VESA (The Video Electronics Standards Association) is developing a standard for a visually lossless codingsystem to be used for the compression of high-bandwidth display data streams. This codingsystem will compleme...
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ISBN:
(纸本)9781629938370
VESA (The Video Electronics Standards Association) is developing a standard for a visually lossless codingsystem to be used for the compression of high-bandwidth display data streams. This codingsystem will complement digital display interface technologies to increase pixel rates or save system power, or both. The display stream codingsystem is primarily being designed to meet the increased pixel rate needed in high resolution displays expected in the next few years. — This paper recounts VESA's process that led to compression requirements, the selection of a codingsystem baseline, and strategies to evaluate a visually lossless codingsystem for consumer electronics and commercial displays. Key concepts in this paper evolved from discussions and documents of VESA's Display Stream Compression Task Group that have been made available to the author with permission from VESA. The Display Stream Compression Standard is forthcoming for publication in the first quarter of 2014.
Fractal codification of images is based on self-similar and self-affine sets. The codification process consists of construction of an operator which will represent the image to be encoded. If a complicated picture can...
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Fractal codification of images is based on self-similar and self-affine sets. The codification process consists of construction of an operator which will represent the image to be encoded. If a complicated picture can be represented by an operator then it will be transmitted or stored very efficiently. Clearly, this has many applications on data compression. The great disadvantage of the automatic form of fractal compression is its encoding time. Most of the time spent in construction of such operator is due on finding the best match between parts of the image to be encoded. However, since the conception of automatic fractal image compression, researches on improvement of the compression time are widespread. This work aims to provide a new idea for decrease the encoding time: a classification of image parts based on their local fractal dimension. The idea is implemented on two steps. First, a preprocessing analysis of the image identify the complexity of each image block computing its dimension. Then, only parts within the same range of complexity are used for testing the better self-affine pairs, reducing the compression time. The performance of this proposition, is compared with others fractal image compression methods. The points considered are image fidelity, encoding time and amount of compression on the image file.
A new fractal-based image compression system, based on a so-called Adaptive Side-Coupling Quadtree (ASCQ) structure, is proposed. The proposed system consists of three processes: a preprocessing, a compression and a d...
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A new fractal-based image compression system, based on a so-called Adaptive Side-Coupling Quadtree (ASCQ) structure, is proposed. The proposed system consists of three processes: a preprocessing, a compression and a decompression process. In the compression process, the original image is represented by an ASCQ structure. The set of Iterated Function system (IFS) codes, which is usually derived in the encoding process, can be calculated directly from this tree structure. Using these IFS codes, an image which is similar to the original one can be reconstructed. Unlike traditional methods, which have separate domain and range pools, the proposed ASCQ structure simultaneously contains the domain pool and range pool. Since the proposed ASCQ is an adaptive structure, the number of IFS codes will be variant depending on their corresponding original images. Experimental results show that the ASCQ structure is indeed an efficient structure for the fractal-based image compression system.
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