David W. Redmill

Low complexity two-dimensional digital filters using unconstrained SPT term allocation

Previous work by the authors has demonstrated how circularly symmetric and diamond-shaped low-pass linear phase 2-D FIR filters can be designed using coefficients comprising the sum or difference of two signed power-of-two (SPT) terms. This has employed a minimax error criterion in conjunction with an optimisation process based on the use of genetic algorithms. The resulting filters exhibit superior performance to those designed using other methods reported such as simulated annealing and linear programming. This paper extends this work by demonstrating the further improvements possible if the constraints are relaxed, such that only the overall number of SPT terms is constrained, while the distribution between filter coefficients is unconstrained.

The EREC: an error-resilient technique for coding variable-length blocks of data

Many source and data compression schemes work by splitting the input signal into blocks and producing variable-length coded data for each block. If these variable-length blocks are transmitted consecutively, then the resulting coder is highly sensitive to channel errors. Synchronization code words are often used to provide occasional resynchronization at the expense of some added redundant information. This paper introduces the error-resilient entropy code (EREC) as a method for adapting existing schemes to give increased resilience to random and burst errors while maintaining high compression. The EREC has been designed to exhibit graceful degradation with worsening channel conditions. The EREC is applicable to many problems and is particularly effective when the more important information is transmitted near the start of each variable-length block and is not dependent on following data. The EREC has been applied to both still image and video compression schemes, using the discrete cosine transform (DCT) and variable-length coding. The results have been compared to schemes using synchronization code words, and a large improvement in performance for noisy channels has been observed.

Multiple description video coding based on zero padding

This paper proposes a simple multiple description video coding approach based on zero padding theory. It is completely based on pre- and post-processing, which require no modifications to the source codec. Redundancy is added by padding zeros in the DCT domain, which results in interpolation of the original frame and increases correlations between pixels. Methods based on 1D and 2D DCT are presented. We also investigate two sub-sampling methods, which are interleaved and quincunx, to generate multiple descriptions. Results are presented for two zero padding approaches using H.264, which shows that the 1D approach performs much better than 2D padding techniques, at a much lower computational complexity. For 1D zero padding, results show that interleaved sub-sampling is better than quincunx.

A Novel Secure H.264 Transcoder using Selective Encryption

In digital broadcast TV systems, video data is normally encrypted before transmission. For in-home redistribution, it is often necessary to transcode the bitstream to achieve optimum utilization of available bandwidth. If a signal is decrypted before transcoding and re-encrypted, this may lead to a security loophole. This paper presents a solution in the form of a novel H.264 selective encryption algorithm that encrypts sign bits of transform coefficients and motion vectors to allow secure transcoding without decryption. The performance of this system is compared with I-frame encryption. The results show that sign encryption is more secure than I-frame encryption and has a lower complexity. A hybrid system using a modified transcoder and sign encryption is found to give an optimal compromise between security and transcoding performance.

Video coding using a fast non-separable matching pursuits algorithm

This paper presents a fast matching pursuits algorithm. In addition to a fast implementation, the algorithm also allows the efficient use of non-separable dictionary basis functions. The use of non-separable components allows basis functions which provide a better match to diagonally orientated image features. In order to demonstrate the proposed method, a simple dictionary is developed and used. Even without any sophisticated entropy coding, the proposed system gives performance exceeding that of H.263.

The design of low complexity two-channel lattice-structure perfect-reconstruction filter banks using genetic algorithms

This paper considers the design of reduced complexity 2 band QMF filter banks. In order to ensure perfect reconstruction, a lattice architecture has been adopted. Genetic algorithms are used to search for an optimal set of coefficients comprising simple sums of signed power of two terms. This allows the entire filter bank to be implemented using only additions and a single multiplicative scaling factor. Results are presented which show that the proposed method can be used to design filters with superior (in terms of minimax ripple) performance, compared to various infinite precision designs. Genetic algorithms can also be used to jointly optimise both performance and complexity in order to achieve an optimum performance/complexity trade off.

Still image coding for noisy channels

We examine how image coding schemes can be designed for noisy channels such as radio links, cordless telephones or mobile communications. We start with a JPEG based scheme and discuss its performance over channels with random and burst errors. We propose a number of modifications to the JPEG scheme including: avoiding DPCM coding of the DC coefficients; using a highly protected short header, the error resilient entropy code (EREC), error concealment and a wavelet transform. We show that these methods can improve the error resilience, without any significant increase of bit rate or loss of error free picture quality.<<ETX>>

Error resilient arithmetic coding of still images

This paper examines the use of arithmetic coding in conjunction with the error resilient entropy code (EREC). The constraints on the coding model are discussed and simulation results are presented and compared to those obtained using Huffman coding. These results show that without the EREC, arithmetic coding is less resilient than Huffman coding, while with the EREC both systems yield comparable results.

Unsupervised image compression-by-synthesis within a JPEG framework

An image compression scheme is proposed, utilising wavelet- based image segmentation and texture analysis, and patch- based texture synthesis. This has been incorporated into a JPEG framework. Homogeneous textured regions are identified and removed prior to transform coding. These regions are then replaced at the decoder by synthesis from marked samples, and colour matched to ensure similarity to the original. Experimental results on natural images show bitrate savings of over 18% compared with JPEG for little change in measured visual quality.

Optimization of image coding algorithms and architectures using genetic algorithms

This paper addresses the application of genetic algorithm (GA)-based optimization techniques to problems in image and video coding, demonstrating the success of GAs when used to solve real design problems with both performance and implementation constraints. Issues considered include problem representation, problem complexity, and fitness evaluation methods. For offline problems, such as the design of two-dimensional filters and filter banks, GAs are shown to be capable of producing results superior to conventional approaches. In the case of problems with real-time constraints, such as motion estimation, fractal search and vector quantization codebook design, GAs can provide solutions superior to those reported using conventional techniques with comparable implementation complexity. The use of GAs to jointly optimize algorithm performance in the context of a selected implementation strategy is emphasized throughout and several design examples are included.