Catálogo de publicaciones - libros

Many desirable properties make fractals a powerful mathematic model applied in several image processing and pattern recognition tasks: image coding, segmentation, feature extraction and indexing, just to cite some of them. Unfortunately, they are based on a strong asymmetric scheme, so suffering from very high coding times. On the other side, linear transforms are quite time balanced, allowing to be usefully integrated in real-time applications, but they do not provide comparable performances with respect to the image quality for high bit rates. Owning to their potential for preserving the original image energy in a few coefficients in the frequency domain, linear transforms also known a widespread diffusion in some side applications such as to select representative features or to define new image quality measures. In this paper, we investigate different levels of embedding linear transforms in a fractal based coding scheme. Experimental results have been organized as to point out what is the contribution of each embedding step to the objective quality of the decoded image.

Principal Components Analysis (PCA) is a valuable technique for dimensionality reduction purposes for huge datasets. Principal components are linear combination of the original variables. The projection of data on this linear subspace keeps the most of the original characteristics. This helps to find robust characteristics for watermarking applications. Most of the PCA based watermarking methods were done in projection space i.e. in eigen image. In this study, different from the other methods, PCA is used to obtain a reference of the cover image by using compression property of PCA. PCA and block-PCA based methods are proposed by using some of the principal vectors in reconstruction. The watermarking is done according to difference of the original and its reference image. The method is compared with Discrete Wavelet Transform (DWT) based approach and its performance against some attacks is discussed.

This work introduces techniques addressed to enhance the coding performance obtained when compressing images that contain areas with irrelevant information, here called . No-data regions can be produced due to several factors, such as geometric corrections, overlapping of successive layers of information, a malfunction of the sensor used to capture the image, etc. Most coding systems are not devised to consider such regions separately from the rest of the image, sometimes causing an important loss in the coding efficiency. Within the framework JPEG2000, we propose five techniques that address this issue. Experimental results suggest that the application of the proposed techniques can achieve, in some cases, a compression gain of 130 over a compression without applying the proposed techniques.

Recently, we proposed a multiplierless 1D Int-DCT improved from our previous proposed Int-DCT by approximating floating multiplications to bit-shift and addition operations. The multiplierless 1D Int-DCT can be well operated both lossless coding and lossy coding. However, our multiplierless 1D Int-DCT is not focused on how to assign word-length for floating-multiplier approximation as short as possible for reduction of hardware complexity. In this paper, we propose a new Optimum-Word-Length-Assignment (OWLA) multiplierless Int-DCT. Apart from inexpensive hardware complexity, the new OWLA multiplierless 1D Int-DCT achieves high coding performance in both lossless and lossy coding. The lossless/lossy coding criterion is applied to evaluate coding performance of the proposed Int-DCT comparing to those of the others Int-DCT.

In this paper, we propose a generic hybrid oriented-transform and wavelet-based image representation for intra-band image coding. We instantiate for three popular directional transforms having similar powers of approximation but different redundancy factors. For each transform type, we design a compression scheme wherein we exploit intra-band coefficient dependencies. We show that our schemes outperform alternative approaches reported in literature. Moreover, on some images, we report that two of the proposed codec schemes outperform JPEG2000 by over 1dB. Finally, we investigate the trade-off between oversampling and sparsity and show that, at low rates, hybrid coding schemes with transform redundancy factors as high as 1.25 to 5.8 are capable in fact of outperforming JPEG2000 and its critically-sampled wavelets.

This paper reports an information-theoretic analysis of the dependencies that exist between curvelet coefficients. We show that strong dependencies exist in local intra-band micro-neighborhoods, and that the shape of these neighborhoods is highly anisotropic. With this respect, it is found that the two immediately adjacent neighbors that lie in a direction orthogonal to the orientation of the subband convey the most information about the coefficient. Moreover, taking into account a larger local neighborhood set than this brings only mild gains with respect to intra-band mutual information estimations. Furthermore, we point out that linear predictors do not represent sufficient statistics, if applied to the entire intra-band neighborhood of a coefficient. We conclude that intra-band dependencies are clearly the strongest, followed by their inter-orientation and inter-scale counterparts; in this respect, the more complex intra-band/inter-scale or intra-band/inter-orientation models bring only mild improvements over intra-band models. Finally, we exploit the coefficient dependencies in a curvelet-based image coding application and show that the scheme is comparable and in some cases even outperforms JPEG2000.

Watermarking is a technique used to embed copyright information in an image. In this paper, we propose a novel image compression method which embeds a part of the coding parameters, instead of the copyright information, into an own image. The proposed method is adapted for the JPEG coding process. In the proposed method for JPEG, the DC coefficients of the DCT transform are embedded into low-to-middle frequency terms of the AC coefficients. Therefore, the DC coefficients need not be transmitted separately, which results in less data being needed for encoding. On the decoder side, first, the data for the DC coefficients embedded in AC coefficients is extracted. After this, the data of the DC and AC coefficients allows for the reconstruction of the image. Experiments on the relation between data compression ratio and PSNR using a quantization scale factor as parameter are carried out. The experimental results show that the proposed method has achieved a 3.65% reduction of the quantity of image data, compared with the standard JPEG method, while maintaining nearly the same image quality.

This paper proposes an improved algorithm of the error-resilient entropy coding (EREC) to limit error propagation (EP) in variable-length-coding (VLC) bit stream. The main novelties include two folds. First, after each stage of EREC encoding process, the resulting states of all slots and blocks are conveyed as side information and used at decoders to remove the EP caused by those erroneous blocks/slots that have been placed-up/filled-up. Second, the alternate placement (AP) technique is proposed to alleviate the EP caused by those erroneous blocks/slots that are still partially-placed/partially-filled. An in-depth analysis shows that less than three bits per block are required for conveying state information. Experiments are conducted and the results show that our proposed method improves recovery quality significantly.