Rateless Lossy Compression via the Extremes
نویسندگان
چکیده
منابع مشابه
Unsupervised segmentation of natural images via lossy data compression
In this paper, we cast natural-image segmentation as a problem of clustering texture features as multivariate mixed data. We model the distribution of the texture features using a mixture of Gaussian distributions. Unlike most existing clustering methods, we allow the mixture components to be degenerate or nearly-degenerate. We contend that this assumption is particularly important for mid-leve...
متن کاملThe evolution of lossy compression
In complex environments, there are costs to both ignorance and perception. An organism needs to track fitness-relevant information about its world, but the more information it tracks, the more resources it must devote to perception. As a first step towards a general understanding of this trade-off, we use a tool from information theory, rate-distortion theory, to study large, unstructured envir...
متن کاملImproved Lossy Compression of Deep Space Images via Genetic Algorithms
Most of the images transmitted from deep space probes to Earth are subject to lossy compression. Recent NASA missions have used the ICER progressive wavelet image compressor to achieve state-of-the-art compression performance. The purpose of the research described in this paper was to demonstrate that it is possible to evolve wavelet and scaling numbers describing novel transforms that outperfo...
متن کاملLossy Compression of Quality Values via Rate Distortion Theory
Motivation: Next Generation Sequencing technologies revolutionized many fields in biology by enabling the fast and cheap sequencing of large amounts of genomic data. The ever increasing sequencing capacities enabled by current sequencing machines hold a lot of promise as for the future applications of these technologies, but also create increasing computational challenges related to the analysi...
متن کاملImage Denoising via Lossy Compression and Wavelet Thresholding
S. Grace Chang1 Bin Yu2 Martin Vetterli1;3 1Department of Electrical Engineering and Computer Sciences University of California, Berkeley, CA 94720, USA 2Department of Statistics University of California, Berkeley, CA 94720, USA 3D epartement d'Electricit e Ecole Polytechnique F ed erale de Lausanne, CH-1015 Lausanne, Switzerland [email protected], [email protected], [email protected]...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2016
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2016.2598148