Wavelet Based Color Image Compression and Mathematical Analysis of Sign Entropy Coding

International audienceOne of the advantages of the Discrete Wavelet Transform (DWT) compared to Fourier Transform (e.g. Discrete Cosine Transform DCT) is its ability to provide both spatial and frequency localization of image energy. However, WT coefficients, like DCT coefficients, are defined by magnitude as well as sign. While algorithms exist for the coding of wavelet coefficients magnitude, there are no efficient for coding their sign. In this paper, we propose a new method based on separate entropy coding of sign and magnitude of wavelet coefficients. The proposed method is applied to the standard color test images Lena, Peppers, and Mandrill. We have shown that sign information of wavelet coefficients as well for the luminance as for the chrominance, and the refinement information of the quantized wavelet coefficients may not be encoded by an estimated probability of 0.5. The proposed method is evaluated; the results obtained are compared to JPEG2000 and SPIHT codec. We have shown that the proposed method has significantly outperformed the JPEG2000 and SPIHT codec as well in terms of PSNR as in subjective quality. We have proved, by an original mathematical analysis of the entropy, that the proposed method uses a minimum bit allocation in the sign information coding

Development of Some Efficient Lossless and Lossy Hybrid Image Compression Schemes

Digital imaging generates a large amount of data which needs to be compressed, without loss of relevant information, to economize storage space and allow speedy data transfer. Though both storage and transmission medium capacities have been continuously increasing over the last two decades, they dont match the present requirement. Many lossless and lossy image compression schemes exist for compression of images in space domain and transform domain. Employing more than one traditional image compression algorithms results in hybrid image compression techniques. Based on the existing schemes, novel hybrid image compression schemes are developed in this doctoral research work, to compress the images effectually maintaining the quality

Contributions for post processing of wavelet transform with SPIHT ROI coding and application in the transmission of images

Orientador: Yuzo IanoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A área que trata de compressão de imagem com perdas é, atualmente, de grande importância. Isso se deve ao fato de que as técnicas de compressão permitem representar de uma forma eficiente uma imagem reduzindo assim, o espaço necessário para armazenamento ou um posterior envio da imagem através de um canal de comunicações. Em particular, o algoritmo SPIHT (Set Partitioning of Hierarchical Trees) muito usado em compressão de imagens é de implementação simples e pode ser aproveitado em aplicações onde se requer uma baixa complexidade. Este trabalho propõe um esquema de compressão de imagens utilizando uma forma personalizada de armazenamento da transformada DWT (Discrete Wavelet Transform), codificação flexível da ROI (Region Of Interest) e a compressão de imagens usando o algoritmo SPIHT. A aplicação consiste na transmissão dos dados correspondentes usando-se codificação turbo. A forma personalizada de armazenamento da DWT visa um melhor aproveitamento da memória por meio do uso de algoritmo SPIHT. A codificação ROI genérica é aplicada em um nível alto da decomposição DWT. Nesse ponto, o algoritmo SPIHT serve para ressaltar e transmitir com prioridade as regiões de interesse. Os dados a serem transmitidos, visando o menor custo de processamento, são codificados com um esquema turbo convolucional. Isso porque esse esquema é de implementação simples no que concerne à codificação. A simulação é implementada em módulos separados e reutilizáveis para esta pesquisa. Os resultados das simulações mostram que o esquema proposto é uma solução que diminui a quantidade de memória utilizada bem como o custo computacional para aplicações de envio de imagens em aplicações como transmissão de imagens via satélite, radiodifusão e outras mídiasAbstract: Nowadays, the area that comes to lossy image compression is really important. This is due to the fact that compression techniques allow an efficient way to represent an image thereby reducing the space required for storage or subsequent submission of an image through a communications channel. In particular, the algorithm SPIHT (Set Partitioning of Hierarchical Trees) widely used in image compression is simple to implement and can be used in applications where a low complexity is required. This study proposes an image compression scheme using a personalized storage transform DWT (Discrete Wavelet Transform), encoding flexible ROI (Region Of Interest) and image compression algorithm using SPIHT. The application consists in a transmission of the corresponding data using turbo coding. The shape of the custom storage DWT aims to make better use of memory by reducing the amount of memory through the use of SPIHT algorithm. ROI coding is applied in a generic high-level DWT decomposition. At this point, the algorithm serves to highlight SPITH and transmit the priority areas of interest. The data to be transmitted in order to lower the cost of processing are encoded with a turbo convolutional scheme. This is due this scheme is simple to implement with regard to coding. The simulation is implemented in separate modules and reusable for this research. The simulations and analysis show that the proposed scheme is a solution that decreases the amount of memory used and the computational cost for applications to send images in applications such as image transmission via satellite, broadcasting and others mediasDoutoradoTelecomunicações e TelemáticaDoutor em Engenharia Elétric