Hybrid video coding is known for a long time and is applied in all video coding standards such as MPEG-x or H.26x.
This paper shows that there is still enough potential for further coding efficiency improvements. The paper starts with
an overview of state-of-the-art hybrid video coding schemes such as H.264/AVC. Thereafter, our advances on main
building blocks of H.264/AVC are presented that significantly improve the coding efficiency. For instance, intra prediction
is improved by changing scan directions and thus providing better reference pixels for specific prediction directions.
Adaptive filtering and high precision motion compensation improves the motion compensated prediction. Furthermore,
the combination of transformation, quantization, and entropy coding of the prediction error is improved using
an advanced frequency selective coding technique. With the transmission of post-filter hints it is possible to design a
Wiener post-filter that significantly enhances the picture quality. Finally, texture synthesis techniques are used to improve
the subjective quality for specific textures with homogenous statistical characteristics. This paper presents our
above-mentioned techniques in detail. Depending on the input sequence and the bit rate, the objective and/or subjective
gains compared to H.264/AVC are quite significant.
Authentication watermarking approaches can be classified into two kinds: fragile and semi-fragile. In contrast to the latter one, fragile watermarking does not tolerate modifications of any single bit of the watermarked data. Since the transmission of digital data often requires lossy compression, an authentication system should accept non-malicious modifications such as JPEG compression. Semi-fragile techniques aim to discriminate malicious manipulations from admissible manipulations. In our approach, we extract image content dependent information, which is hashed afterwards and encrypted using secure methods known from the classical cryptography. The image data is partitioned into nonoverlapping 4x4 pixel blocks in the spatial domain. The mean values of these blocks form n-dimensional vectors, which are quantized to the nearest lattice point neighbours. Based on the changed vector values, a hash is calculated and asymmetrically encrypted, resulting in a digital signature. Traditional dual subspace approaches divide the signal space into a region for signature generation and a region for signature embedding. To ensure the security of the whole image, we join the two subspaces. The vectors, where to embed the bits using quantization-based data hiding techniques, are predistorted and also used for the signature generation. Our scheme applies error correction coding to gain the robustness of the embedded signature to non-malicious distortions. A second quantization run finally embeds the signature.
Autostereoscopic displays support vertical and horizontal head movements in front of the screen. Although the number of views is limited in the vertical and horizontal direction, the amount of data, which has to be stored or transmitted for these multi-view images, is huge compared to a single image. Therefore compression algorithms have to be used to remove the data redundany. In this paper, we propose a multi-level 4d-DWT to transform multi-view images. This novel approach is able to concentrate the energy of a multi-view image much better than any two-dimensional or three-dimensional transform suggested so far. Therefore much higher compression ratios can be reached. In our paper, we further focus on progressive
coding of disparity maps. This approach is inevitable, because the estimated disparity map is only optimal for the target bit rate. In contrast to other approaches, a high-resolution depth map can be reconstructed at the end of the decoding process.
Multi-view images visualized by autostereoscopic displays are a heavy load for networks. The amount of data which has to be stored and transmitted is huge compared to mono-view images. In this paper, we show, that the upcoming ITU-T H.264 standard, which is designed to compress moving pictures, is also suited to code multi-view images after some minor modifications. This upcoming standard is even capable of outperforming the best stereo image coders known so far. It is only lacking the ability to code multi-view images progressively, and it is missing the multi-resolution property of wavelet-based coders.
In this paper, we propose a coder based on the Discrete Multiwavelet Transform, block-based disparity estimation and interpolation. By using the Discrete Multiwavelet Transform instead of the popular Discrete Cosine Transform we avoid artifacts which appear at low bit rates in the reconstructed stereo image and which do not only affect the subjective quality of each image individually, but also the depth perception. Our existing coder consists of an adapted state-of-the-art still image coder. The correlation between the two images is exploited by disparity compensation using overlapping blocks. Since the full-search block matching algorithm is very time-consuming, an interpolation factor of two has been used by our coder so far. However, to be able to improve the disparity compensation for certain images, our coder is upgraded by increasing the interpolation factor. To prevent an immense slow-down, faster search algorithms could be implemented. These faster algorithms can reduce the search space considerably. They do not give optimal compensation results, but in conjunction with a higher interpolation factors, they still can improve the performance. The results published in this paper are competitive.
This paper deals with the efficient storage and transmission of stereo images. It introduces a compression algorithm based on the Discrete Wavelet Transform and an adapted SPIHT-coder. By using objective quality tests, it is shown that this coder is superior to all other coders published so far.
KEYWORDS: Image compression, Transform theory, Image quality, Quantization, Signal processing, Signal analysis, Signal analyzers, Electronics, Video coding, Video compression
In this paper, new methods to eliminate boundary artifacts for overlapping trigonometric bases used in image compression are introduced. By applying overlapping cosine-sine-II bases to images instead of non-overlapping cosine-II bases used in the JPEG algorithm, block artifacts can be reduced. In contrast to non-overlapping transforms, an extension of the signal at the signal bounds is necessary. To prevent boundary artifacts in the reconstructed image, the symmetric periodic extension is preferred in image coding. The cosine-II and sine-II basis functions are symmetric, but nevertheless a conventional symmetric periodic extension is not possible, because different basis functions are used in adjacent intervals. In this paper, we derive weighting functions to make the symmetric periodic extension for these bases possible. We show, that compared to the periodic extension, no visible artifacts appear in the reconstructed image if our new approach is used. In addition, we show that the adaptation of the basis functions at the signal boundaries leads to a better quality of the reconstructed signal.
KEYWORDS: Transform theory, Image compression, Signal analyzers, Quantization, Signal analysis, Video compression, Video, Reconstruction algorithms, Electronics, Video coding
In this paper, we introduce new approaches to remove the boundary artifacts of the reconstructed images caused by transforms using overlapping non-symmetrical cosine-IV bases in image compression. In the field of image compression, overlapping cosine-IV bases can reduce the block artifacts that occur in JPEG. These basis functions are longer than the block size and they decay to zero at their boundaries. These cosine-IV bases have, however, one important disadvantage. They are not symmetric. Therefore the symmetric periodic extension cannot be applied to sequences of finite length. Artifacts appear at low bit rates in image compression if only the periodic extension is used. With the aid of the folding operator, we derive the symmetric periodic extension for cosine-IV bases. Weighting functions are introduced. We point out that no artifacts appear at image boundaries if our weighting functions are used. In the second part of our paper, we present a new approach which avoids the extension of the image. There is no overlap at the image boundaries. The efficiency of our proposed methods in image compression is studied. We show, that there are no artifacts at image boundaries in the reconstructed image if our methods are used.
In this paper, the symmetric periodic extension method is generalized for multiwavelet filter banks. It is described how the sequences should be extended for any symmetry type of multifilter of size two and the corresponding pre- /postfilter and how the filtered sequence should be downsampled. The present paper shows that there are restrictions for any symmetry type of multifilter relating to the size of the sequence and the type of pre-/postfilter. Examples are given. The symmetric periodic extension method is compared with the periodic extension method and the effects on the transformed sequence are discussed.
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