     

High voltage gain CMOS OTA for micropower SC filters

The letter describes a single stage operational transconductance amplifier (OTA) with cascoded output transistors, designed for micropower switched-capacitor filters. The device features high voltage gain (>90 dB) under capacitive load, large output swing, very low power consumption (5 ?W at 3 V supply voltage for 100 kHz bandwidth with 10 pF load) and reduced circuit area (<0.1 mm2).     

Graphics image coding for freeze-frame videoconferencing

A technique is presented for coding images that are bilevel in nature but have been captured in continuous-tone format. Following various stages of image processing, a three-level image is generated, and compressed to about 0.1 to 0.2 b/pixel. The technique has been implemented in the IBM freeze-frame videoconferencing system     

Vector-scalar classification for transform image coding

This paper introduces vector-scalar classification (VSC) for discrete cosine transform (DCT) coding of images. Two main characteristics of VSC differentiate it from previously proposed classification methods. First, pattern classification is effectively performed in the energy domain of the DCT subvectors using vector quantization. Second, the subvectors, instead of the DCT vectors, are mapped into a prescribed number of classes according to a pattern-to-class link established by scalar quantization. Simulation results demonstrate that the DCT coding systems based on VSC are superior to the other proposed DCT coding systems and are competitive compared to the best subband and wavelet coding systems reported in the literature.