Rate-control algorithms for non-embedded wavelet-based image coding

During the last decade, there has been an increasing interest in the design of very fast wavelet image encoders focused on specific applications like interactive real-time image and video systems, running on power-constrained devices such as digital cameras, mobile phones where coding delay and/or available computing resources (working memory and power processing) are critical for proper operation. In order to reduce complexity, most of these fast wavelet image encoders are non-(SNR)-embedded and as a consequence, precise rate control is not supported. In this work, we propose some simple rate control algorithms for these kind of encoders and we analyze their impact to determine if, despite their inclusion, the global encoder is still competitive with respect to popular embedded encoders like SPIHT and JPEG2000. In this study we focus on the non-embedded LTW encoder, showing that the increase in complexity due to the rate control algorithm inclusion, maintains LTW competitive with respect to SPIHT and JPEG2000 in terms of R/D performance, coding delay and memory consumption. © Springer Science+Business Media, LLC 2011This work was funded by Spanish Ministry of education and Science under grant DPI2007-66796-C03-03.Lopez Granado, OM.; Onofre Martinez-Rach, M.; Pinol Peral, P.; Oliver Gil, JS.; Perez Malumbres, MJ. (2012). Rate-control algorithms for non-embedded wavelet-based image coding. Journal of Signal Processing Systems. 68(2):203-216. https://doi.org/10.1007/s11265-011-0598-6S203216682Antonini, M., Barlaud, M., Mathieu, P., & Daubechies, I. (1992). Image coding using wavelet transform. IEEE Transaction on Image Processing, 1(2), 205–220.Cho, Y., & Pearlman, W.A. (2007). Hierarchical dynamic range coding of wavelet subbands for fast and efficient image compression. IEEE Transactions on Image Processing, 16, 2005–2015.Chrysafis, C., Said, A., Drukarev, A., Islam, A., & Pearlman, W. (2000). SBHP—A low complexity wavelet coder. In IEEE international conference on acoustics, speech and signal processing.CIPR: http://www.cipr.rpi.edu/resource/stills/kodak.html . Center for Image Processing Research.Davis, P. J. (1975) Interpolation and approximation. Dover Publications.Grottke, S., Richter, T., & Seiler, R. (2006). Apriori rate allocation in wavelet-based image compression. In Second international conference on automated production of cross media content for multi-channel distribution, 2006. AXMEDIS ’06 (pp. 329–336). doi: 10.1109/AXMEDIS.2006.12 .Guo, J., Mitra, S., Nutter, B., & Karp, T. (2006). Backward coding of wavelet trees with fine-grained bitrate control. Journal of Computers, 1(4), 1–7. doi: 10.4304/jcp.1.4.1-7 .ISO/IEC 10918-1/ITU-T Recommendation T.81 (1992). Digital compression and coding of continuous-tone still image.ISO/IEC 15444-1 (2000). JPEG2000 image coding system.Kakadu, S. (2006). http://www.kakadusoftware.com .Kasner, J., Marcellin, M., & Hunt, B. (1999). Universal trellis coded quantization. IEEE Transactions on Image Processing, 8(12), 1677–1687. doi: 10.1109/83.806615 .Lancaster, P. (1986). Curve and surface fitting: An introduction. Academic Press.Oliver, J., & Malumbres, M. (2001). A new fast lower-tree wavelet image encoder. In Proceedings of international conference on image processing, 2001 (Vol. 3, pp. 780–783). doi: 10.1109/ICIP.2001.958236 .Oliver, J., & Malumbres, M. P. (2006). Low-complexity multiresolution image compression using wavelet lower trees. IEEE Transactions on Circuits and Systems for Video Technology, 16(11), 1437–1444.Pearlman, W. A. (2001). Trends of tree-based, set partitioning compression techniques in still and moving image systems. In Picture coding symposium.Said, A., & Pearlman, A. (1996). A new, fast and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits, Systems and Video Technology, 6(3), 243–250.Table Curve 3D 3.0 (1998). http://www.systat.com. Systat Software Inc.Wu, X. (2001). The transform and data compression handbook, chap. Compression of wavelet transform coefficients, (pp. 347–378). CRC Press.Zhidkov, N., & Kobelkov, G. (1987). Numerical methods. Moscow: Nauka

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Setting priorities: a new SPIHT-compatible algorithm for image compression

We introduce a new algorithm for progressive or multiresolution image compression. The algorithm improves on the Set Partitioning in Hierarchical Trees (SPIHT) algorithm by replacing the SPIHT encoder. The new encoder optimizes the multiresolution code performance relative to a user- defined probability distribution over the code's rates or resolutions. The new algorithm's decoder is identical to the SPIHT decoder. The resulting code achieves the optimal expected performance across resolutions subject to the constraints imposed by the use of the SPIHT decoder and the distribution over resolutions set by the user. The encoder optimization yields performance improvements at the rates or resolutions of greatest importance at the expense of performance degradation at low priority rates or resolutions. The algorithm is fully compatible at the decoder with the original SPIHT algorithm. In particular, the decoder requires no knowledge of the priority function employed at the encoder. Experimental results on an image containing both text and photographic material yield up to 0.86 dB performance improvement over SPIHT at the resolution of highest priority

On the design of fast and efficient wavelet image coders with reduced memory usage

Image compression is of great importance in multimedia systems and applications because it drastically reduces bandwidth requirements for transmission and memory requirements for storage. Although earlier standards for image compression were based on the Discrete Cosine Transform (DCT), a recently developed mathematical technique, called Discrete Wavelet Transform (DWT), has been found to be more efficient for image coding. Despite improvements in compression efficiency, wavelet image coders significantly increase memory usage and complexity when compared with DCT-based coders. A major reason for the high memory requirements is that the usual algorithm to compute the wavelet transform requires the entire image to be in memory. Although some proposals reduce the memory usage, they present problems that hinder their implementation. In addition, some wavelet image coders, like SPIHT (which has become a benchmark for wavelet coding), always need to hold the entire image in memory. Regarding the complexity of the coders, SPIHT can be considered quite complex because it performs bit-plane coding with multiple image scans. The wavelet-based JPEG 2000 standard is still more complex because it improves coding efficiency through time-consuming methods, such as an iterative optimization algorithm based on the Lagrange multiplier method, and high-order context modeling. In this thesis, we aim to reduce memory usage and complexity in wavelet-based image coding, while preserving compression efficiency. To this end, a run-length encoder and a tree-based wavelet encoder are proposed. In addition, a new algorithm to efficiently compute the wavelet transform is presented. This algorithm achieves low memory consumption using line-by-line processing, and it employs recursion to automatically place the order in which the wavelet transform is computed, solving some synchronization problems that have not been tackled by previous proposals. The proposed encodeOliver Gil, JS. (2006). On the design of fast and efficient wavelet image coders with reduced memory usage [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1826Palanci

Wavelet-Neural Network Based Image Compression System for Colour Images

There are many images used by human being, such as medical, satellite, telescope, painting, and graphic or animation generated by computer images. In order to use these images practically, image compression method has an essential role for transmission and storage purposes. In this research, a wavelet based image compression technique is used. There are various wavelet filters available. The selection of filters has considerable impact on the compression performance. The filter which is suitable for one image may not be the best for another. The image characteristics are expected to be parameters that can be used to select the available wavelet filter. The main objective of this research is to develop an automatic wavelet-based colour image compression system using neural network. The system should select the appropriate wavelet for the image compression based on the image features. In order to reach the main goal, this study observes the cause-effect relation of image features on the wavelet codec (compression-decompression) performance. The images are compressed by applying different families of wavelets. Statistical hypothesis testing by non parametric test is used to establish the cause-effect relation between image features and the wavelet codec performance measurements. The image features used are image gradient, namely image activity measurement (IAM) and spatial frequency (SF) values of each colour component. This research is also carried out to select the most appropriate wavelet for colour image compression, based on certain image features using artificial neural network (ANN) as a tool. The IAM and SF values are used as the input; therefore, the wavelet filters are used as the output or target in the network training. This research has asserted that there are the cause-effect relations between image features and the wavelet codec performance measurements. Furthermore, the study reveals that the parameters in this investigation can be used for the selection of appropriate wavelet filters. An automatic wavelet-based colour image compression system using neural network is developed. The system can give considerably good results

State-of-the-Art and Trends in Scalable Video Compression with Wavelet Based Approaches

3noScalable Video Coding (SVC) differs form traditional single point approaches mainly because it allows to encode in a unique bit stream several working points corresponding to different quality, picture size and frame rate. This work describes the current state-of-the-art in SVC, focusing on wavelet based motion-compensated approaches (WSVC). It reviews individual components that have been designed to address the problem over the years and how such components are typically combined to achieve meaningful WSVC architectures. Coding schemes which mainly differ from the space-time order in which the wavelet transforms operate are here compared, discussing strengths and weaknesses of the resulting implementations. An evaluation of the achievable coding performances is provided considering the reference architectures studied and developed by ISO/MPEG in its exploration on WSVC. The paper also attempts to draw a list of major differences between wavelet based solutions and the SVC standard jointly targeted by ITU and ISO/MPEG. A major emphasis is devoted to a promising WSVC solution, named STP-tool, which presents architectural similarities with respect to the SVC standard. The paper ends drawing some evolution trends for WSVC systems and giving insights on video coding applications which could benefit by a wavelet based approach.partially_openpartially_openADAMI N; SIGNORONI. A; R. LEONARDIAdami, Nicola; Signoroni, Alberto; Leonardi, Riccard

Algorithms for compression of high dynamic range images and video

The recent advances in sensor and display technologies have brought upon the High Dynamic Range (HDR) imaging capability. The modern multiple exposure HDR sensors can achieve the dynamic range of 100-120 dB and LED and OLED display devices have contrast ratios of 10^5:1 to 10^6:1. Despite the above advances in technology the image/video compression algorithms and associated hardware are yet based on Standard Dynamic Range (SDR) technology, i.e. they operate within an effective dynamic range of up to 70 dB for 8 bit gamma corrected images. Further the existing infrastructure for content distribution is also designed for SDR, which creates interoperability problems with true HDR capture and display equipment. The current solutions for the above problem include tone mapping the HDR content to fit SDR. However this approach leads to image quality associated problems, when strong dynamic range compression is applied. Even though some HDR-only solutions have been proposed in literature, they are not interoperable with current SDR infrastructure and are thus typically used in closed systems. Given the above observations a research gap was identified in the need for efficient algorithms for the compression of still images and video, which are capable of storing full dynamic range and colour gamut of HDR images and at the same time backward compatible with existing SDR infrastructure. To improve the usability of SDR content it is vital that any such algorithms should accommodate different tone mapping operators, including those that are spatially non-uniform. In the course of the research presented in this thesis a novel two layer CODEC architecture is introduced for both HDR image and video coding. Further a universal and computationally efficient approximation of the tone mapping operator is developed and presented. It is shown that the use of perceptually uniform colourspaces for internal representation of pixel data enables improved compression efficiency of the algorithms. Further proposed novel approaches to the compression of metadata for the tone mapping operator is shown to improve compression performance for low bitrate video content. Multiple compression algorithms are designed, implemented and compared and quality-complexity trade-offs are identified. Finally practical aspects of implementing the developed algorithms are explored by automating the design space exploration flow and integrating the high level systems design framework with domain specific tools for synthesis and simulation of multiprocessor systems. The directions for further work are also presented

Contributions in image and video coding

Orientador: Max Henrique Machado CostaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A comunidade de codificação de imagens e vídeo vem também trabalhando em inovações que vão além das tradicionais técnicas de codificação de imagens e vídeo. Este trabalho é um conjunto de contribuições a vários tópicos que têm recebido crescente interesse de pesquisadores na comunidade, nominalmente, codificação escalável, codificação de baixa complexidade para dispositivos móveis, codificação de vídeo de múltiplas vistas e codificação adaptativa em tempo real. A primeira contribuição estuda o desempenho de três transformadas 3-D rápidas por blocos em um codificador de vídeo de baixa complexidade. O codificador recebeu o nome de Fast Embedded Video Codec (FEVC). Novos métodos de implementação e ordens de varredura são propostos para as transformadas. Os coeficiente 3-D são codificados por planos de bits pelos codificadores de entropia, produzindo um fluxo de bits (bitstream) de saída totalmente embutida. Todas as implementações são feitas usando arquitetura com aritmética inteira de 16 bits. Somente adições e deslocamentos de bits são necessários, o que reduz a complexidade computacional. Mesmo com essas restrições, um bom desempenho em termos de taxa de bits versus distorção pôde ser obtido e os tempos de codificação são significativamente menores (em torno de 160 vezes) quando comparados ao padrão H.264/AVC. A segunda contribuição é a otimização de uma recente abordagem proposta para codificação de vídeo de múltiplas vistas em aplicações de video-conferência e outras aplicações do tipo "unicast" similares. O cenário alvo nessa abordagem é fornecer vídeo com percepção real em 3-D e ponto de vista livre a boas taxas de compressão. Para atingir tal objetivo, pesos são atribuídos a cada vista e mapeados em parâmetros de quantização. Neste trabalho, o mapeamento ad-hoc anteriormente proposto entre pesos e parâmetros de quantização é mostrado ser quase-ótimo para uma fonte Gaussiana e um mapeamento ótimo é derivado para fonte típicas de vídeo. A terceira contribuição explora várias estratégias para varredura adaptativa dos coeficientes da transformada no padrão JPEG XR. A ordem de varredura original, global e adaptativa do JPEG XR é comparada com os métodos de varredura localizados e híbridos propostos neste trabalho. Essas novas ordens não requerem mudanças nem nos outros estágios de codificação e decodificação, nem na definição da bitstream A quarta e última contribuição propõe uma transformada por blocos dependente do sinal. As transformadas hierárquicas usualmente exploram a informação residual entre os níveis no estágio da codificação de entropia, mas não no estágio da transformada. A transformada proposta neste trabalho é uma técnica de compactação de energia que também explora as similaridades estruturais entre os níveis de resolução. A idéia central da técnica é incluir na transformada hierárquica um número de funções de base adaptativas derivadas da resolução menor do sinal. Um codificador de imagens completo foi desenvolvido para medir o desempenho da nova transformada e os resultados obtidos são discutidos neste trabalhoAbstract: The image and video coding community has often been working on new advances that go beyond traditional image and video architectures. This work is a set of contributions to various topics that have received increasing attention from researchers in the community, namely, scalable coding, low-complexity coding for portable devices, multiview video coding and run-time adaptive coding. The first contribution studies the performance of three fast block-based 3-D transforms in a low complexity video codec. The codec has received the name Fast Embedded Video Codec (FEVC). New implementation methods and scanning orders are proposed for the transforms. The 3-D coefficients are encoded bit-plane by bit-plane by entropy coders, producing a fully embedded output bitstream. All implementation is performed using 16-bit integer arithmetic. Only additions and bit shifts are necessary, thus lowering computational complexity. Even with these constraints, reasonable rate versus distortion performance can be achieved and the encoding time is significantly smaller (around 160 times) when compared to the H.264/AVC standard. The second contribution is the optimization of a recent approach proposed for multiview video coding in videoconferencing applications or other similar unicast-like applications. The target scenario in this approach is providing realistic 3-D video with free viewpoint video at good compression rates. To achieve such an objective, weights are computed for each view and mapped into quantization parameters. In this work, the previously proposed ad-hoc mapping between weights and quantization parameters is shown to be quasi-optimum for a Gaussian source and an optimum mapping is derived for a typical video source. The third contribution exploits several strategies for adaptive scanning of transform coefficients in the JPEG XR standard. The original global adaptive scanning order applied in JPEG XR is compared with the localized and hybrid scanning methods proposed in this work. These new orders do not require changes in either the other coding and decoding stages or in the bitstream definition. The fourth and last contribution proposes an hierarchical signal dependent block-based transform. Hierarchical transforms usually exploit the residual cross-level information at the entropy coding step, but not at the transform step. The transform proposed in this work is an energy compaction technique that can also exploit these cross-resolution-level structural similarities. The core idea of the technique is to include in the hierarchical transform a number of adaptive basis functions derived from the lower resolution of the signal. A full image codec is developed in order to measure the performance of the new transform and the obtained results are discussed in this workDoutoradoTelecomunicações e TelemáticaDoutor em Engenharia Elétric